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Turkish Consumer Finance Company Quick Finans Selects Provenir’s AI-Powered Data and Decisioning Platform

<\/p>\n

Parsippany, NJ \u2014 Jan. 26, 2023 \u2014 <\/strong>Provenir, a global leader in data and AI-powered risk decisioning software, announced today that Quick Finans, a consumer finance company located in Turkey, has selected Provenir\u2019s AI-Powered Data and Decisioning Platform to quickly approve and onboard new customers.<\/p>\n

<\/p>\n

Quick Finans, a wholly owned subsidiary of Quick Insurance, which is under the umbrella of Maher Holding, offers solutions for consumer finance loans (GPL), auto financing, mortgages, agricultural financing, and small business lending. They were looking for a low\/no code platform that could be deployed quickly, modified in real-time and scale as the company expands its offerings.<\/p>\n

<\/p>\n

\u201cAfter evaluating several options, we determined that Provenir best met our requirements and could support our aggressive growth strategies,\u201d said Cumhur Ta\u015f \u2013 Deputy General Manager responsible for Credit & Operations in Quick Finans. \u201cThe platform provides the flexibility we need to power our business now and in the future. Another key differentiator was the ability to easily access and integrate new data sources to help us gain a more holistic view of our applicants and customers.\u201d<\/p>\n

<\/p>\n

\u201cWe are pleased to partner with Quick Finans to develop real-time decisioning solutions that will provide a superior customer experience,\u201d said Emre Unlusoy, Regional Manager for Provenir. \u201cProvenir\u2019s no-code, visual UI eliminates vendor and development team reliance, and will provide Quick Finans the flexibility and agility needed to rapidly make changes, test new strategies and get products to market faster.\u201d<\/p>\n

<\/p>\n

Provenir\u2019s industry-leading AI-Powered Data and Decisioning Platform is data fueled and AI driven for smarter risk decisioning. The solution, managed through a single UI, empowers organizations to innovate further and faster than ever before, driving the continuous optimization they need to power growth and agility, without increasing risk. With the unique combination of universal access to data, embedded AI and world-class decisioning technology, Provenir provides a cohesive risk ecosystem to enable smarter decisions across the entire customer lifecycle \u2013 offering diverse data for deeper insights, auto-optimized decisions, and a continuous feedback loop for constant improvement both at onboarding when assessing risk and monitoring ongoing transactions for fraud.<\/p>“,”margin”:”default”}}]},{“type”:”column”,”props”:{“image_position”:”center-center”,”padding”:”small”,”position_sticky”:”row”,”position_sticky_breakpoint”:”m”,”position_sticky_offset”:”100″,”style”:”card-default”,”width_medium”:”1-3″},”children”:[{“type”:”headline”,”props”:{“content”:”The Ultimate Guide to Decision Engines”,”text_align”:”center”,”title_color”:”success”,”title_element”:”h3″,”title_style”:”h3″}},{“type”:”text”,”props”:{“column_breakpoint”:”m”,”content”:”

What is a decision engine and how does it help your business processes?<\/p>“,”margin”:”default”,”text_align”:”center”}},{“type”:”button”,”props”:{“grid_column_gap”:”small”,”grid_row_gap”:””,”margin”:””,”margin_remove_bottom”:false,”maxwidth”:”medium”,”text_align”:”center”},”children”:[{“type”:”button_item”,”props”:{“button_style”:”default”,”content”:”Learn More”,”icon”:””,”icon_align”:”left”,”link”:”\/blog\/the-ultimate-guide-to-decision-engines\/”}}]}]}],”props”:{“layout”:”2-3,1-3″}}]},{“type”:”section”,”props”:{“image_position”:”center-center”,”style”:”secondary”,”title_breakpoint”:”xl”,”title_position”:”top-left”,”title_rotation”:”left”,”vertical_align”:””,”width”:”default”},”children”:[{“type”:”row”,”children”:[{“type”:”column”,”props”:{“image_position”:”center-center”,”position_sticky_breakpoint”:”m”},”children”:[{“type”:”divider”,”props”:{“divider_element”:”hr”}},{“type”:”headline”,”props”:{“content”:”LATEST NEWS”,”title_color”:”background”,”title_element”:”h1″,”title_style”:”text-large”}},{“type”:”grid”,”props”:{“content_column_breakpoint”:”m”,”filter_align”:”left”,”filter_all”:true,”filter_grid_breakpoint”:”m”,”filter_grid_width”:”auto”,”filter_position”:”top”,”filter_style”:”tab”,”grid_column_align”:false,”grid_default”:”auto”,”grid_divider”:true,”grid_large”:”3″,”grid_medium”:”3″,”grid_parallax_justify”:true,”grid_row_align”:false,”grid_xlarge”:”3″,”icon_width”:80,”image_align”:”top”,”image_grid_breakpoint”:”m”,”image_grid_width”:”1-2″,”image_link”:true,”image_svg_color”:”emphasis”,”image_transition”:”scale-up”,”image_transition_border”:false,”item_animation”:true,”link_size”:”small”,”link_style”:”default”,”link_text”:”Read more”,”margin”:”default”,”meta_align”:”below-title”,”meta_element”:”div”,”meta_style”:”text-meta”,”show_content”:true,”show_image”:true,”show_link”:true,”show_meta”:true,”show_title”:true,”title_align”:”top”,”title_color”:”success”,”title_element”:”h3″,”title_grid_breakpoint”:”m”,”title_grid_width”:”1-2″,”title_hover_style”:”reset”,”title_link”:true},”children”:[{“type”:”grid_item”,”source”:{“query”:{“name”:”posts.customPosts”,”arguments”:{“terms”:[52],”category_operator”:”IN”,”post_tag_operator”:”IN”,”users”:[],”users_operator”:”IN”,”offset”:0,”limit”:3,”order”:”date”,”order_direction”:”DESC”,”industry_operator”:”IN”,”language_operator”:”IN”,”resources_operator”:”IN”}},”props”:{“_condition”:{“filters”:{“condition”:”!!”},”name”:”author.name”},”title”:{“filters”:{“search”:””},”name”:”title”},”content”:{“filters”:{“search”:””,”limit”:100},”name”:”excerpt”},”image”:{“filters”:{“search”:””},”name”:”featuredImage.url”},”link”:{“filters”:{“search”:””},”name”:”link”}}}}]}]}]}]}],”version”:”4.4.1″} –>

The Ultimate Guide to Decision Engines

What is a decision engine and how does it help your business processes?

Learn More


LATEST NEWS

<\/p>\n

Provenir\u2019s no-code platform delivers rapid deployment, flexibility and scalability for a growing company<\/em><\/p>\n

<\/p>\n

Parsippany, NJ \u2014 Jan. 26, 2023 \u2014 <\/strong>Provenir, a global leader in data and AI-powered risk decisioning software, announced today that Quick Finans, a consumer finance company located in Turkey, has selected Provenir\u2019s AI-Powered Data and Decisioning Platform to quickly approve and onboard new customers.<\/p>\n

<\/p>\n

Quick Finans, a wholly owned subsidiary of Quick Insurance, which is under the umbrella of Maher Holding, offers solutions for consumer finance loans (GPL), auto financing, mortgages, agricultural financing, and small business lending. They were looking for a low\/no code platform that could be deployed quickly, modified in real-time and scale as the company expands its offerings.<\/p>\n

<\/p>\n

\u201cAfter evaluating several options, we determined that Provenir best met our requirements and could support our aggressive growth strategies,\u201d said Cumhur Ta\u015f \u2013 Deputy General Manager responsible for Credit & Operations in Quick Finans. \u201cThe platform provides the flexibility we need to power our business now and in the future. Another key differentiator was the ability to easily access and integrate new data sources to help us gain a more holistic view of our applicants and customers.\u201d<\/p>\n

<\/p>\n

\u201cWe are pleased to partner with Quick Finans to develop real-time decisioning solutions that will provide a superior customer experience,\u201d said Emre Unlusoy, Regional Manager for Provenir. \u201cProvenir\u2019s no-code, visual UI eliminates vendor and development team reliance, and will provide Quick Finans the flexibility and agility needed to rapidly make changes, test new strategies and get products to market faster.\u201d<\/p>\n

<\/p>\n

Provenir\u2019s industry-leading AI-Powered Data and Decisioning Platform is data fueled and AI driven for smarter risk decisioning. The solution, managed through a single UI, empowers organizations to innovate further and faster than ever before, driving the continuous optimization they need to power growth and agility, without increasing risk. With the unique combination of universal access to data, embedded AI and world-class decisioning technology, Provenir provides a cohesive risk ecosystem to enable smarter decisions across the entire customer lifecycle \u2013 offering diverse data for deeper insights, auto-optimized decisions, and a continuous feedback loop for constant improvement both at onboarding when assessing risk and monitoring ongoing transactions for fraud.<\/p>“,”margin”:”default”}}]},{“type”:”column”,”props”:{“image_position”:”center-center”,”padding”:”small”,”position_sticky”:”row”,”position_sticky_breakpoint”:”m”,”position_sticky_offset”:”100″,”style”:”card-default”,”width_medium”:”1-3″},”children”:[{“type”:”headline”,”props”:{“content”:”The Ultimate Guide to Decision Engines”,”text_align”:”center”,”title_color”:”success”,”title_element”:”h3″,”title_style”:”h3″}},{“type”:”text”,”props”:{“column_breakpoint”:”m”,”content”:”

What is a decision engine and how does it help your business processes?<\/p>“,”margin”:”default”,”text_align”:”center”}},{“type”:”button”,”props”:{“grid_column_gap”:”small”,”grid_row_gap”:””,”margin”:””,”margin_remove_bottom”:false,”maxwidth”:”medium”,”text_align”:”center”},”children”:[{“type”:”button_item”,”props”:{“button_style”:”default”,”content”:”Learn More”,”icon”:””,”icon_align”:”left”,”link”:”\/blog\/the-ultimate-guide-to-decision-engines\/”}}]}]}],”props”:{“layout”:”2-3,1-3″}}]},{“type”:”section”,”props”:{“image_position”:”center-center”,”style”:”secondary”,”title_breakpoint”:”xl”,”title_position”:”top-left”,”title_rotation”:”left”,”vertical_align”:””,”width”:”default”},”children”:[{“type”:”row”,”children”:[{“type”:”column”,”props”:{“image_position”:”center-center”,”position_sticky_breakpoint”:”m”},”children”:[{“type”:”divider”,”props”:{“divider_element”:”hr”}},{“type”:”headline”,”props”:{“content”:”LATEST NEWS”,”title_color”:”background”,”title_element”:”h1″,”title_style”:”text-large”}},{“type”:”grid”,”props”:{“content_column_breakpoint”:”m”,”filter_align”:”left”,”filter_all”:true,”filter_grid_breakpoint”:”m”,”filter_grid_width”:”auto”,”filter_position”:”top”,”filter_style”:”tab”,”grid_column_align”:false,”grid_default”:”auto”,”grid_divider”:true,”grid_large”:”3″,”grid_medium”:”3″,”grid_parallax_justify”:true,”grid_row_align”:false,”grid_xlarge”:”3″,”icon_width”:80,”image_align”:”top”,”image_grid_breakpoint”:”m”,”image_grid_width”:”1-2″,”image_link”:true,”image_svg_color”:”emphasis”,”image_transition”:”scale-up”,”image_transition_border”:false,”item_animation”:true,”link_size”:”small”,”link_style”:”default”,”link_text”:”Read more”,”margin”:”default”,”meta_align”:”below-title”,”meta_element”:”div”,”meta_style”:”text-meta”,”show_content”:true,”show_image”:true,”show_link”:true,”show_meta”:true,”show_title”:true,”title_align”:”top”,”title_color”:”success”,”title_element”:”h3″,”title_grid_breakpoint”:”m”,”title_grid_width”:”1-2″,”title_hover_style”:”reset”,”title_link”:true},”children”:[{“type”:”grid_item”,”source”:{“query”:{“name”:”posts.customPosts”,”arguments”:{“terms”:[52],”category_operator”:”IN”,”post_tag_operator”:”IN”,”users”:[],”users_operator”:”IN”,”offset”:0,”limit”:3,”order”:”date”,”order_direction”:”DESC”,”industry_operator”:”IN”,”language_operator”:”IN”,”resources_operator”:”IN”}},”props”:{“_condition”:{“filters”:{“condition”:”!!”},”name”:”author.name”},”title”:{“filters”:{“search”:””},”name”:”title”},”content”:{“filters”:{“search”:””,”limit”:100},”name”:”excerpt”},”image”:{“filters”:{“search”:””},”name”:”featuredImage.url”},”link”:{“filters”:{“search”:””},”name”:”link”}}}}]}]}]}]}],”version”:”4.4.1″} –>

The Ultimate Guide to Decision Engines

What is a decision engine and how does it help your business processes?

Learn More


LATEST NEWS

<\/p>\n

Parsippany, NJ \u2014 Jan. 26, 2023 \u2014 <\/strong>Provenir, a global leader in data and AI-powered risk decisioning software, announced today that Quick Finans, a consumer finance company located in Turkey, has selected Provenir\u2019s AI-Powered Data and Decisioning Platform to quickly approve and onboard new customers.<\/p>\n

<\/p>\n

Quick Finans, a wholly owned subsidiary of Quick Insurance, which is under the umbrella of Maher Holding, offers solutions for consumer finance loans (GPL), auto financing, mortgages, agricultural financing, and small business lending. They were looking for a low\/no code platform that could be deployed quickly, modified in real-time and scale as the company expands its offerings.<\/p>\n

<\/p>\n

\u201cAfter evaluating several options, we determined that Provenir best met our requirements and could support our aggressive growth strategies,\u201d said Cumhur Ta\u015f \u2013 Deputy General Manager responsible for Credit & Operations in Quick Finans. \u201cThe platform provides the flexibility we need to power our business now and in the future. Another key differentiator was the ability to easily access and integrate new data sources to help us gain a more holistic view of our applicants and customers.\u201d<\/p>\n

<\/p>\n

\u201cWe are pleased to partner with Quick Finans to develop real-time decisioning solutions that will provide a superior customer experience,\u201d said Emre Unlusoy, Regional Manager for Provenir. \u201cProvenir\u2019s no-code, visual UI eliminates vendor and development team reliance, and will provide Quick Finans the flexibility and agility needed to rapidly make changes, test new strategies and get products to market faster.\u201d<\/p>\n

<\/p>\n

Provenir\u2019s industry-leading AI-Powered Data and Decisioning Platform is data fueled and AI driven for smarter risk decisioning. The solution, managed through a single UI, empowers organizations to innovate further and faster than ever before, driving the continuous optimization they need to power growth and agility, without increasing risk. With the unique combination of universal access to data, embedded AI and world-class decisioning technology, Provenir provides a cohesive risk ecosystem to enable smarter decisions across the entire customer lifecycle \u2013 offering diverse data for deeper insights, auto-optimized decisions, and a continuous feedback loop for constant improvement both at onboarding when assessing risk and monitoring ongoing transactions for fraud.<\/p>“,”margin”:”default”}}]},{“type”:”column”,”props”:{“image_position”:”center-center”,”padding”:”small”,”position_sticky”:”row”,”position_sticky_breakpoint”:”m”,”position_sticky_offset”:”100″,”style”:”card-default”,”width_medium”:”1-3″},”children”:[{“type”:”headline”,”props”:{“content”:”The Ultimate Guide to Decision Engines”,”text_align”:”center”,”title_color”:”success”,”title_element”:”h3″,”title_style”:”h3″}},{“type”:”text”,”props”:{“column_breakpoint”:”m”,”content”:”

What is a decision engine and how does it help your business processes?<\/p>“,”margin”:”default”,”text_align”:”center”}},{“type”:”button”,”props”:{“grid_column_gap”:”small”,”grid_row_gap”:””,”margin”:””,”margin_remove_bottom”:false,”maxwidth”:”medium”,”text_align”:”center”},”children”:[{“type”:”button_item”,”props”:{“button_style”:”default”,”content”:”Learn More”,”icon”:””,”icon_align”:”left”,”link”:”\/blog\/the-ultimate-guide-to-decision-engines\/”}}]}]}],”props”:{“layout”:”2-3,1-3″}}]},{“type”:”section”,”props”:{“image_position”:”center-center”,”style”:”secondary”,”title_breakpoint”:”xl”,”title_position”:”top-left”,”title_rotation”:”left”,”vertical_align”:””,”width”:”default”},”children”:[{“type”:”row”,”children”:[{“type”:”column”,”props”:{“image_position”:”center-center”,”position_sticky_breakpoint”:”m”},”children”:[{“type”:”divider”,”props”:{“divider_element”:”hr”}},{“type”:”headline”,”props”:{“content”:”LATEST NEWS”,”title_color”:”background”,”title_element”:”h1″,”title_style”:”text-large”}},{“type”:”grid”,”props”:{“content_column_breakpoint”:”m”,”filter_align”:”left”,”filter_all”:true,”filter_grid_breakpoint”:”m”,”filter_grid_width”:”auto”,”filter_position”:”top”,”filter_style”:”tab”,”grid_column_align”:false,”grid_default”:”auto”,”grid_divider”:true,”grid_large”:”3″,”grid_medium”:”3″,”grid_parallax_justify”:true,”grid_row_align”:false,”grid_xlarge”:”3″,”icon_width”:80,”image_align”:”top”,”image_grid_breakpoint”:”m”,”image_grid_width”:”1-2″,”image_link”:true,”image_svg_color”:”emphasis”,”image_transition”:”scale-up”,”image_transition_border”:false,”item_animation”:true,”link_size”:”small”,”link_style”:”default”,”link_text”:”Read more”,”margin”:”default”,”meta_align”:”below-title”,”meta_element”:”div”,”meta_style”:”text-meta”,”show_content”:true,”show_image”:true,”show_link”:true,”show_meta”:true,”show_title”:true,”title_align”:”top”,”title_color”:”success”,”title_element”:”h3″,”title_grid_breakpoint”:”m”,”title_grid_width”:”1-2″,”title_hover_style”:”reset”,”title_link”:true},”children”:[{“type”:”grid_item”,”source”:{“query”:{“name”:”posts.customPosts”,”arguments”:{“terms”:[52],”category_operator”:”IN”,”post_tag_operator”:”IN”,”users”:[],”users_operator”:”IN”,”offset”:0,”limit”:3,”order”:”date”,”order_direction”:”DESC”,”industry_operator”:”IN”,”language_operator”:”IN”,”resources_operator”:”IN”}},”props”:{“_condition”:{“filters”:{“condition”:”!!”},”name”:”author.name”},”title”:{“filters”:{“search”:””},”name”:”title”},”content”:{“filters”:{“search”:””,”limit”:100},”name”:”excerpt”},”image”:{“filters”:{“search”:””},”name”:”featuredImage.url”},”link”:{“filters”:{“search”:””},”name”:”link”}}}}]}]}]}]}],”version”:”4.4.1″} –><\/p>\n

Provenir\u2019s no-code platform delivers rapid deployment, flexibility and scalability for a growing company<\/em><\/p>\n

<\/p>\n

Parsippany, NJ \u2014 Jan. 26, 2023 \u2014 <\/strong>Provenir, a global leader in data and AI-powered risk decisioning software, announced today that Quick Finans, a consumer finance company located in Turkey, has selected Provenir\u2019s AI-Powered Data and Decisioning Platform to quickly approve and onboard new customers.<\/p>\n

<\/p>\n

Quick Finans, a wholly owned subsidiary of Quick Insurance, which is under the umbrella of Maher Holding, offers solutions for consumer finance loans (GPL), auto financing, mortgages, agricultural financing, and small business lending. They were looking for a low\/no code platform that could be deployed quickly, modified in real-time and scale as the company expands its offerings.<\/p>\n

<\/p>\n

\u201cAfter evaluating several options, we determined that Provenir best met our requirements and could support our aggressive growth strategies,\u201d said Cumhur Ta\u015f \u2013 Deputy General Manager responsible for Credit & Operations in Quick Finans. \u201cThe platform provides the flexibility we need to power our business now and in the future. Another key differentiator was the ability to easily access and integrate new data sources to help us gain a more holistic view of our applicants and customers.\u201d<\/p>\n

<\/p>\n

\u201cWe are pleased to partner with Quick Finans to develop real-time decisioning solutions that will provide a superior customer experience,\u201d said Emre Unlusoy, Regional Manager for Provenir. \u201cProvenir\u2019s no-code, visual UI eliminates vendor and development team reliance, and will provide Quick Finans the flexibility and agility needed to rapidly make changes, test new strategies and get products to market faster.\u201d<\/p>\n

<\/p>\n

Provenir\u2019s industry-leading AI-Powered Data and Decisioning Platform is data fueled and AI driven for smarter risk decisioning. The solution, managed through a single UI, empowers organizations to innovate further and faster than ever before, driving the continuous optimization they need to power growth and agility, without increasing risk. With the unique combination of universal access to data, embedded AI and world-class decisioning technology, Provenir provides a cohesive risk ecosystem to enable smarter decisions across the entire customer lifecycle \u2013 offering diverse data for deeper insights, auto-optimized decisions, and a continuous feedback loop for constant improvement both at onboarding when assessing risk and monitoring ongoing transactions for fraud.<\/p>“,”margin”:”default”}}]},{“type”:”column”,”props”:{“image_position”:”center-center”,”padding”:”small”,”position_sticky”:”row”,”position_sticky_breakpoint”:”m”,”position_sticky_offset”:”100″,”style”:”card-default”,”width_medium”:”1-3″},”children”:[{“type”:”headline”,”props”:{“content”:”The Ultimate Guide to Decision Engines”,”text_align”:”center”,”title_color”:”success”,”title_element”:”h3″,”title_style”:”h3″}},{“type”:”text”,”props”:{“column_breakpoint”:”m”,”content”:”

What is a decision engine and how does it help your business processes?<\/p>“,”margin”:”default”,”text_align”:”center”}},{“type”:”button”,”props”:{“grid_column_gap”:”small”,”grid_row_gap”:””,”margin”:””,”margin_remove_bottom”:false,”maxwidth”:”medium”,”text_align”:”center”},”children”:[{“type”:”button_item”,”props”:{“button_style”:”default”,”content”:”Learn More”,”icon”:””,”icon_align”:”left”,”link”:”\/blog\/the-ultimate-guide-to-decision-engines\/”}}]}]}],”props”:{“layout”:”2-3,1-3″}}]},{“type”:”section”,”props”:{“image_position”:”center-center”,”style”:”secondary”,”title_breakpoint”:”xl”,”title_position”:”top-left”,”title_rotation”:”left”,”vertical_align”:””,”width”:”default”},”children”:[{“type”:”row”,”children”:[{“type”:”column”,”props”:{“image_position”:”center-center”,”position_sticky_breakpoint”:”m”},”children”:[{“type”:”divider”,”props”:{“divider_element”:”hr”}},{“type”:”headline”,”props”:{“content”:”LATEST NEWS”,”title_color”:”background”,”title_element”:”h1″,”title_style”:”text-large”}},{“type”:”grid”,”props”:{“content_column_breakpoint”:”m”,”filter_align”:”left”,”filter_all”:true,”filter_grid_breakpoint”:”m”,”filter_grid_width”:”auto”,”filter_position”:”top”,”filter_style”:”tab”,”grid_column_align”:false,”grid_default”:”auto”,”grid_divider”:true,”grid_large”:”3″,”grid_medium”:”3″,”grid_parallax_justify”:true,”grid_row_align”:false,”grid_xlarge”:”3″,”icon_width”:80,”image_align”:”top”,”image_grid_breakpoint”:”m”,”image_grid_width”:”1-2″,”image_link”:true,”image_svg_color”:”emphasis”,”image_transition”:”scale-up”,”image_transition_border”:false,”item_animation”:true,”link_size”:”small”,”link_style”:”default”,”link_text”:”Read more”,”margin”:”default”,”meta_align”:”below-title”,”meta_element”:”div”,”meta_style”:”text-meta”,”show_content”:true,”show_image”:true,”show_link”:true,”show_meta”:true,”show_title”:true,”title_align”:”top”,”title_color”:”success”,”title_element”:”h3″,”title_grid_breakpoint”:”m”,”title_grid_width”:”1-2″,”title_hover_style”:”reset”,”title_link”:true},”children”:[{“type”:”grid_item”,”source”:{“query”:{“name”:”posts.customPosts”,”arguments”:{“terms”:[52],”category_operator”:”IN”,”post_tag_operator”:”IN”,”users”:[],”users_operator”:”IN”,”offset”:0,”limit”:3,”order”:”date”,”order_direction”:”DESC”,”industry_operator”:”IN”,”language_operator”:”IN”,”resources_operator”:”IN”}},”props”:{“_condition”:{“filters”:{“condition”:”!!”},”name”:”author.name”},”title”:{“filters”:{“search”:””},”name”:”title”},”content”:{“filters”:{“search”:””,”limit”:100},”name”:”excerpt”},”image”:{“filters”:{“search”:””},”name”:”featuredImage.url”},”link”:{“filters”:{“search”:””},”name”:”link”}}}}]}]}]}]}],”version”:”4.4.1″} –>

The Ultimate Guide to Decision Engines

What is a decision engine and how does it help your business processes?

Learn More


LATEST NEWS

<\/p>\n

Parsippany, NJ \u2014 Jan. 26, 2023 \u2014 <\/strong>Provenir, a global leader in data and AI-powered risk decisioning software, announced today that Quick Finans, a consumer finance company located in Turkey, has selected Provenir\u2019s AI-Powered Data and Decisioning Platform to quickly approve and onboard new customers.<\/p>\n

<\/p>\n

Quick Finans, a wholly owned subsidiary of Quick Insurance, which is under the umbrella of Maher Holding, offers solutions for consumer finance loans (GPL), auto financing, mortgages, agricultural financing, and small business lending. They were looking for a low\/no code platform that could be deployed quickly, modified in real-time and scale as the company expands its offerings.<\/p>\n

<\/p>\n

\u201cAfter evaluating several options, we determined that Provenir best met our requirements and could support our aggressive growth strategies,\u201d said Cumhur Ta\u015f \u2013 Deputy General Manager responsible for Credit & Operations in Quick Finans. \u201cThe platform provides the flexibility we need to power our business now and in the future. Another key differentiator was the ability to easily access and integrate new data sources to help us gain a more holistic view of our applicants and customers.\u201d<\/p>\n

<\/p>\n

\u201cWe are pleased to partner with Quick Finans to develop real-time decisioning solutions that will provide a superior customer experience,\u201d said Emre Unlusoy, Regional Manager for Provenir. \u201cProvenir\u2019s no-code, visual UI eliminates vendor and development team reliance, and will provide Quick Finans the flexibility and agility needed to rapidly make changes, test new strategies and get products to market faster.\u201d<\/p>\n

<\/p>\n

Provenir\u2019s industry-leading AI-Powered Data and Decisioning Platform is data fueled and AI driven for smarter risk decisioning. The solution, managed through a single UI, empowers organizations to innovate further and faster than ever before, driving the continuous optimization they need to power growth and agility, without increasing risk. With the unique combination of universal access to data, embedded AI and world-class decisioning technology, Provenir provides a cohesive risk ecosystem to enable smarter decisions across the entire customer lifecycle \u2013 offering diverse data for deeper insights, auto-optimized decisions, and a continuous feedback loop for constant improvement both at onboarding when assessing risk and monitoring ongoing transactions for fraud.<\/p>“,”margin”:”default”}}]},{“type”:”column”,”props”:{“image_position”:”center-center”,”padding”:”small”,”position_sticky”:”row”,”position_sticky_breakpoint”:”m”,”position_sticky_offset”:”100″,”style”:”card-default”,”width_medium”:”1-3″},”children”:[{“type”:”headline”,”props”:{“content”:”The Ultimate Guide to Decision Engines”,”text_align”:”center”,”title_color”:”success”,”title_element”:”h3″,”title_style”:”h3″}},{“type”:”text”,”props”:{“column_breakpoint”:”m”,”content”:”

What is a decision engine and how does it help your business processes?<\/p>“,”margin”:”default”,”text_align”:”center”}},{“type”:”button”,”props”:{“grid_column_gap”:”small”,”grid_row_gap”:””,”margin”:””,”margin_remove_bottom”:false,”maxwidth”:”medium”,”text_align”:”center”},”children”:[{“type”:”button_item”,”props”:{“button_style”:”default”,”content”:”Learn More”,”icon”:””,”icon_align”:”left”,”link”:”\/blog\/the-ultimate-guide-to-decision-engines\/”}}]}]}],”props”:{“layout”:”2-3,1-3″}}]},{“type”:”section”,”props”:{“image_position”:”center-center”,”style”:”secondary”,”title_breakpoint”:”xl”,”title_position”:”top-left”,”title_rotation”:”left”,”vertical_align”:””,”width”:”default”},”children”:[{“type”:”row”,”children”:[{“type”:”column”,”props”:{“image_position”:”center-center”,”position_sticky_breakpoint”:”m”},”children”:[{“type”:”divider”,”props”:{“divider_element”:”hr”}},{“type”:”headline”,”props”:{“content”:”LATEST NEWS”,”title_color”:”background”,”title_element”:”h1″,”title_style”:”text-large”}},{“type”:”grid”,”props”:{“content_column_breakpoint”:”m”,”filter_align”:”left”,”filter_all”:true,”filter_grid_breakpoint”:”m”,”filter_grid_width”:”auto”,”filter_position”:”top”,”filter_style”:”tab”,”grid_column_align”:false,”grid_default”:”auto”,”grid_divider”:true,”grid_large”:”3″,”grid_medium”:”3″,”grid_parallax_justify”:true,”grid_row_align”:false,”grid_xlarge”:”3″,”icon_width”:80,”image_align”:”top”,”image_grid_breakpoint”:”m”,”image_grid_width”:”1-2″,”image_link”:true,”image_svg_color”:”emphasis”,”image_transition”:”scale-up”,”image_transition_border”:false,”item_animation”:true,”link_size”:”small”,”link_style”:”default”,”link_text”:”Read more”,”margin”:”default”,”meta_align”:”below-title”,”meta_element”:”div”,”meta_style”:”text-meta”,”show_content”:true,”show_image”:true,”show_link”:true,”show_meta”:true,”show_title”:true,”title_align”:”top”,”title_color”:”success”,”title_element”:”h3″,”title_grid_breakpoint”:”m”,”title_grid_width”:”1-2″,”title_hover_style”:”reset”,”title_link”:true},”children”:[{“type”:”grid_item”,”source”:{“query”:{“name”:”posts.customPosts”,”arguments”:{“terms”:[52],”category_operator”:”IN”,”post_tag_operator”:”IN”,”users”:[],”users_operator”:”IN”,”offset”:0,”limit”:3,”order”:”date”,”order_direction”:”DESC”,”industry_operator”:”IN”,”language_operator”:”IN”,”resources_operator”:”IN”}},”props”:{“_condition”:{“filters”:{“condition”:”!!”},”name”:”author.name”},”title”:{“filters”:{“search”:””},”name”:”title”},”content”:{“filters”:{“search”:””,”limit”:100},”name”:”excerpt”},”image”:{“filters”:{“search”:””},”name”:”featuredImage.url”},”link”:{“filters”:{“search”:””},”name”:”link”}}}}]}]}]}]}],”version”:”4.4.1″} –>

The Ultimate Guide to Decision Engines

What is a decision engine and how does it help your business processes?

Learn More


LATEST NEWS

(more…)

<\/p>\n

Provenir\u2019s no-code platform delivers rapid deployment, flexibility and scalability for a growing company<\/em><\/p>\n

<\/p>\n

Parsippany, NJ \u2014 Jan. 26, 2023 \u2014 <\/strong>Provenir, a global leader in data and AI-powered risk decisioning software, announced today that Quick Finans, a consumer finance company located in Turkey, has selected Provenir\u2019s AI-Powered Data and Decisioning Platform to quickly approve and onboard new customers.<\/p>\n

<\/p>\n

Quick Finans, a wholly owned subsidiary of Quick Insurance, which is under the umbrella of Maher Holding, offers solutions for consumer finance loans (GPL), auto financing, mortgages, agricultural financing, and small business lending. They were looking for a low\/no code platform that could be deployed quickly, modified in real-time and scale as the company expands its offerings.<\/p>\n

<\/p>\n

\u201cAfter evaluating several options, we determined that Provenir best met our requirements and could support our aggressive growth strategies,\u201d said Cumhur Ta\u015f \u2013 Deputy General Manager responsible for Credit & Operations in Quick Finans. \u201cThe platform provides the flexibility we need to power our business now and in the future. Another key differentiator was the ability to easily access and integrate new data sources to help us gain a more holistic view of our applicants and customers.\u201d<\/p>\n

<\/p>\n

\u201cWe are pleased to partner with Quick Finans to develop real-time decisioning solutions that will provide a superior customer experience,\u201d said Emre Unlusoy, Regional Manager for Provenir. \u201cProvenir\u2019s no-code, visual UI eliminates vendor and development team reliance, and will provide Quick Finans the flexibility and agility needed to rapidly make changes, test new strategies and get products to market faster.\u201d<\/p>\n

<\/p>\n

Provenir\u2019s industry-leading AI-Powered Data and Decisioning Platform is data fueled and AI driven for smarter risk decisioning. The solution, managed through a single UI, empowers organizations to innovate further and faster than ever before, driving the continuous optimization they need to power growth and agility, without increasing risk. With the unique combination of universal access to data, embedded AI and world-class decisioning technology, Provenir provides a cohesive risk ecosystem to enable smarter decisions across the entire customer lifecycle \u2013 offering diverse data for deeper insights, auto-optimized decisions, and a continuous feedback loop for constant improvement both at onboarding when assessing risk and monitoring ongoing transactions for fraud.<\/p>“,”margin”:”default”}}]},{“type”:”column”,”props”:{“image_position”:”center-center”,”padding”:”small”,”position_sticky”:”row”,”position_sticky_breakpoint”:”m”,”position_sticky_offset”:”100″,”style”:”card-default”,”width_medium”:”1-3″},”children”:[{“type”:”headline”,”props”:{“content”:”The Ultimate Guide to Decision Engines”,”text_align”:”center”,”title_color”:”success”,”title_element”:”h3″,”title_style”:”h3″}},{“type”:”text”,”props”:{“column_breakpoint”:”m”,”content”:”

What is a decision engine and how does it help your business processes?<\/p>“,”margin”:”default”,”text_align”:”center”}},{“type”:”button”,”props”:{“grid_column_gap”:”small”,”grid_row_gap”:””,”margin”:””,”margin_remove_bottom”:false,”maxwidth”:”medium”,”text_align”:”center”},”children”:[{“type”:”button_item”,”props”:{“button_style”:”default”,”content”:”Learn More”,”icon”:””,”icon_align”:”left”,”link”:”\/blog\/the-ultimate-guide-to-decision-engines\/”}}]}]}],”props”:{“layout”:”2-3,1-3″}}]},{“type”:”section”,”props”:{“image_position”:”center-center”,”style”:”secondary”,”title_breakpoint”:”xl”,”title_position”:”top-left”,”title_rotation”:”left”,”vertical_align”:””,”width”:”default”},”children”:[{“type”:”row”,”children”:[{“type”:”column”,”props”:{“image_position”:”center-center”,”position_sticky_breakpoint”:”m”},”children”:[{“type”:”divider”,”props”:{“divider_element”:”hr”}},{“type”:”headline”,”props”:{“content”:”LATEST NEWS”,”title_color”:”background”,”title_element”:”h1″,”title_style”:”text-large”}},{“type”:”grid”,”props”:{“content_column_breakpoint”:”m”,”filter_align”:”left”,”filter_all”:true,”filter_grid_breakpoint”:”m”,”filter_grid_width”:”auto”,”filter_position”:”top”,”filter_style”:”tab”,”grid_column_align”:false,”grid_default”:”auto”,”grid_divider”:true,”grid_large”:”3″,”grid_medium”:”3″,”grid_parallax_justify”:true,”grid_row_align”:false,”grid_xlarge”:”3″,”icon_width”:80,”image_align”:”top”,”image_grid_breakpoint”:”m”,”image_grid_width”:”1-2″,”image_link”:true,”image_svg_color”:”emphasis”,”image_transition”:”scale-up”,”image_transition_border”:false,”item_animation”:true,”link_size”:”small”,”link_style”:”default”,”link_text”:”Read more”,”margin”:”default”,”meta_align”:”below-title”,”meta_element”:”div”,”meta_style”:”text-meta”,”show_content”:true,”show_image”:true,”show_link”:true,”show_meta”:true,”show_title”:true,”title_align”:”top”,”title_color”:”success”,”title_element”:”h3″,”title_grid_breakpoint”:”m”,”title_grid_width”:”1-2″,”title_hover_style”:”reset”,”title_link”:true},”children”:[{“type”:”grid_item”,”source”:{“query”:{“name”:”posts.customPosts”,”arguments”:{“terms”:[52],”category_operator”:”IN”,”post_tag_operator”:”IN”,”users”:[],”users_operator”:”IN”,”offset”:0,”limit”:3,”order”:”date”,”order_direction”:”DESC”,”industry_operator”:”IN”,”language_operator”:”IN”,”resources_operator”:”IN”}},”props”:{“_condition”:{“filters”:{“condition”:”!!”},”name”:”author.name”},”title”:{“filters”:{“search”:””},”name”:”title”},”content”:{“filters”:{“search”:””,”limit”:100},”name”:”excerpt”},”image”:{“filters”:{“search”:””},”name”:”featuredImage.url”},”link”:{“filters”:{“search”:””},”name”:”link”}}}}]}]}]}]}],”version”:”4.4.1″} –>

The Ultimate Guide to Decision Engines

What is a decision engine and how does it help your business processes?

Learn More


LATEST NEWS

(more…)

<\/p>\n

Parsippany, NJ \u2014 Jan. 26, 2023 \u2014 <\/strong>Provenir, a global leader in data and AI-powered risk decisioning software, announced today that Quick Finans, a consumer finance company located in Turkey, has selected Provenir\u2019s AI-Powered Data and Decisioning Platform to quickly approve and onboard new customers.<\/p>\n

<\/p>\n

Quick Finans, a wholly owned subsidiary of Quick Insurance, which is under the umbrella of Maher Holding, offers solutions for consumer finance loans (GPL), auto financing, mortgages, agricultural financing, and small business lending. They were looking for a low\/no code platform that could be deployed quickly, modified in real-time and scale as the company expands its offerings.<\/p>\n

<\/p>\n

\u201cAfter evaluating several options, we determined that Provenir best met our requirements and could support our aggressive growth strategies,\u201d said Cumhur Ta\u015f \u2013 Deputy General Manager responsible for Credit & Operations in Quick Finans. \u201cThe platform provides the flexibility we need to power our business now and in the future. Another key differentiator was the ability to easily access and integrate new data sources to help us gain a more holistic view of our applicants and customers.\u201d<\/p>\n

<\/p>\n

\u201cWe are pleased to partner with Quick Finans to develop real-time decisioning solutions that will provide a superior customer experience,\u201d said Emre Unlusoy, Regional Manager for Provenir. \u201cProvenir\u2019s no-code, visual UI eliminates vendor and development team reliance, and will provide Quick Finans the flexibility and agility needed to rapidly make changes, test new strategies and get products to market faster.\u201d<\/p>\n

<\/p>\n

Provenir\u2019s industry-leading AI-Powered Data and Decisioning Platform is data fueled and AI driven for smarter risk decisioning. The solution, managed through a single UI, empowers organizations to innovate further and faster than ever before, driving the continuous optimization they need to power growth and agility, without increasing risk. With the unique combination of universal access to data, embedded AI and world-class decisioning technology, Provenir provides a cohesive risk ecosystem to enable smarter decisions across the entire customer lifecycle \u2013 offering diverse data for deeper insights, auto-optimized decisions, and a continuous feedback loop for constant improvement both at onboarding when assessing risk and monitoring ongoing transactions for fraud.<\/p>“,”margin”:”default”}}]},{“type”:”column”,”props”:{“image_position”:”center-center”,”padding”:”small”,”position_sticky”:”row”,”position_sticky_breakpoint”:”m”,”position_sticky_offset”:”100″,”style”:”card-default”,”width_medium”:”1-3″},”children”:[{“type”:”headline”,”props”:{“content”:”The Ultimate Guide to Decision Engines”,”text_align”:”center”,”title_color”:”success”,”title_element”:”h3″,”title_style”:”h3″}},{“type”:”text”,”props”:{“column_breakpoint”:”m”,”content”:”

What is a decision engine and how does it help your business processes?<\/p>“,”margin”:”default”,”text_align”:”center”}},{“type”:”button”,”props”:{“grid_column_gap”:”small”,”grid_row_gap”:””,”margin”:””,”margin_remove_bottom”:false,”maxwidth”:”medium”,”text_align”:”center”},”children”:[{“type”:”button_item”,”props”:{“button_style”:”default”,”content”:”Learn More”,”icon”:””,”icon_align”:”left”,”link”:”\/blog\/the-ultimate-guide-to-decision-engines\/”}}]}]}],”props”:{“layout”:”2-3,1-3″}}]},{“type”:”section”,”props”:{“image_position”:”center-center”,”style”:”secondary”,”title_breakpoint”:”xl”,”title_position”:”top-left”,”title_rotation”:”left”,”vertical_align”:””,”width”:”default”},”children”:[{“type”:”row”,”children”:[{“type”:”column”,”props”:{“image_position”:”center-center”,”position_sticky_breakpoint”:”m”},”children”:[{“type”:”divider”,”props”:{“divider_element”:”hr”}},{“type”:”headline”,”props”:{“content”:”LATEST NEWS”,”title_color”:”background”,”title_element”:”h1″,”title_style”:”text-large”}},{“type”:”grid”,”props”:{“content_column_breakpoint”:”m”,”filter_align”:”left”,”filter_all”:true,”filter_grid_breakpoint”:”m”,”filter_grid_width”:”auto”,”filter_position”:”top”,”filter_style”:”tab”,”grid_column_align”:false,”grid_default”:”auto”,”grid_divider”:true,”grid_large”:”3″,”grid_medium”:”3″,”grid_parallax_justify”:true,”grid_row_align”:false,”grid_xlarge”:”3″,”icon_width”:80,”image_align”:”top”,”image_grid_breakpoint”:”m”,”image_grid_width”:”1-2″,”image_link”:true,”image_svg_color”:”emphasis”,”image_transition”:”scale-up”,”image_transition_border”:false,”item_animation”:true,”link_size”:”small”,”link_style”:”default”,”link_text”:”Read more”,”margin”:”default”,”meta_align”:”below-title”,”meta_element”:”div”,”meta_style”:”text-meta”,”show_content”:true,”show_image”:true,”show_link”:true,”show_meta”:true,”show_title”:true,”title_align”:”top”,”title_color”:”success”,”title_element”:”h3″,”title_grid_breakpoint”:”m”,”title_grid_width”:”1-2″,”title_hover_style”:”reset”,”title_link”:true},”children”:[{“type”:”grid_item”,”source”:{“query”:{“name”:”posts.customPosts”,”arguments”:{“terms”:[52],”category_operator”:”IN”,”post_tag_operator”:”IN”,”users”:[],”users_operator”:”IN”,”offset”:0,”limit”:3,”order”:”date”,”order_direction”:”DESC”,”industry_operator”:”IN”,”language_operator”:”IN”,”resources_operator”:”IN”}},”props”:{“_condition”:{“filters”:{“condition”:”!!”},”name”:”author.name”},”title”:{“filters”:{“search”:””},”name”:”title”},”content”:{“filters”:{“search”:””,”limit”:100},”name”:”excerpt”},”image”:{“filters”:{“search”:””},”name”:”featuredImage.url”},”link”:{“filters”:{“search”:””},”name”:”link”}}}}]}]}]}]}],”version”:”4.4.1″} –><\/p>\n

Provenir\u2019s no-code platform delivers rapid deployment, flexibility and scalability for a growing company<\/em><\/p>\n

<\/p>\n

Parsippany, NJ \u2014 Jan. 26, 2023 \u2014 <\/strong>Provenir, a global leader in data and AI-powered risk decisioning software, announced today that Quick Finans, a consumer finance company located in Turkey, has selected Provenir\u2019s AI-Powered Data and Decisioning Platform to quickly approve and onboard new customers.<\/p>\n

<\/p>\n

Quick Finans, a wholly owned subsidiary of Quick Insurance, which is under the umbrella of Maher Holding, offers solutions for consumer finance loans (GPL), auto financing, mortgages, agricultural financing, and small business lending. They were looking for a low\/no code platform that could be deployed quickly, modified in real-time and scale as the company expands its offerings.<\/p>\n

<\/p>\n

\u201cAfter evaluating several options, we determined that Provenir best met our requirements and could support our aggressive growth strategies,\u201d said Cumhur Ta\u015f \u2013 Deputy General Manager responsible for Credit & Operations in Quick Finans. \u201cThe platform provides the flexibility we need to power our business now and in the future. Another key differentiator was the ability to easily access and integrate new data sources to help us gain a more holistic view of our applicants and customers.\u201d<\/p>\n

<\/p>\n

\u201cWe are pleased to partner with Quick Finans to develop real-time decisioning solutions that will provide a superior customer experience,\u201d said Emre Unlusoy, Regional Manager for Provenir. \u201cProvenir\u2019s no-code, visual UI eliminates vendor and development team reliance, and will provide Quick Finans the flexibility and agility needed to rapidly make changes, test new strategies and get products to market faster.\u201d<\/p>\n

<\/p>\n

Provenir\u2019s industry-leading AI-Powered Data and Decisioning Platform is data fueled and AI driven for smarter risk decisioning. The solution, managed through a single UI, empowers organizations to innovate further and faster than ever before, driving the continuous optimization they need to power growth and agility, without increasing risk. With the unique combination of universal access to data, embedded AI and world-class decisioning technology, Provenir provides a cohesive risk ecosystem to enable smarter decisions across the entire customer lifecycle \u2013 offering diverse data for deeper insights, auto-optimized decisions, and a continuous feedback loop for constant improvement both at onboarding when assessing risk and monitoring ongoing transactions for fraud.<\/p>“,”margin”:”default”}}]},{“type”:”column”,”props”:{“image_position”:”center-center”,”padding”:”small”,”position_sticky”:”row”,”position_sticky_breakpoint”:”m”,”position_sticky_offset”:”100″,”style”:”card-default”,”width_medium”:”1-3″},”children”:[{“type”:”headline”,”props”:{“content”:”The Ultimate Guide to Decision Engines”,”text_align”:”center”,”title_color”:”success”,”title_element”:”h3″,”title_style”:”h3″}},{“type”:”text”,”props”:{“column_breakpoint”:”m”,”content”:”

What is a decision engine and how does it help your business processes?<\/p>“,”margin”:”default”,”text_align”:”center”}},{“type”:”button”,”props”:{“grid_column_gap”:”small”,”grid_row_gap”:””,”margin”:””,”margin_remove_bottom”:false,”maxwidth”:”medium”,”text_align”:”center”},”children”:[{“type”:”button_item”,”props”:{“button_style”:”default”,”content”:”Learn More”,”icon”:””,”icon_align”:”left”,”link”:”\/blog\/the-ultimate-guide-to-decision-engines\/”}}]}]}],”props”:{“layout”:”2-3,1-3″}}]},{“type”:”section”,”props”:{“image_position”:”center-center”,”style”:”secondary”,”title_breakpoint”:”xl”,”title_position”:”top-left”,”title_rotation”:”left”,”vertical_align”:””,”width”:”default”},”children”:[{“type”:”row”,”children”:[{“type”:”column”,”props”:{“image_position”:”center-center”,”position_sticky_breakpoint”:”m”},”children”:[{“type”:”divider”,”props”:{“divider_element”:”hr”}},{“type”:”headline”,”props”:{“content”:”LATEST NEWS”,”title_color”:”background”,”title_element”:”h1″,”title_style”:”text-large”}},{“type”:”grid”,”props”:{“content_column_breakpoint”:”m”,”filter_align”:”left”,”filter_all”:true,”filter_grid_breakpoint”:”m”,”filter_grid_width”:”auto”,”filter_position”:”top”,”filter_style”:”tab”,”grid_column_align”:false,”grid_default”:”auto”,”grid_divider”:true,”grid_large”:”3″,”grid_medium”:”3″,”grid_parallax_justify”:true,”grid_row_align”:false,”grid_xlarge”:”3″,”icon_width”:80,”image_align”:”top”,”image_grid_breakpoint”:”m”,”image_grid_width”:”1-2″,”image_link”:true,”image_svg_color”:”emphasis”,”image_transition”:”scale-up”,”image_transition_border”:false,”item_animation”:true,”link_size”:”small”,”link_style”:”default”,”link_text”:”Read more”,”margin”:”default”,”meta_align”:”below-title”,”meta_element”:”div”,”meta_style”:”text-meta”,”show_content”:true,”show_image”:true,”show_link”:true,”show_meta”:true,”show_title”:true,”title_align”:”top”,”title_color”:”success”,”title_element”:”h3″,”title_grid_breakpoint”:”m”,”title_grid_width”:”1-2″,”title_hover_style”:”reset”,”title_link”:true},”children”:[{“type”:”grid_item”,”source”:{“query”:{“name”:”posts.customPosts”,”arguments”:{“terms”:[52],”category_operator”:”IN”,”post_tag_operator”:”IN”,”users”:[],”users_operator”:”IN”,”offset”:0,”limit”:3,”order”:”date”,”order_direction”:”DESC”,”industry_operator”:”IN”,”language_operator”:”IN”,”resources_operator”:”IN”}},”props”:{“_condition”:{“filters”:{“condition”:”!!”},”name”:”author.name”},”title”:{“filters”:{“search”:””},”name”:”title”},”content”:{“filters”:{“search”:””,”limit”:100},”name”:”excerpt”},”image”:{“filters”:{“search”:””},”name”:”featuredImage.url”},”link”:{“filters”:{“search”:””},”name”:”link”}}}}]}]}]}]}],”version”:”4.4.1″} –>

The Ultimate Guide to Decision Engines

What is a decision engine and how does it help your business processes?

Learn More


LATEST NEWS

(more…)

<\/p>\n

Parsippany, NJ \u2014 Jan. 26, 2023 \u2014 <\/strong>Provenir, a global leader in data and AI-powered risk decisioning software, announced today that Quick Finans, a consumer finance company located in Turkey, has selected Provenir\u2019s AI-Powered Data and Decisioning Platform to quickly approve and onboard new customers.<\/p>\n

<\/p>\n

Quick Finans, a wholly owned subsidiary of Quick Insurance, which is under the umbrella of Maher Holding, offers solutions for consumer finance loans (GPL), auto financing, mortgages, agricultural financing, and small business lending. They were looking for a low\/no code platform that could be deployed quickly, modified in real-time and scale as the company expands its offerings.<\/p>\n

<\/p>\n

\u201cAfter evaluating several options, we determined that Provenir best met our requirements and could support our aggressive growth strategies,\u201d said Cumhur Ta\u015f \u2013 Deputy General Manager responsible for Credit & Operations in Quick Finans. \u201cThe platform provides the flexibility we need to power our business now and in the future. Another key differentiator was the ability to easily access and integrate new data sources to help us gain a more holistic view of our applicants and customers.\u201d<\/p>\n

<\/p>\n

\u201cWe are pleased to partner with Quick Finans to develop real-time decisioning solutions that will provide a superior customer experience,\u201d said Emre Unlusoy, Regional Manager for Provenir. \u201cProvenir\u2019s no-code, visual UI eliminates vendor and development team reliance, and will provide Quick Finans the flexibility and agility needed to rapidly make changes, test new strategies and get products to market faster.\u201d<\/p>\n

<\/p>\n

Provenir\u2019s industry-leading AI-Powered Data and Decisioning Platform is data fueled and AI driven for smarter risk decisioning. The solution, managed through a single UI, empowers organizations to innovate further and faster than ever before, driving the continuous optimization they need to power growth and agility, without increasing risk. With the unique combination of universal access to data, embedded AI and world-class decisioning technology, Provenir provides a cohesive risk ecosystem to enable smarter decisions across the entire customer lifecycle \u2013 offering diverse data for deeper insights, auto-optimized decisions, and a continuous feedback loop for constant improvement both at onboarding when assessing risk and monitoring ongoing transactions for fraud.<\/p>“,”margin”:”default”}}]},{“type”:”column”,”props”:{“image_position”:”center-center”,”padding”:”small”,”position_sticky”:”row”,”position_sticky_breakpoint”:”m”,”position_sticky_offset”:”100″,”style”:”card-default”,”width_medium”:”1-3″},”children”:[{“type”:”headline”,”props”:{“content”:”The Ultimate Guide to Decision Engines”,”text_align”:”center”,”title_color”:”success”,”title_element”:”h3″,”title_style”:”h3″}},{“type”:”text”,”props”:{“column_breakpoint”:”m”,”content”:”

What is a decision engine and how does it help your business processes?<\/p>“,”margin”:”default”,”text_align”:”center”}},{“type”:”button”,”props”:{“grid_column_gap”:”small”,”grid_row_gap”:””,”margin”:””,”margin_remove_bottom”:false,”maxwidth”:”medium”,”text_align”:”center”},”children”:[{“type”:”button_item”,”props”:{“button_style”:”default”,”content”:”Learn More”,”icon”:””,”icon_align”:”left”,”link”:”\/blog\/the-ultimate-guide-to-decision-engines\/”}}]}]}],”props”:{“layout”:”2-3,1-3″}}]},{“type”:”section”,”props”:{“image_position”:”center-center”,”style”:”secondary”,”title_breakpoint”:”xl”,”title_position”:”top-left”,”title_rotation”:”left”,”vertical_align”:””,”width”:”default”},”children”:[{“type”:”row”,”children”:[{“type”:”column”,”props”:{“image_position”:”center-center”,”position_sticky_breakpoint”:”m”},”children”:[{“type”:”divider”,”props”:{“divider_element”:”hr”}},{“type”:”headline”,”props”:{“content”:”LATEST NEWS”,”title_color”:”background”,”title_element”:”h1″,”title_style”:”text-large”}},{“type”:”grid”,”props”:{“content_column_breakpoint”:”m”,”filter_align”:”left”,”filter_all”:true,”filter_grid_breakpoint”:”m”,”filter_grid_width”:”auto”,”filter_position”:”top”,”filter_style”:”tab”,”grid_column_align”:false,”grid_default”:”auto”,”grid_divider”:true,”grid_large”:”3″,”grid_medium”:”3″,”grid_parallax_justify”:true,”grid_row_align”:false,”grid_xlarge”:”3″,”icon_width”:80,”image_align”:”top”,”image_grid_breakpoint”:”m”,”image_grid_width”:”1-2″,”image_link”:true,”image_svg_color”:”emphasis”,”image_transition”:”scale-up”,”image_transition_border”:false,”item_animation”:true,”link_size”:”small”,”link_style”:”default”,”link_text”:”Read more”,”margin”:”default”,”meta_align”:”below-title”,”meta_element”:”div”,”meta_style”:”text-meta”,”show_content”:true,”show_image”:true,”show_link”:true,”show_meta”:true,”show_title”:true,”title_align”:”top”,”title_color”:”success”,”title_element”:”h3″,”title_grid_breakpoint”:”m”,”title_grid_width”:”1-2″,”title_hover_style”:”reset”,”title_link”:true},”children”:[{“type”:”grid_item”,”source”:{“query”:{“name”:”posts.customPosts”,”arguments”:{“terms”:[52],”category_operator”:”IN”,”post_tag_operator”:”IN”,”users”:[],”users_operator”:”IN”,”offset”:0,”limit”:3,”order”:”date”,”order_direction”:”DESC”,”industry_operator”:”IN”,”language_operator”:”IN”,”resources_operator”:”IN”}},”props”:{“_condition”:{“filters”:{“condition”:”!!”},”name”:”author.name”},”title”:{“filters”:{“search”:””},”name”:”title”},”content”:{“filters”:{“search”:””,”limit”:100},”name”:”excerpt”},”image”:{“filters”:{“search”:””},”name”:”featuredImage.url”},”link”:{“filters”:{“search”:””},”name”:”link”}}}}]}]}]}]}],”version”:”4.4.1″} –><\/p>\n

Provenir\u2019s no-code platform delivers rapid deployment, flexibility and scalability for a growing company<\/em><\/p>\n

<\/p>\n

Parsippany, NJ \u2014 Jan. 26, 2023 \u2014 <\/strong>Provenir, a global leader in data and AI-powered risk decisioning software, announced today that Quick Finans, a consumer finance company located in Turkey, has selected Provenir\u2019s AI-Powered Data and Decisioning Platform to quickly approve and onboard new customers.<\/p>\n

<\/p>\n

Quick Finans, a wholly owned subsidiary of Quick Insurance, which is under the umbrella of Maher Holding, offers solutions for consumer finance loans (GPL), auto financing, mortgages, agricultural financing, and small business lending. They were looking for a low\/no code platform that could be deployed quickly, modified in real-time and scale as the company expands its offerings.<\/p>\n

<\/p>\n

\u201cAfter evaluating several options, we determined that Provenir best met our requirements and could support our aggressive growth strategies,\u201d said Cumhur Ta\u015f \u2013 Deputy General Manager responsible for Credit & Operations in Quick Finans. \u201cThe platform provides the flexibility we need to power our business now and in the future. Another key differentiator was the ability to easily access and integrate new data sources to help us gain a more holistic view of our applicants and customers.\u201d<\/p>\n

<\/p>\n

\u201cWe are pleased to partner with Quick Finans to develop real-time decisioning solutions that will provide a superior customer experience,\u201d said Emre Unlusoy, Regional Manager for Provenir. \u201cProvenir\u2019s no-code, visual UI eliminates vendor and development team reliance, and will provide Quick Finans the flexibility and agility needed to rapidly make changes, test new strategies and get products to market faster.\u201d<\/p>\n

<\/p>\n

Provenir\u2019s industry-leading AI-Powered Data and Decisioning Platform is data fueled and AI driven for smarter risk decisioning. The solution, managed through a single UI, empowers organizations to innovate further and faster than ever before, driving the continuous optimization they need to power growth and agility, without increasing risk. With the unique combination of universal access to data, embedded AI and world-class decisioning technology, Provenir provides a cohesive risk ecosystem to enable smarter decisions across the entire customer lifecycle \u2013 offering diverse data for deeper insights, auto-optimized decisions, and a continuous feedback loop for constant improvement both at onboarding when assessing risk and monitoring ongoing transactions for fraud.<\/p>“,”margin”:”default”}}]},{“type”:”column”,”props”:{“image_position”:”center-center”,”padding”:”small”,”position_sticky”:”row”,”position_sticky_breakpoint”:”m”,”position_sticky_offset”:”100″,”style”:”card-default”,”width_medium”:”1-3″},”children”:[{“type”:”headline”,”props”:{“content”:”The Ultimate Guide to Decision Engines”,”text_align”:”center”,”title_color”:”success”,”title_element”:”h3″,”title_style”:”h3″}},{“type”:”text”,”props”:{“column_breakpoint”:”m”,”content”:”

What is a decision engine and how does it help your business processes?<\/p>“,”margin”:”default”,”text_align”:”center”}},{“type”:”button”,”props”:{“grid_column_gap”:”small”,”grid_row_gap”:””,”margin”:””,”margin_remove_bottom”:false,”maxwidth”:”medium”,”text_align”:”center”},”children”:[{“type”:”button_item”,”props”:{“button_style”:”default”,”content”:”Learn More”,”icon”:””,”icon_align”:”left”,”link”:”\/blog\/the-ultimate-guide-to-decision-engines\/”}}]}]}],”props”:{“layout”:”2-3,1-3″}}]},{“type”:”section”,”props”:{“image_position”:”center-center”,”style”:”secondary”,”title_breakpoint”:”xl”,”title_position”:”top-left”,”title_rotation”:”left”,”vertical_align”:””,”width”:”default”},”children”:[{“type”:”row”,”children”:[{“type”:”column”,”props”:{“image_position”:”center-center”,”position_sticky_breakpoint”:”m”},”children”:[{“type”:”divider”,”props”:{“divider_element”:”hr”}},{“type”:”headline”,”props”:{“content”:”LATEST NEWS”,”title_color”:”background”,”title_element”:”h1″,”title_style”:”text-large”}},{“type”:”grid”,”props”:{“content_column_breakpoint”:”m”,”filter_align”:”left”,”filter_all”:true,”filter_grid_breakpoint”:”m”,”filter_grid_width”:”auto”,”filter_position”:”top”,”filter_style”:”tab”,”grid_column_align”:false,”grid_default”:”auto”,”grid_divider”:true,”grid_large”:”3″,”grid_medium”:”3″,”grid_parallax_justify”:true,”grid_row_align”:false,”grid_xlarge”:”3″,”icon_width”:80,”image_align”:”top”,”image_grid_breakpoint”:”m”,”image_grid_width”:”1-2″,”image_link”:true,”image_svg_color”:”emphasis”,”image_transition”:”scale-up”,”image_transition_border”:false,”item_animation”:true,”link_size”:”small”,”link_style”:”default”,”link_text”:”Read more”,”margin”:”default”,”meta_align”:”below-title”,”meta_element”:”div”,”meta_style”:”text-meta”,”show_content”:true,”show_image”:true,”show_link”:true,”show_meta”:true,”show_title”:true,”title_align”:”top”,”title_color”:”success”,”title_element”:”h3″,”title_grid_breakpoint”:”m”,”title_grid_width”:”1-2″,”title_hover_style”:”reset”,”title_link”:true},”children”:[{“type”:”grid_item”,”source”:{“query”:{“name”:”posts.customPosts”,”arguments”:{“terms”:[52],”category_operator”:”IN”,”post_tag_operator”:”IN”,”users”:[],”users_operator”:”IN”,”offset”:0,”limit”:3,”order”:”date”,”order_direction”:”DESC”,”industry_operator”:”IN”,”language_operator”:”IN”,”resources_operator”:”IN”}},”props”:{“_condition”:{“filters”:{“condition”:”!!”},”name”:”author.name”},”title”:{“filters”:{“search”:””},”name”:”title”},”content”:{“filters”:{“search”:””,”limit”:100},”name”:”excerpt”},”image”:{“filters”:{“search”:””},”name”:”featuredImage.url”},”link”:{“filters”:{“search”:””},”name”:”link”}}}}]}]}]}]}],”version”:”4.4.1″} –>

The Ultimate Guide to Decision Engines

What is a decision engine and how does it help your business processes?

Learn More


LATEST NEWS

(more…)

<\/p>\n

\u201cAfter evaluating several options, we determined that Provenir best met our requirements and could support our aggressive growth strategies,\u201d said Cumhur Ta\u015f \u2013 Deputy General Manager responsible for Credit & Operations in Quick Finans. \u201cThe platform provides the flexibility we need to power our business now and in the future. Another key differentiator was the ability to easily access and integrate new data sources to help us gain a more holistic view of our applicants and customers.\u201d<\/p>\n

<\/p>\n

\u201cWe are pleased to partner with Quick Finans to develop real-time decisioning solutions that will provide a superior customer experience,\u201d said Emre Unlusoy, Regional Manager for Provenir. \u201cProvenir\u2019s no-code, visual UI eliminates vendor and development team reliance, and will provide Quick Finans the flexibility and agility needed to rapidly make changes, test new strategies and get products to market faster.\u201d<\/p>\n

<\/p>\n

Provenir\u2019s industry-leading AI-Powered Data and Decisioning Platform is data fueled and AI driven for smarter risk decisioning. The solution, managed through a single UI, empowers organizations to innovate further and faster than ever before, driving the continuous optimization they need to power growth and agility, without increasing risk. With the unique combination of universal access to data, embedded AI and world-class decisioning technology, Provenir provides a cohesive risk ecosystem to enable smarter decisions across the entire customer lifecycle \u2013 offering diverse data for deeper insights, auto-optimized decisions, and a continuous feedback loop for constant improvement both at onboarding when assessing risk and monitoring ongoing transactions for fraud.<\/p>“,”margin”:”default”}}]},{“type”:”column”,”props”:{“image_position”:”center-center”,”padding”:”small”,”position_sticky”:”row”,”position_sticky_breakpoint”:”m”,”position_sticky_offset”:”100″,”style”:”card-default”,”width_medium”:”1-3″},”children”:[{“type”:”headline”,”props”:{“content”:”The Ultimate Guide to Decision Engines”,”text_align”:”center”,”title_color”:”success”,”title_element”:”h3″,”title_style”:”h3″}},{“type”:”text”,”props”:{“column_breakpoint”:”m”,”content”:”

What is a decision engine and how does it help your business processes?<\/p>“,”margin”:”default”,”text_align”:”center”}},{“type”:”button”,”props”:{“grid_column_gap”:”small”,”grid_row_gap”:””,”margin”:””,”margin_remove_bottom”:false,”maxwidth”:”medium”,”text_align”:”center”},”children”:[{“type”:”button_item”,”props”:{“button_style”:”default”,”content”:”Learn More”,”icon”:””,”icon_align”:”left”,”link”:”\/blog\/the-ultimate-guide-to-decision-engines\/”}}]}]}],”props”:{“layout”:”2-3,1-3″}}]},{“type”:”section”,”props”:{“image_position”:”center-center”,”style”:”secondary”,”title_breakpoint”:”xl”,”title_position”:”top-left”,”title_rotation”:”left”,”vertical_align”:””,”width”:”default”},”children”:[{“type”:”row”,”children”:[{“type”:”column”,”props”:{“image_position”:”center-center”,”position_sticky_breakpoint”:”m”},”children”:[{“type”:”divider”,”props”:{“divider_element”:”hr”}},{“type”:”headline”,”props”:{“content”:”LATEST NEWS”,”title_color”:”background”,”title_element”:”h1″,”title_style”:”text-large”}},{“type”:”grid”,”props”:{“content_column_breakpoint”:”m”,”filter_align”:”left”,”filter_all”:true,”filter_grid_breakpoint”:”m”,”filter_grid_width”:”auto”,”filter_position”:”top”,”filter_style”:”tab”,”grid_column_align”:false,”grid_default”:”auto”,”grid_divider”:true,”grid_large”:”3″,”grid_medium”:”3″,”grid_parallax_justify”:true,”grid_row_align”:false,”grid_xlarge”:”3″,”icon_width”:80,”image_align”:”top”,”image_grid_breakpoint”:”m”,”image_grid_width”:”1-2″,”image_link”:true,”image_svg_color”:”emphasis”,”image_transition”:”scale-up”,”image_transition_border”:false,”item_animation”:true,”link_size”:”small”,”link_style”:”default”,”link_text”:”Read more”,”margin”:”default”,”meta_align”:”below-title”,”meta_element”:”div”,”meta_style”:”text-meta”,”show_content”:true,”show_image”:true,”show_link”:true,”show_meta”:true,”show_title”:true,”title_align”:”top”,”title_color”:”success”,”title_element”:”h3″,”title_grid_breakpoint”:”m”,”title_grid_width”:”1-2″,”title_hover_style”:”reset”,”title_link”:true},”children”:[{“type”:”grid_item”,”source”:{“query”:{“name”:”posts.customPosts”,”arguments”:{“terms”:[52],”category_operator”:”IN”,”post_tag_operator”:”IN”,”users”:[],”users_operator”:”IN”,”offset”:0,”limit”:3,”order”:”date”,”order_direction”:”DESC”,”industry_operator”:”IN”,”language_operator”:”IN”,”resources_operator”:”IN”}},”props”:{“_condition”:{“filters”:{“condition”:”!!”},”name”:”author.name”},”title”:{“filters”:{“search”:””},”name”:”title”},”content”:{“filters”:{“search”:””,”limit”:100},”name”:”excerpt”},”image”:{“filters”:{“search”:””},”name”:”featuredImage.url”},”link”:{“filters”:{“search”:””},”name”:”link”}}}}]}]}]}]}],”version”:”4.4.1″} –><\/p>\n

Parsippany, NJ \u2014 Jan. 26, 2023 \u2014 <\/strong>Provenir, a global leader in data and AI-powered risk decisioning software, announced today that Quick Finans, a consumer finance company located in Turkey, has selected Provenir\u2019s AI-Powered Data and Decisioning Platform to quickly approve and onboard new customers.<\/p>\n

<\/p>\n

Quick Finans, a wholly owned subsidiary of Quick Insurance, which is under the umbrella of Maher Holding, offers solutions for consumer finance loans (GPL), auto financing, mortgages, agricultural financing, and small business lending. They were looking for a low\/no code platform that could be deployed quickly, modified in real-time and scale as the company expands its offerings.<\/p>\n

<\/p>\n

\u201cAfter evaluating several options, we determined that Provenir best met our requirements and could support our aggressive growth strategies,\u201d said Cumhur Ta\u015f \u2013 Deputy General Manager responsible for Credit & Operations in Quick Finans. \u201cThe platform provides the flexibility we need to power our business now and in the future. Another key differentiator was the ability to easily access and integrate new data sources to help us gain a more holistic view of our applicants and customers.\u201d<\/p>\n

<\/p>\n

\u201cWe are pleased to partner with Quick Finans to develop real-time decisioning solutions that will provide a superior customer experience,\u201d said Emre Unlusoy, Regional Manager for Provenir. \u201cProvenir\u2019s no-code, visual UI eliminates vendor and development team reliance, and will provide Quick Finans the flexibility and agility needed to rapidly make changes, test new strategies and get products to market faster.\u201d<\/p>\n

<\/p>\n

Provenir\u2019s industry-leading AI-Powered Data and Decisioning Platform is data fueled and AI driven for smarter risk decisioning. The solution, managed through a single UI, empowers organizations to innovate further and faster than ever before, driving the continuous optimization they need to power growth and agility, without increasing risk. With the unique combination of universal access to data, embedded AI and world-class decisioning technology, Provenir provides a cohesive risk ecosystem to enable smarter decisions across the entire customer lifecycle \u2013 offering diverse data for deeper insights, auto-optimized decisions, and a continuous feedback loop for constant improvement both at onboarding when assessing risk and monitoring ongoing transactions for fraud.<\/p>“,”margin”:”default”}}]},{“type”:”column”,”props”:{“image_position”:”center-center”,”padding”:”small”,”position_sticky”:”row”,”position_sticky_breakpoint”:”m”,”position_sticky_offset”:”100″,”style”:”card-default”,”width_medium”:”1-3″},”children”:[{“type”:”headline”,”props”:{“content”:”The Ultimate Guide to Decision Engines”,”text_align”:”center”,”title_color”:”success”,”title_element”:”h3″,”title_style”:”h3″}},{“type”:”text”,”props”:{“column_breakpoint”:”m”,”content”:”

What is a decision engine and how does it help your business processes?<\/p>“,”margin”:”default”,”text_align”:”center”}},{“type”:”button”,”props”:{“grid_column_gap”:”small”,”grid_row_gap”:””,”margin”:””,”margin_remove_bottom”:false,”maxwidth”:”medium”,”text_align”:”center”},”children”:[{“type”:”button_item”,”props”:{“button_style”:”default”,”content”:”Learn More”,”icon”:””,”icon_align”:”left”,”link”:”\/blog\/the-ultimate-guide-to-decision-engines\/”}}]}]}],”props”:{“layout”:”2-3,1-3″}}]},{“type”:”section”,”props”:{“image_position”:”center-center”,”style”:”secondary”,”title_breakpoint”:”xl”,”title_position”:”top-left”,”title_rotation”:”left”,”vertical_align”:””,”width”:”default”},”children”:[{“type”:”row”,”children”:[{“type”:”column”,”props”:{“image_position”:”center-center”,”position_sticky_breakpoint”:”m”},”children”:[{“type”:”divider”,”props”:{“divider_element”:”hr”}},{“type”:”headline”,”props”:{“content”:”LATEST NEWS”,”title_color”:”background”,”title_element”:”h1″,”title_style”:”text-large”}},{“type”:”grid”,”props”:{“content_column_breakpoint”:”m”,”filter_align”:”left”,”filter_all”:true,”filter_grid_breakpoint”:”m”,”filter_grid_width”:”auto”,”filter_position”:”top”,”filter_style”:”tab”,”grid_column_align”:false,”grid_default”:”auto”,”grid_divider”:true,”grid_large”:”3″,”grid_medium”:”3″,”grid_parallax_justify”:true,”grid_row_align”:false,”grid_xlarge”:”3″,”icon_width”:80,”image_align”:”top”,”image_grid_breakpoint”:”m”,”image_grid_width”:”1-2″,”image_link”:true,”image_svg_color”:”emphasis”,”image_transition”:”scale-up”,”image_transition_border”:false,”item_animation”:true,”link_size”:”small”,”link_style”:”default”,”link_text”:”Read more”,”margin”:”default”,”meta_align”:”below-title”,”meta_element”:”div”,”meta_style”:”text-meta”,”show_content”:true,”show_image”:true,”show_link”:true,”show_meta”:true,”show_title”:true,”title_align”:”top”,”title_color”:”success”,”title_element”:”h3″,”title_grid_breakpoint”:”m”,”title_grid_width”:”1-2″,”title_hover_style”:”reset”,”title_link”:true},”children”:[{“type”:”grid_item”,”source”:{“query”:{“name”:”posts.customPosts”,”arguments”:{“terms”:[52],”category_operator”:”IN”,”post_tag_operator”:”IN”,”users”:[],”users_operator”:”IN”,”offset”:0,”limit”:3,”order”:”date”,”order_direction”:”DESC”,”industry_operator”:”IN”,”language_operator”:”IN”,”resources_operator”:”IN”}},”props”:{“_condition”:{“filters”:{“condition”:”!!”},”name”:”author.name”},”title”:{“filters”:{“search”:””},”name”:”title”},”content”:{“filters”:{“search”:””,”limit”:100},”name”:”excerpt”},”image”:{“filters”:{“search”:””},”name”:”featuredImage.url”},”link”:{“filters”:{“search”:””},”name”:”link”}}}}]}]}]}]}],”version”:”4.4.1″} –><\/p>\n

Provenir\u2019s no-code platform delivers rapid deployment, flexibility and scalability for a growing company<\/em><\/p>\n

<\/p>\n

Parsippany, NJ \u2014 Jan. 26, 2023 \u2014 <\/strong>Provenir, a global leader in data and AI-powered risk decisioning software, announced today that Quick Finans, a consumer finance company located in Turkey, has selected Provenir\u2019s AI-Powered Data and Decisioning Platform to quickly approve and onboard new customers.<\/p>\n

<\/p>\n

Quick Finans, a wholly owned subsidiary of Quick Insurance, which is under the umbrella of Maher Holding, offers solutions for consumer finance loans (GPL), auto financing, mortgages, agricultural financing, and small business lending. They were looking for a low\/no code platform that could be deployed quickly, modified in real-time and scale as the company expands its offerings.<\/p>\n

<\/p>\n

\u201cAfter evaluating several options, we determined that Provenir best met our requirements and could support our aggressive growth strategies,\u201d said Cumhur Ta\u015f \u2013 Deputy General Manager responsible for Credit & Operations in Quick Finans. \u201cThe platform provides the flexibility we need to power our business now and in the future. Another key differentiator was the ability to easily access and integrate new data sources to help us gain a more holistic view of our applicants and customers.\u201d<\/p>\n

<\/p>\n

\u201cWe are pleased to partner with Quick Finans to develop real-time decisioning solutions that will provide a superior customer experience,\u201d said Emre Unlusoy, Regional Manager for Provenir. \u201cProvenir\u2019s no-code, visual UI eliminates vendor and development team reliance, and will provide Quick Finans the flexibility and agility needed to rapidly make changes, test new strategies and get products to market faster.\u201d<\/p>\n

<\/p>\n

Provenir\u2019s industry-leading AI-Powered Data and Decisioning Platform is data fueled and AI driven for smarter risk decisioning. The solution, managed through a single UI, empowers organizations to innovate further and faster than ever before, driving the continuous optimization they need to power growth and agility, without increasing risk. With the unique combination of universal access to data, embedded AI and world-class decisioning technology, Provenir provides a cohesive risk ecosystem to enable smarter decisions across the entire customer lifecycle \u2013 offering diverse data for deeper insights, auto-optimized decisions, and a continuous feedback loop for constant improvement both at onboarding when assessing risk and monitoring ongoing transactions for fraud.<\/p>“,”margin”:”default”}}]},{“type”:”column”,”props”:{“image_position”:”center-center”,”padding”:”small”,”position_sticky”:”row”,”position_sticky_breakpoint”:”m”,”position_sticky_offset”:”100″,”style”:”card-default”,”width_medium”:”1-3″},”children”:[{“type”:”headline”,”props”:{“content”:”The Ultimate Guide to Decision Engines”,”text_align”:”center”,”title_color”:”success”,”title_element”:”h3″,”title_style”:”h3″}},{“type”:”text”,”props”:{“column_breakpoint”:”m”,”content”:”

What is a decision engine and how does it help your business processes?<\/p>“,”margin”:”default”,”text_align”:”center”}},{“type”:”button”,”props”:{“grid_column_gap”:”small”,”grid_row_gap”:””,”margin”:””,”margin_remove_bottom”:false,”maxwidth”:”medium”,”text_align”:”center”},”children”:[{“type”:”button_item”,”props”:{“button_style”:”default”,”content”:”Learn More”,”icon”:””,”icon_align”:”left”,”link”:”\/blog\/the-ultimate-guide-to-decision-engines\/”}}]}]}],”props”:{“layout”:”2-3,1-3″}}]},{“type”:”section”,”props”:{“image_position”:”center-center”,”style”:”secondary”,”title_breakpoint”:”xl”,”title_position”:”top-left”,”title_rotation”:”left”,”vertical_align”:””,”width”:”default”},”children”:[{“type”:”row”,”children”:[{“type”:”column”,”props”:{“image_position”:”center-center”,”position_sticky_breakpoint”:”m”},”children”:[{“type”:”divider”,”props”:{“divider_element”:”hr”}},{“type”:”headline”,”props”:{“content”:”LATEST NEWS”,”title_color”:”background”,”title_element”:”h1″,”title_style”:”text-large”}},{“type”:”grid”,”props”:{“content_column_breakpoint”:”m”,”filter_align”:”left”,”filter_all”:true,”filter_grid_breakpoint”:”m”,”filter_grid_width”:”auto”,”filter_position”:”top”,”filter_style”:”tab”,”grid_column_align”:false,”grid_default”:”auto”,”grid_divider”:true,”grid_large”:”3″,”grid_medium”:”3″,”grid_parallax_justify”:true,”grid_row_align”:false,”grid_xlarge”:”3″,”icon_width”:80,”image_align”:”top”,”image_grid_breakpoint”:”m”,”image_grid_width”:”1-2″,”image_link”:true,”image_svg_color”:”emphasis”,”image_transition”:”scale-up”,”image_transition_border”:false,”item_animation”:true,”link_size”:”small”,”link_style”:”default”,”link_text”:”Read more”,”margin”:”default”,”meta_align”:”below-title”,”meta_element”:”div”,”meta_style”:”text-meta”,”show_content”:true,”show_image”:true,”show_link”:true,”show_meta”:true,”show_title”:true,”title_align”:”top”,”title_color”:”success”,”title_element”:”h3″,”title_grid_breakpoint”:”m”,”title_grid_width”:”1-2″,”title_hover_style”:”reset”,”title_link”:true},”children”:[{“type”:”grid_item”,”source”:{“query”:{“name”:”posts.customPosts”,”arguments”:{“terms”:[52],”category_operator”:”IN”,”post_tag_operator”:”IN”,”users”:[],”users_operator”:”IN”,”offset”:0,”limit”:3,”order”:”date”,”order_direction”:”DESC”,”industry_operator”:”IN”,”language_operator”:”IN”,”resources_operator”:”IN”}},”props”:{“_condition”:{“filters”:{“condition”:”!!”},”name”:”author.name”},”title”:{“filters”:{“search”:””},”name”:”title”},”content”:{“filters”:{“search”:””,”limit”:100},”name”:”excerpt”},”image”:{“filters”:{“search”:””},”name”:”featuredImage.url”},”link”:{“filters”:{“search”:””},”name”:”link”}}}}]}]}]}]}],”version”:”4.4.1″} –>

The Ultimate Guide to Decision Engines

What is a decision engine and how does it help your business processes?

Learn More


LATEST NEWS

(more…)

<\/p>\n

Parsippany, NJ \u2014 Jan. 26, 2023 \u2014 <\/strong>Provenir, a global leader in data and AI-powered risk decisioning software, announced today that Quick Finans, a consumer finance company located in Turkey, has selected Provenir\u2019s AI-Powered Data and Decisioning Platform to quickly approve and onboard new customers.<\/p>\n

<\/p>\n

Quick Finans, a wholly owned subsidiary of Quick Insurance, which is under the umbrella of Maher Holding, offers solutions for consumer finance loans (GPL), auto financing, mortgages, agricultural financing, and small business lending. They were looking for a low\/no code platform that could be deployed quickly, modified in real-time and scale as the company expands its offerings.<\/p>\n

<\/p>\n

\u201cAfter evaluating several options, we determined that Provenir best met our requirements and could support our aggressive growth strategies,\u201d said Cumhur Ta\u015f \u2013 Deputy General Manager responsible for Credit & Operations in Quick Finans. \u201cThe platform provides the flexibility we need to power our business now and in the future. Another key differentiator was the ability to easily access and integrate new data sources to help us gain a more holistic view of our applicants and customers.\u201d<\/p>\n

<\/p>\n

\u201cWe are pleased to partner with Quick Finans to develop real-time decisioning solutions that will provide a superior customer experience,\u201d said Emre Unlusoy, Regional Manager for Provenir. \u201cProvenir\u2019s no-code, visual UI eliminates vendor and development team reliance, and will provide Quick Finans the flexibility and agility needed to rapidly make changes, test new strategies and get products to market faster.\u201d<\/p>\n

<\/p>\n

Provenir\u2019s industry-leading AI-Powered Data and Decisioning Platform is data fueled and AI driven for smarter risk decisioning. The solution, managed through a single UI, empowers organizations to innovate further and faster than ever before, driving the continuous optimization they need to power growth and agility, without increasing risk. With the unique combination of universal access to data, embedded AI and world-class decisioning technology, Provenir provides a cohesive risk ecosystem to enable smarter decisions across the entire customer lifecycle \u2013 offering diverse data for deeper insights, auto-optimized decisions, and a continuous feedback loop for constant improvement both at onboarding when assessing risk and monitoring ongoing transactions for fraud.<\/p>“,”margin”:”default”}}]},{“type”:”column”,”props”:{“image_position”:”center-center”,”padding”:”small”,”position_sticky”:”row”,”position_sticky_breakpoint”:”m”,”position_sticky_offset”:”100″,”style”:”card-default”,”width_medium”:”1-3″},”children”:[{“type”:”headline”,”props”:{“content”:”The Ultimate Guide to Decision Engines”,”text_align”:”center”,”title_color”:”success”,”title_element”:”h3″,”title_style”:”h3″}},{“type”:”text”,”props”:{“column_breakpoint”:”m”,”content”:”

What is a decision engine and how does it help your business processes?<\/p>“,”margin”:”default”,”text_align”:”center”}},{“type”:”button”,”props”:{“grid_column_gap”:”small”,”grid_row_gap”:””,”margin”:””,”margin_remove_bottom”:false,”maxwidth”:”medium”,”text_align”:”center”},”children”:[{“type”:”button_item”,”props”:{“button_style”:”default”,”content”:”Learn More”,”icon”:””,”icon_align”:”left”,”link”:”\/blog\/the-ultimate-guide-to-decision-engines\/”}}]}]}],”props”:{“layout”:”2-3,1-3″}}]},{“type”:”section”,”props”:{“image_position”:”center-center”,”style”:”secondary”,”title_breakpoint”:”xl”,”title_position”:”top-left”,”title_rotation”:”left”,”vertical_align”:””,”width”:”default”},”children”:[{“type”:”row”,”children”:[{“type”:”column”,”props”:{“image_position”:”center-center”,”position_sticky_breakpoint”:”m”},”children”:[{“type”:”divider”,”props”:{“divider_element”:”hr”}},{“type”:”headline”,”props”:{“content”:”LATEST NEWS”,”title_color”:”background”,”title_element”:”h1″,”title_style”:”text-large”}},{“type”:”grid”,”props”:{“content_column_breakpoint”:”m”,”filter_align”:”left”,”filter_all”:true,”filter_grid_breakpoint”:”m”,”filter_grid_width”:”auto”,”filter_position”:”top”,”filter_style”:”tab”,”grid_column_align”:false,”grid_default”:”auto”,”grid_divider”:true,”grid_large”:”3″,”grid_medium”:”3″,”grid_parallax_justify”:true,”grid_row_align”:false,”grid_xlarge”:”3″,”icon_width”:80,”image_align”:”top”,”image_grid_breakpoint”:”m”,”image_grid_width”:”1-2″,”image_link”:true,”image_svg_color”:”emphasis”,”image_transition”:”scale-up”,”image_transition_border”:false,”item_animation”:true,”link_size”:”small”,”link_style”:”default”,”link_text”:”Read more”,”margin”:”default”,”meta_align”:”below-title”,”meta_element”:”div”,”meta_style”:”text-meta”,”show_content”:true,”show_image”:true,”show_link”:true,”show_meta”:true,”show_title”:true,”title_align”:”top”,”title_color”:”success”,”title_element”:”h3″,”title_grid_breakpoint”:”m”,”title_grid_width”:”1-2″,”title_hover_style”:”reset”,”title_link”:true},”children”:[{“type”:”grid_item”,”source”:{“query”:{“name”:”posts.customPosts”,”arguments”:{“terms”:[52],”category_operator”:”IN”,”post_tag_operator”:”IN”,”users”:[],”users_operator”:”IN”,”offset”:0,”limit”:3,”order”:”date”,”order_direction”:”DESC”,”industry_operator”:”IN”,”language_operator”:”IN”,”resources_operator”:”IN”}},”props”:{“_condition”:{“filters”:{“condition”:”!!”},”name”:”author.name”},”title”:{“filters”:{“search”:””},”name”:”title”},”content”:{“filters”:{“search”:””,”limit”:100},”name”:”excerpt”},”image”:{“filters”:{“search”:””},”name”:”featuredImage.url”},”link”:{“filters”:{“search”:””},”name”:”link”}}}}]}]}]}]}],”version”:”4.4.1″} –><\/p>\n

Provenir\u2019s no-code platform delivers rapid deployment, flexibility and scalability for a growing company<\/em><\/p>\n

<\/p>\n

Parsippany, NJ \u2014 Jan. 26, 2023 \u2014 <\/strong>Provenir, a global leader in data and AI-powered risk decisioning software, announced today that Quick Finans, a consumer finance company located in Turkey, has selected Provenir\u2019s AI-Powered Data and Decisioning Platform to quickly approve and onboard new customers.<\/p>\n

<\/p>\n

Quick Finans, a wholly owned subsidiary of Quick Insurance, which is under the umbrella of Maher Holding, offers solutions for consumer finance loans (GPL), auto financing, mortgages, agricultural financing, and small business lending. They were looking for a low\/no code platform that could be deployed quickly, modified in real-time and scale as the company expands its offerings.<\/p>\n

<\/p>\n

\u201cAfter evaluating several options, we determined that Provenir best met our requirements and could support our aggressive growth strategies,\u201d said Cumhur Ta\u015f \u2013 Deputy General Manager responsible for Credit & Operations in Quick Finans. \u201cThe platform provides the flexibility we need to power our business now and in the future. Another key differentiator was the ability to easily access and integrate new data sources to help us gain a more holistic view of our applicants and customers.\u201d<\/p>\n

<\/p>\n

\u201cWe are pleased to partner with Quick Finans to develop real-time decisioning solutions that will provide a superior customer experience,\u201d said Emre Unlusoy, Regional Manager for Provenir. \u201cProvenir\u2019s no-code, visual UI eliminates vendor and development team reliance, and will provide Quick Finans the flexibility and agility needed to rapidly make changes, test new strategies and get products to market faster.\u201d<\/p>\n

<\/p>\n

Provenir\u2019s industry-leading AI-Powered Data and Decisioning Platform is data fueled and AI driven for smarter risk decisioning. The solution, managed through a single UI, empowers organizations to innovate further and faster than ever before, driving the continuous optimization they need to power growth and agility, without increasing risk. With the unique combination of universal access to data, embedded AI and world-class decisioning technology, Provenir provides a cohesive risk ecosystem to enable smarter decisions across the entire customer lifecycle \u2013 offering diverse data for deeper insights, auto-optimized decisions, and a continuous feedback loop for constant improvement both at onboarding when assessing risk and monitoring ongoing transactions for fraud.<\/p>“,”margin”:”default”}}]},{“type”:”column”,”props”:{“image_position”:”center-center”,”padding”:”small”,”position_sticky”:”row”,”position_sticky_breakpoint”:”m”,”position_sticky_offset”:”100″,”style”:”card-default”,”width_medium”:”1-3″},”children”:[{“type”:”headline”,”props”:{“content”:”The Ultimate Guide to Decision Engines”,”text_align”:”center”,”title_color”:”success”,”title_element”:”h3″,”title_style”:”h3″}},{“type”:”text”,”props”:{“column_breakpoint”:”m”,”content”:”

What is a decision engine and how does it help your business processes?<\/p>“,”margin”:”default”,”text_align”:”center”}},{“type”:”button”,”props”:{“grid_column_gap”:”small”,”grid_row_gap”:””,”margin”:””,”margin_remove_bottom”:false,”maxwidth”:”medium”,”text_align”:”center”},”children”:[{“type”:”button_item”,”props”:{“button_style”:”default”,”content”:”Learn More”,”icon”:””,”icon_align”:”left”,”link”:”\/blog\/the-ultimate-guide-to-decision-engines\/”}}]}]}],”props”:{“layout”:”2-3,1-3″}}]},{“type”:”section”,”props”:{“image_position”:”center-center”,”style”:”secondary”,”title_breakpoint”:”xl”,”title_position”:”top-left”,”title_rotation”:”left”,”vertical_align”:””,”width”:”default”},”children”:[{“type”:”row”,”children”:[{“type”:”column”,”props”:{“image_position”:”center-center”,”position_sticky_breakpoint”:”m”},”children”:[{“type”:”divider”,”props”:{“divider_element”:”hr”}},{“type”:”headline”,”props”:{“content”:”LATEST NEWS”,”title_color”:”background”,”title_element”:”h1″,”title_style”:”text-large”}},{“type”:”grid”,”props”:{“content_column_breakpoint”:”m”,”filter_align”:”left”,”filter_all”:true,”filter_grid_breakpoint”:”m”,”filter_grid_width”:”auto”,”filter_position”:”top”,”filter_style”:”tab”,”grid_column_align”:false,”grid_default”:”auto”,”grid_divider”:true,”grid_large”:”3″,”grid_medium”:”3″,”grid_parallax_justify”:true,”grid_row_align”:false,”grid_xlarge”:”3″,”icon_width”:80,”image_align”:”top”,”image_grid_breakpoint”:”m”,”image_grid_width”:”1-2″,”image_link”:true,”image_svg_color”:”emphasis”,”image_transition”:”scale-up”,”image_transition_border”:false,”item_animation”:true,”link_size”:”small”,”link_style”:”default”,”link_text”:”Read more”,”margin”:”default”,”meta_align”:”below-title”,”meta_element”:”div”,”meta_style”:”text-meta”,”show_content”:true,”show_image”:true,”show_link”:true,”show_meta”:true,”show_title”:true,”title_align”:”top”,”title_color”:”success”,”title_element”:”h3″,”title_grid_breakpoint”:”m”,”title_grid_width”:”1-2″,”title_hover_style”:”reset”,”title_link”:true},”children”:[{“type”:”grid_item”,”source”:{“query”:{“name”:”posts.customPosts”,”arguments”:{“terms”:[52],”category_operator”:”IN”,”post_tag_operator”:”IN”,”users”:[],”users_operator”:”IN”,”offset”:0,”limit”:3,”order”:”date”,”order_direction”:”DESC”,”industry_operator”:”IN”,”language_operator”:”IN”,”resources_operator”:”IN”}},”props”:{“_condition”:{“filters”:{“condition”:”!!”},”name”:”author.name”},”title”:{“filters”:{“search”:””},”name”:”title”},”content”:{“filters”:{“search”:””,”limit”:100},”name”:”excerpt”},”image”:{“filters”:{“search”:””},”name”:”featuredImage.url”},”link”:{“filters”:{“search”:””},”name”:”link”}}}}]}]}]}]}],”version”:”4.4.1″} –>

The Ultimate Guide to Decision Engines

What is a decision engine and how does it help your business processes?

Learn More


LATEST NEWS

<\/p>\n

\u201cAfter evaluating several options, we determined that Provenir best met our requirements and could support our aggressive growth strategies,\u201d said Cumhur Ta\u015f \u2013 Deputy General Manager responsible for Credit & Operations in Quick Finans. \u201cThe platform provides the flexibility we need to power our business now and in the future. Another key differentiator was the ability to easily access and integrate new data sources to help us gain a more holistic view of our applicants and customers.\u201d<\/p>\n

<\/p>\n

\u201cWe are pleased to partner with Quick Finans to develop real-time decisioning solutions that will provide a superior customer experience,\u201d said Emre Unlusoy, Regional Manager for Provenir. \u201cProvenir\u2019s no-code, visual UI eliminates vendor and development team reliance, and will provide Quick Finans the flexibility and agility needed to rapidly make changes, test new strategies and get products to market faster.\u201d<\/p>\n

<\/p>\n

Provenir\u2019s industry-leading AI-Powered Data and Decisioning Platform is data fueled and AI driven for smarter risk decisioning. The solution, managed through a single UI, empowers organizations to innovate further and faster than ever before, driving the continuous optimization they need to power growth and agility, without increasing risk. With the unique combination of universal access to data, embedded AI and world-class decisioning technology, Provenir provides a cohesive risk ecosystem to enable smarter decisions across the entire customer lifecycle \u2013 offering diverse data for deeper insights, auto-optimized decisions, and a continuous feedback loop for constant improvement both at onboarding when assessing risk and monitoring ongoing transactions for fraud.<\/p>“,”margin”:”default”}}]},{“type”:”column”,”props”:{“image_position”:”center-center”,”padding”:”small”,”position_sticky”:”row”,”position_sticky_breakpoint”:”m”,”position_sticky_offset”:”100″,”style”:”card-default”,”width_medium”:”1-3″},”children”:[{“type”:”headline”,”props”:{“content”:”The Ultimate Guide to Decision Engines”,”text_align”:”center”,”title_color”:”success”,”title_element”:”h3″,”title_style”:”h3″}},{“type”:”text”,”props”:{“column_breakpoint”:”m”,”content”:”

What is a decision engine and how does it help your business processes?<\/p>“,”margin”:”default”,”text_align”:”center”}},{“type”:”button”,”props”:{“grid_column_gap”:”small”,”grid_row_gap”:””,”margin”:””,”margin_remove_bottom”:false,”maxwidth”:”medium”,”text_align”:”center”},”children”:[{“type”:”button_item”,”props”:{“button_style”:”default”,”content”:”Learn More”,”icon”:””,”icon_align”:”left”,”link”:”\/blog\/the-ultimate-guide-to-decision-engines\/”}}]}]}],”props”:{“layout”:”2-3,1-3″}}]},{“type”:”section”,”props”:{“image_position”:”center-center”,”style”:”secondary”,”title_breakpoint”:”xl”,”title_position”:”top-left”,”title_rotation”:”left”,”vertical_align”:””,”width”:”default”},”children”:[{“type”:”row”,”children”:[{“type”:”column”,”props”:{“image_position”:”center-center”,”position_sticky_breakpoint”:”m”},”children”:[{“type”:”divider”,”props”:{“divider_element”:”hr”}},{“type”:”headline”,”props”:{“content”:”LATEST NEWS”,”title_color”:”background”,”title_element”:”h1″,”title_style”:”text-large”}},{“type”:”grid”,”props”:{“content_column_breakpoint”:”m”,”filter_align”:”left”,”filter_all”:true,”filter_grid_breakpoint”:”m”,”filter_grid_width”:”auto”,”filter_position”:”top”,”filter_style”:”tab”,”grid_column_align”:false,”grid_default”:”auto”,”grid_divider”:true,”grid_large”:”3″,”grid_medium”:”3″,”grid_parallax_justify”:true,”grid_row_align”:false,”grid_xlarge”:”3″,”icon_width”:80,”image_align”:”top”,”image_grid_breakpoint”:”m”,”image_grid_width”:”1-2″,”image_link”:true,”image_svg_color”:”emphasis”,”image_transition”:”scale-up”,”image_transition_border”:false,”item_animation”:true,”link_size”:”small”,”link_style”:”default”,”link_text”:”Read more”,”margin”:”default”,”meta_align”:”below-title”,”meta_element”:”div”,”meta_style”:”text-meta”,”show_content”:true,”show_image”:true,”show_link”:true,”show_meta”:true,”show_title”:true,”title_align”:”top”,”title_color”:”success”,”title_element”:”h3″,”title_grid_breakpoint”:”m”,”title_grid_width”:”1-2″,”title_hover_style”:”reset”,”title_link”:true},”children”:[{“type”:”grid_item”,”source”:{“query”:{“name”:”posts.customPosts”,”arguments”:{“terms”:[52],”category_operator”:”IN”,”post_tag_operator”:”IN”,”users”:[],”users_operator”:”IN”,”offset”:0,”limit”:3,”order”:”date”,”order_direction”:”DESC”,”industry_operator”:”IN”,”language_operator”:”IN”,”resources_operator”:”IN”}},”props”:{“_condition”:{“filters”:{“condition”:”!!”},”name”:”author.name”},”title”:{“filters”:{“search”:””},”name”:”title”},”content”:{“filters”:{“search”:””,”limit”:100},”name”:”excerpt”},”image”:{“filters”:{“search”:””},”name”:”featuredImage.url”},”link”:{“filters”:{“search”:””},”name”:”link”}}}}]}]}]}]}],”version”:”4.4.1″} –><\/p>\n

Parsippany, NJ \u2014 Jan. 26, 2023 \u2014 <\/strong>Provenir, a global leader in data and AI-powered risk decisioning software, announced today that Quick Finans, a consumer finance company located in Turkey, has selected Provenir\u2019s AI-Powered Data and Decisioning Platform to quickly approve and onboard new customers.<\/p>\n

<\/p>\n

Quick Finans, a wholly owned subsidiary of Quick Insurance, which is under the umbrella of Maher Holding, offers solutions for consumer finance loans (GPL), auto financing, mortgages, agricultural financing, and small business lending. They were looking for a low\/no code platform that could be deployed quickly, modified in real-time and scale as the company expands its offerings.<\/p>\n

<\/p>\n

\u201cAfter evaluating several options, we determined that Provenir best met our requirements and could support our aggressive growth strategies,\u201d said Cumhur Ta\u015f \u2013 Deputy General Manager responsible for Credit & Operations in Quick Finans. \u201cThe platform provides the flexibility we need to power our business now and in the future. Another key differentiator was the ability to easily access and integrate new data sources to help us gain a more holistic view of our applicants and customers.\u201d<\/p>\n

<\/p>\n

\u201cWe are pleased to partner with Quick Finans to develop real-time decisioning solutions that will provide a superior customer experience,\u201d said Emre Unlusoy, Regional Manager for Provenir. \u201cProvenir\u2019s no-code, visual UI eliminates vendor and development team reliance, and will provide Quick Finans the flexibility and agility needed to rapidly make changes, test new strategies and get products to market faster.\u201d<\/p>\n

<\/p>\n

Provenir\u2019s industry-leading AI-Powered Data and Decisioning Platform is data fueled and AI driven for smarter risk decisioning. The solution, managed through a single UI, empowers organizations to innovate further and faster than ever before, driving the continuous optimization they need to power growth and agility, without increasing risk. With the unique combination of universal access to data, embedded AI and world-class decisioning technology, Provenir provides a cohesive risk ecosystem to enable smarter decisions across the entire customer lifecycle \u2013 offering diverse data for deeper insights, auto-optimized decisions, and a continuous feedback loop for constant improvement both at onboarding when assessing risk and monitoring ongoing transactions for fraud.<\/p>“,”margin”:”default”}}]},{“type”:”column”,”props”:{“image_position”:”center-center”,”padding”:”small”,”position_sticky”:”row”,”position_sticky_breakpoint”:”m”,”position_sticky_offset”:”100″,”style”:”card-default”,”width_medium”:”1-3″},”children”:[{“type”:”headline”,”props”:{“content”:”The Ultimate Guide to Decision Engines”,”text_align”:”center”,”title_color”:”success”,”title_element”:”h3″,”title_style”:”h3″}},{“type”:”text”,”props”:{“column_breakpoint”:”m”,”content”:”

What is a decision engine and how does it help your business processes?<\/p>“,”margin”:”default”,”text_align”:”center”}},{“type”:”button”,”props”:{“grid_column_gap”:”small”,”grid_row_gap”:””,”margin”:””,”margin_remove_bottom”:false,”maxwidth”:”medium”,”text_align”:”center”},”children”:[{“type”:”button_item”,”props”:{“button_style”:”default”,”content”:”Learn More”,”icon”:””,”icon_align”:”left”,”link”:”\/blog\/the-ultimate-guide-to-decision-engines\/”}}]}]}],”props”:{“layout”:”2-3,1-3″}}]},{“type”:”section”,”props”:{“image_position”:”center-center”,”style”:”secondary”,”title_breakpoint”:”xl”,”title_position”:”top-left”,”title_rotation”:”left”,”vertical_align”:””,”width”:”default”},”children”:[{“type”:”row”,”children”:[{“type”:”column”,”props”:{“image_position”:”center-center”,”position_sticky_breakpoint”:”m”},”children”:[{“type”:”divider”,”props”:{“divider_element”:”hr”}},{“type”:”headline”,”props”:{“content”:”LATEST NEWS”,”title_color”:”background”,”title_element”:”h1″,”title_style”:”text-large”}},{“type”:”grid”,”props”:{“content_column_breakpoint”:”m”,”filter_align”:”left”,”filter_all”:true,”filter_grid_breakpoint”:”m”,”filter_grid_width”:”auto”,”filter_position”:”top”,”filter_style”:”tab”,”grid_column_align”:false,”grid_default”:”auto”,”grid_divider”:true,”grid_large”:”3″,”grid_medium”:”3″,”grid_parallax_justify”:true,”grid_row_align”:false,”grid_xlarge”:”3″,”icon_width”:80,”image_align”:”top”,”image_grid_breakpoint”:”m”,”image_grid_width”:”1-2″,”image_link”:true,”image_svg_color”:”emphasis”,”image_transition”:”scale-up”,”image_transition_border”:false,”item_animation”:true,”link_size”:”small”,”link_style”:”default”,”link_text”:”Read more”,”margin”:”default”,”meta_align”:”below-title”,”meta_element”:”div”,”meta_style”:”text-meta”,”show_content”:true,”show_image”:true,”show_link”:true,”show_meta”:true,”show_title”:true,”title_align”:”top”,”title_color”:”success”,”title_element”:”h3″,”title_grid_breakpoint”:”m”,”title_grid_width”:”1-2″,”title_hover_style”:”reset”,”title_link”:true},”children”:[{“type”:”grid_item”,”source”:{“query”:{“name”:”posts.customPosts”,”arguments”:{“terms”:[52],”category_operator”:”IN”,”post_tag_operator”:”IN”,”users”:[],”users_operator”:”IN”,”offset”:0,”limit”:3,”order”:”date”,”order_direction”:”DESC”,”industry_operator”:”IN”,”language_operator”:”IN”,”resources_operator”:”IN”}},”props”:{“_condition”:{“filters”:{“condition”:”!!”},”name”:”author.name”},”title”:{“filters”:{“search”:””},”name”:”title”},”content”:{“filters”:{“search”:””,”limit”:100},”name”:”excerpt”},”image”:{“filters”:{“search”:””},”name”:”featuredImage.url”},”link”:{“filters”:{“search”:””},”name”:”link”}}}}]}]}]}]}],”version”:”4.4.1″} –><\/p>\n

Provenir\u2019s no-code platform delivers rapid deployment, flexibility and scalability for a growing company<\/em><\/p>\n

<\/p>\n

Parsippany, NJ \u2014 Jan. 26, 2023 \u2014 <\/strong>Provenir, a global leader in data and AI-powered risk decisioning software, announced today that Quick Finans, a consumer finance company located in Turkey, has selected Provenir\u2019s AI-Powered Data and Decisioning Platform to quickly approve and onboard new customers.<\/p>\n

<\/p>\n

Quick Finans, a wholly owned subsidiary of Quick Insurance, which is under the umbrella of Maher Holding, offers solutions for consumer finance loans (GPL), auto financing, mortgages, agricultural financing, and small business lending. They were looking for a low\/no code platform that could be deployed quickly, modified in real-time and scale as the company expands its offerings.<\/p>\n

<\/p>\n

\u201cAfter evaluating several options, we determined that Provenir best met our requirements and could support our aggressive growth strategies,\u201d said Cumhur Ta\u015f \u2013 Deputy General Manager responsible for Credit & Operations in Quick Finans. \u201cThe platform provides the flexibility we need to power our business now and in the future. Another key differentiator was the ability to easily access and integrate new data sources to help us gain a more holistic view of our applicants and customers.\u201d<\/p>\n

<\/p>\n

\u201cWe are pleased to partner with Quick Finans to develop real-time decisioning solutions that will provide a superior customer experience,\u201d said Emre Unlusoy, Regional Manager for Provenir. \u201cProvenir\u2019s no-code, visual UI eliminates vendor and development team reliance, and will provide Quick Finans the flexibility and agility needed to rapidly make changes, test new strategies and get products to market faster.\u201d<\/p>\n

<\/p>\n

Provenir\u2019s industry-leading AI-Powered Data and Decisioning Platform is data fueled and AI driven for smarter risk decisioning. The solution, managed through a single UI, empowers organizations to innovate further and faster than ever before, driving the continuous optimization they need to power growth and agility, without increasing risk. With the unique combination of universal access to data, embedded AI and world-class decisioning technology, Provenir provides a cohesive risk ecosystem to enable smarter decisions across the entire customer lifecycle \u2013 offering diverse data for deeper insights, auto-optimized decisions, and a continuous feedback loop for constant improvement both at onboarding when assessing risk and monitoring ongoing transactions for fraud.<\/p>“,”margin”:”default”}}]},{“type”:”column”,”props”:{“image_position”:”center-center”,”padding”:”small”,”position_sticky”:”row”,”position_sticky_breakpoint”:”m”,”position_sticky_offset”:”100″,”style”:”card-default”,”width_medium”:”1-3″},”children”:[{“type”:”headline”,”props”:{“content”:”The Ultimate Guide to Decision Engines”,”text_align”:”center”,”title_color”:”success”,”title_element”:”h3″,”title_style”:”h3″}},{“type”:”text”,”props”:{“column_breakpoint”:”m”,”content”:”

What is a decision engine and how does it help your business processes?<\/p>“,”margin”:”default”,”text_align”:”center”}},{“type”:”button”,”props”:{“grid_column_gap”:”small”,”grid_row_gap”:””,”margin”:””,”margin_remove_bottom”:false,”maxwidth”:”medium”,”text_align”:”center”},”children”:[{“type”:”button_item”,”props”:{“button_style”:”default”,”content”:”Learn More”,”icon”:””,”icon_align”:”left”,”link”:”\/blog\/the-ultimate-guide-to-decision-engines\/”}}]}]}],”props”:{“layout”:”2-3,1-3″}}]},{“type”:”section”,”props”:{“image_position”:”center-center”,”style”:”secondary”,”title_breakpoint”:”xl”,”title_position”:”top-left”,”title_rotation”:”left”,”vertical_align”:””,”width”:”default”},”children”:[{“type”:”row”,”children”:[{“type”:”column”,”props”:{“image_position”:”center-center”,”position_sticky_breakpoint”:”m”},”children”:[{“type”:”divider”,”props”:{“divider_element”:”hr”}},{“type”:”headline”,”props”:{“content”:”LATEST NEWS”,”title_color”:”background”,”title_element”:”h1″,”title_style”:”text-large”}},{“type”:”grid”,”props”:{“content_column_breakpoint”:”m”,”filter_align”:”left”,”filter_all”:true,”filter_grid_breakpoint”:”m”,”filter_grid_width”:”auto”,”filter_position”:”top”,”filter_style”:”tab”,”grid_column_align”:false,”grid_default”:”auto”,”grid_divider”:true,”grid_large”:”3″,”grid_medium”:”3″,”grid_parallax_justify”:true,”grid_row_align”:false,”grid_xlarge”:”3″,”icon_width”:80,”image_align”:”top”,”image_grid_breakpoint”:”m”,”image_grid_width”:”1-2″,”image_link”:true,”image_svg_color”:”emphasis”,”image_transition”:”scale-up”,”image_transition_border”:false,”item_animation”:true,”link_size”:”small”,”link_style”:”default”,”link_text”:”Read more”,”margin”:”default”,”meta_align”:”below-title”,”meta_element”:”div”,”meta_style”:”text-meta”,”show_content”:true,”show_image”:true,”show_link”:true,”show_meta”:true,”show_title”:true,”title_align”:”top”,”title_color”:”success”,”title_element”:”h3″,”title_grid_breakpoint”:”m”,”title_grid_width”:”1-2″,”title_hover_style”:”reset”,”title_link”:true},”children”:[{“type”:”grid_item”,”source”:{“query”:{“name”:”posts.customPosts”,”arguments”:{“terms”:[52],”category_operator”:”IN”,”post_tag_operator”:”IN”,”users”:[],”users_operator”:”IN”,”offset”:0,”limit”:3,”order”:”date”,”order_direction”:”DESC”,”industry_operator”:”IN”,”language_operator”:”IN”,”resources_operator”:”IN”}},”props”:{“_condition”:{“filters”:{“condition”:”!!”},”name”:”author.name”},”title”:{“filters”:{“search”:””},”name”:”title”},”content”:{“filters”:{“search”:””,”limit”:100},”name”:”excerpt”},”image”:{“filters”:{“search”:””},”name”:”featuredImage.url”},”link”:{“filters”:{“search”:””},”name”:”link”}}}}]}]}]}]}],”version”:”4.4.1″} –>

The Ultimate Guide to Decision Engines

What is a decision engine and how does it help your business processes?

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Driving a Better Consumer Experience in Auto Financing

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Driving a Better Consumer Experience
in Auto Financing

Satisfied vehicle shoppers make for repeat customers

Did you know that 65% of car shoppers feel that finance applications take too long? Whether you’re looking for a car, an RV, a motorcycle or even a boat – some of the biggest headaches in our buying lives come from the mountains of paperwork that financing or leasing a vehicle requires. The traditional loan origination process is arduous, doesn’t benefit either the customer or the lender, and increases the risk of losing a customer before they can sign on the dotted line.

Let’s face it, customers are not keen to sit in dealerships for hours and fill out reams of paperwork to hopefully get approved for a loan. In the age of instant everything, customer experience matters. Entertainment is available on demand, your favorite milkshake can be delivered without talking to anyone, you can order a ride in minutes – consumers expect more and aren’t shy about telling the world when their expectations aren’t met. Brands that make missteps should expect to have their failures broadcast far and wide in viral twitter threads, WhatsApp groups and Facebook posts.

Consumers have power

If traditional vehicle dealers want to maintain and grow their customer base, they need to ensure consumer satisfaction. There are countless examples of small, innovative companies that grew to behemoths – they all have a few things in common:

  1. they take something (a process, a product, a service) that frustrates consumers and change it entirely to better suit the consumer’s needs;
  2. they continuously adapt to changing, emerging technology and;
  3. they treat their customers incredibly well.

Look at Uber and how they changed the face of private transportation. Or Netflix and how they’ve completely disrupted cable television. Or Airbnb and VRBO and the changes they’ve inspired in the hospitality industry. Of course, there’s also Amazon and the way it changed… everything, or Facebook and the advent of instant, social, worldwide communication. And no list of disruptive tech would be complete without Apple, the mother of all companies that entirely transformed the way people use personal technology. One of the ways that Apple has disrupted an entire industry is through functionality – or more specifically, the ease of functionality. “Using an Apple product feels so natural, so intuitive, so transparent… The design is so intuitive that the instruction manual is almost non-existent.” What if auto lenders positioned themselves the same way? And what if what they promised was actually true? These days, you can get a car delivered to your doorstep with innovative companies like Carvana or Carvago without having to set foot in a dealership. It’s never been more important for auto lenders to ensure they are easy to work with. 

More than ever before, our connected world and social media makes it possible for companies that do things really well to stand out. On the flipside, it ensures that the word is spread about companies that don’t do things well. Consumers have inside access to brands in a way they’ve never had before – they can sit on the phone waiting for a faceless customer service rep to maybe answer the phone, or they can instantly tweet their complaints and get a company rep to address their concerns in real time (while the rest of the twitter-verse watches). Even with the supposed ease of online loan applications, 90% of bank customers will abandon an onboarding application if the process takes more than an hour to complete, according to The Paypers. Bottom line? Consumers won’t sit and wait around for a subpar experience if they don’t have to.

Old versus new

So how does this translate to something like auto loan origination? The old-guard method of auto financing requires customers to fill out mountains of paperwork, provide copious amounts of data and multiple forms of identity. Behind the scenes underwriters then spend hours manually processing applications to determine a customer’s credit risk. The end result? Customers often feel like their time isn’t valued and that they are little more than a number on an assembly line. Even if you have technology in place to support increased automation and faster underwriting, as soon as your sales rep needs to make a phone call for a loan approval, you’re already too slow for today’s savvy, instant-everything consumers. But the good news is, when there are problems or lags in an industry or process, innovation flourishes. 

Captive/manufacturer finance currently owns over half of the market, so there is a lot to lose. Conversely, new competitors like smaller lenders have a long runway of opportunity. They are threatening the traditional dealership finance and sales process, and these threats are growing rapidly:

Enter in a new way of originating auto loans that can help transform the dealership experience:

  • Smart, digital applications that automatically pull information in through a decisioning platform
  • Automated KYC data, including identity verification and due diligence
  • Powerful decisioning tools that automate data gathering, risk modeling and personalized pricing
  • Loan decisions in UNDER A SECOND

A truly memorable, satisfactory consumer experience in auto financing is fast, easily available, and most importantly, personalized. Your customers aren’t just numbers and your finance products need to reassure them of that fact.

The future of auto financing is here – the question is how many auto lenders will put their customers first and take advantage of it? The kicker is, not only will those who do take advantage of it have happier, more loyal customers, but they will also be poised to innovate better, and faster. By creating new industry benchmarks – with better deals, instant approvals and personalized processes – you can stand out in the auto financing industry. And maybe even be the subject of the next positive viral twitter thread?

Download the eBook to discover how auto financing is changing. Learn how you can improve the customer experience and innovate faster with real-time data and AI-powered, automated decisioning tools.

Discover how Flexiplan, a digital motorcycle financing platform, uses Provenir to manage risk more effectively.

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Fintech in 2023: Predictions From Provenir, THORWallet DEX, Riskified

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Fintech in 2023:
Predictions From Provenir, THORWallet DEX, Riskified

As 2023 kicks off, The Fintech Times is tapping industry experts for their predictions for the coming year.  In this article, Kathy Stares, Executive Vice President, America for Provenir, shares her insights on the incredible opportunity (and challenge) fintechs have to demonstrate how best to operate in uncertain times.

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Credit Risk Software: Build vs. Buy Options (Complete Guide)

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Credit Risk Software:
Build vs. Buy Options
(Complete Guide)

12 factors to consider when evaluating build vs buy options for credit risk software.

I loved Lego when I was a kid, ok, ok, I’m going to be totally honest, I still love Lego (PSA: other brands of building blocks are available). The pirate theme was a favorite, but Santa must have lost my pirate ship box set somewhere over the Atlantic. So, my pirate Lego supply was limited to a mini boat, Lego characters wearing pirate costumes, and treasure chests filled with pieces of eight. So, here I have my menacing pirates setting off on elaborate plundering adventures in… a tiny ‘wooden dinghy’. Let’s face it, no self-respecting pirate would be taking that dinghy anywhere, even to pop down to the grocery store to stock up on grog.

But what does Lego have to do with deciding whether to build or buy credit risk software?

Building a credit decisioning solution for your business is like creating a Lego model. Your solution – whether it’s a loan origination system, merchant onboarding tool, or payment platform – is not a self-contained Lego brick that can act as a user interface, store data, process applications, manage integrations, maintain KYC compliance, host risk models, use machine learning algorithms, and provide a credit decision. Similar to Lego, it is a set of building blocks joined together to create the right decisioning solution for your business.

Build Vs. Buy—More Options Than Ever

The build vs. buy debate has been going on for years, and much of the discussion falls around simple options: you buy, or you build. But with technology getting more advanced every day there’s now other options such as: buying the building blocks or selecting a strategic partner. So, for the purpose of this guide we’re going to compare four options:

– Build

This is the from scratch, internal approach. If this were a Lego project it would include creating the plans for your blocks, developing the blocks internally, and building them into your finished solution. This is often the first option explored by tech savvy companies, especially if they have a wealth of tech talent available to take on the project.

– Build, but not from Scratch

This is the Lego kit solution for credit risk software. You buy the kit—so you don’t need to handle building the blocks/ components—and combine them into the solution that best fits your needs. The flexibility in finished design will vary by vendor solution. For example, some solutions may give you the option to build anything from a paddle board to a cruise liner. Others may only let you build a sailboat.

– Buy

Another common choice is the buy approach, in this situation you’re buying your pirate boat fully built, you might be able to change a few of the decorations, but the design stays pretty standard. Ongoing maintenance and upgrade options will vary by vendor. If you spring a leak you may need to depend on the vendor to fix the hole.

– Partner

Someone else owns the Lego and has already built the ship, you use it. This may sound like the perfect solution, but you could be very limited on the design. In other words, you’ll need to adjust your needs to fit their ship design.

12 Factors to Consider When Evaluating Your Build Vs. Buy Options

Are you facing challenges in managing credit risks within your business? Maybe you’re struggling to keep up with your competitors, experiencing limitations in business growth, or dealing with a poor user experience. One way to address these challenges is by using credit risk software. However, before selecting a solution, it’s important to consider several factors:

  1. Your Pain Points What’s your pain point? – Is there an issue causing you to lag behind your competitors, impacting your user experience, or limiting business growth? What do you need to do to fix it? Is it increasing your decisioning speed? Reducing the time it takes your team to deploy new risk models? Make integration to internal or external data sources easier? Improve the accuracy of your decisioning? Automate the decisioning process? Defining the project scope and listing solution requirements is an essential step in fully evaluating your options. Without knowing your need list and your wish list you could end up with a risk decisioning river boat when what you really needed was a jet ski
  2. Fit – Perhaps the most important question: would the implemented solution meet all of your decisioning needs?  Or would you need to bring in other solutions to make up for any shortcomings? It’s also important to look at how the solution will fit in with your existing technology stack and how easy integrating the systems would be. For example, will the tech stack together like Lego blocks, or will it will it be more like trying to attach a Lego block to a house brick.
  3. Flexibility – The thing that makes Lego so incredible is the huge amount of designs you can make with just a small set of blocks. My Lego house could absolutely transform into a pirate ship when needed! So, which of the solutions will give you the flexibility you need to create the right system for your business needs?
  4. Time – Instant launch or long development process? How will each option impact your time to market? Long delays can be expensive, extend product launch times, limit business agility, and expose the business to increased risk, especially where credit origination and KYC processes are involved.
  5. Costs – The cost of each option is an obvious consideration, but it’s important to look at both initial costs and ongoing costs. Things to consider include the cost of ongoing maintenance, changes, and upgrades, whether they’re completed internally or externally. If your solution will be inadequate in a few years, what will be the cost to replace it or make it fit new business needs?
  6. Resources – What resources will you need to complete the project, and do you currently have that talent in your team? If not, what training or recruitment will need to be completed and what will be the cost to bring the required resources in house?
  7. Focus – New development projects can be all consuming—using resources, effort, and focus that could be utilized elsewhere to drive the business towards its goals. If you decide to focus your resources on an internal build, what opportunities will you miss elsewhere and is the delay to these other projects a problem?
  8. Usability – Usability can make a huge difference to your business in both the short and long-term, so it’s important to ask how usable the finished solution will be? Will you need specially trained team members? If it’s an externally built solution how much will it cost to train your team to use the system? In Lego terms, are you getting a simple kit with a few pages of instructions, or a 2000-block pack with a 500-page manual?
  9. Control – While the ability to change settings and adjust processes may seem like a nice to have option, the delays caused by waiting for vendors or your tech team to implement change requests from your risk team can have a long-term impact. Each time you have to wait for a new data source to be integrated, a score card to be changed, or a risk model to be deployed you’re falling behind your competitors. When evaluating solutions make sure to ask how much control will you have over the software. Will you be able to easily make changes and adjust settings, or will you be reliant on a third party such as the vendor?
  10. Competitive Advantage – In some situations, one solution will give you an advantage over the competition. For example, if you can build a Lego ship that has a unique design that makes it faster, smarter, and more efficient than other ships, then creating your own Intellectual Property makes sense. However, if an industry leading solution is available to buy, what competitive advantages would you gain by building internally?
  11. Business Agility – Will the selected option impact your business agility? For example, could you quickly pivot direction and make quick decisions? Or would you need long lead times to adjust your decisioning processes, make updates, or completely switch direction?
  12. Scalability – While it may be easier to shop for or build a solution that fits your needs now, looking ahead can help you avoid needing to replace your solution in a few years. So, when evaluating options ask: will your solution be able to easily grow and develop with your business, or will the decisioning solution be obsolete in a few years?

The decision to build or buy credit risk software is a critical one for financial institutions. While building an in-house solution may provide greater control and customization, it comes with a higher cost and longer development time. Buying a pre-built solution can offer faster implementation, cost savings, and access to advanced features and technology. Ultimately, the decision should be based on a thorough evaluation of the organization’s specific needs and capabilities. Working with a trusted partner can help organizations navigate the complex process of selecting and implementing the right credit risk software solution for their business.

The Ultimate guide to Decision Engines

What is a decision engine and how does it help your business processes?

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The Ultimate Guide to Decision Engines

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The Ultimate Guide
to Decision Engines

What is a decision engine and how does it help your business processes?

Decision engines, sometimes referred to as decision trees, are software platforms that automate business rules or business decisions – helping you streamline business processes that require decision-making without having to think about it. A decision engine automates these business decisions based on your business needs and the particular criteria the platform’s owner sets out, saving you from manual work and centralizing the decision-making process. 

What does a decision engine need to run? Besides the set of rules (logic), otherwise known as the decisioning workflow, decision engines need data. Lots and lots of data. By accessing and integrating data from multiple sources and applying these ‘rules’ according to your criteria, voila – you can automate decision-making. In the finance world in particular, decision engines are often used to help you make decisions on who to lend to and helps determine which sort of products you can offer your customers.

Automated decision engines can also enable personalized pricing and offers (i.e. finance terms and interest rates), all of which are customizable to your unique needs. Some popular examples in the world of fintech/financial services include: consumer lending, loan origination, credit card approvals, auto financing, point of sale lending like buy now, pay later (BNPL), lending to SMEs, insurance policy approvals, upsell/cross-sell offers, champion/challenger strategies, audits, collections and more.  

How does a decision engine help inform business decisions?

Decision engines can help inform various types of business decisions – on everything from basic day-to-day operations to more high-level, strategic business decisions. 

  • Strategic Decisions: Strategic decisions are top-level, and tend to be more complex, affecting a much larger portion of the organization and often applicable for a longer term (i.e. changing cost structures or planning for longer-term organizational growth). Decision engines and automated decisioning processes can expedite and streamline various processes, improve efficiency, and allow you to make smarter decisions overall. In the case of financial services, this could mean a shift in deciding who you can lend to in order to expand your overall customer base and plan for growth. Keep in mind that more complex decision execution typically requires a large amount of data, provided from a variety of data sources. Utilizing decision engines and automated decisioning processes can help an organization access, analyze, and action a large variety of data, enabling smarter decision-making.
  • Tactical Decisions: Tactical decisions are much more focused on business processes and tend to be shorter-term and less complex. Examples include launching new products, changing product pricing, managing inventory control, and supply chain and logistics. With decision engines, you can more easily analyze performance data and help determine new pricing strategies for your financial services products or look strategically at which demographic or region to target next. 
  • Operational Decisions: Focused on day-to-day operations of a business, operational decisions are much smaller in scale. They tend to be related to overall daily production and are usually executed in alignment with the overall strategic vision of an organization. In financial services, decision engines can improve efficiency and help automate or streamline varying day-to-day decisions, including loan approvals, interest rate offers, guidance on collections, merchant onboarding, pricing optimization, compliance processes, identity verification, fraud prevention and more.

Decision Engine Framework

So how does a decision engine actually work? And how do decision engines function in a business? While it’s up to each individual organization (and all of the individual business rules within) how they want their business decisions to be executed, there are some basic steps that remain true across the board.

  1. Set Desired Outcomes: Look at what your goals are. What are the specific business rules that you need your decision engine or workflows to execute on?
  2. Determine Decision Criteria: What are the standards or requirements to which you are making your evaluations or decisions? For example, in the case of many credit applications, particular criteria often include income, job status, age, marital status, debt ratio, etc.
  3. Organize Data Sources: To process these business decisions based on your desired outcomes and your determined criteria, what sort of data sources do you need? Do you need traditional credit bureau data, third-party sources, alternative data like rental info, social media presence and web data, etc.?
  4. Create Decisioning Workflows: What are the necessary steps in your decisioning process? Use the configuration tools within your decision engine to lay out your workflows and business rules and enable automated decisions.
  5. Test and Iterate: Create, test and deploy your modelling scorecards and decisioning process, and look at what happens when a typical customer is put into your system. For example, if a customer applies for a credit card, their information is put into the decision engine, which then pulls in necessary data (identity verification, KYC, income verification, fraud), and rejects or approves based on the initial criteria determined. Is something missing? Can your business process be smoother? Iterate!
  6. Determine Next Steps: Where is your threshold for complex applications? Which applications need manual intervention? Straight-through processing enables instant decisions for more simple credit and lending requests, while a rules-driven decisioning process helps to identify and re-route exceptions that require more manual intervention. 
  7. Monitor and Optimize: Is your decision engine offering real business value? Keep tabs on your decisioning performance by using the information your decision engine gives you. Identify opportunities for further enhancement of your decisioning process and tools and enable more efficient decisioning – and business growth.

How does a decision engine function in a business?

As we’ve shown, there are a large variety of ways that decision engines can help inform business processes. But how exactly does it do that? In the case of financial services, think of all the manual decisions that require human intervention. If an individual needs a car loan, for example, how does a lender determine if that individual is creditworthy or not? And if they are, what interest rate or repayment terms should they be offered? Having an automated decision engine can streamline the application, approval, and funding process to ensure an efficient, superior customer experience. 

In the auto financing example, applications can move from manual, paper-heavy forms, and hours of sitting in a dealership to simplified, online applications. An individual can easily fill out an application and provide ID, which then allows a decision engine to move that person quickly and easily through the decisioning workflow along a series of pre-determined steps, according to the initial criteria.

In this case, that criteria could start with analyzing data for identity verification (is this person really who they say they are? How old are they? Do they have a valid driver’s license?), then move through to various factors that determine creditworthiness. Does this person have an income that is above our threshold? What is their credit score? How much debt does this person already have, and what is their debt-to-income ratio? Do they have previous loan defaults on their record?

As the decision engine automatically accesses and analyzes all the data required according to the business rules, it moves that application through the workflow based on the answers. Driver’s license? Check, on to the next step! Old enough to own a car? You betcha. Have a job? Yep, move along! But then comes a doozy of a credit score and a record of numerous loans having gone to collections. The buck stops here and the decision engine (as per the initial ‘instructions’ when setting out the original workflow) stops the application and determines that this individual is NOT a risk this lender wants to take.

Of course, not all situations are as black and white as that example, but the beauty of automating business processes with a decision engine is that you can streamline and improve efficiency for many situations and types of applicants, while focusing that most precious resource, humans, on the more complex cases that require manual intervention.

Data, Data, and More Data

Despite all the wonderful ways that business processes can be improved using decision strategies, there can be no automating decision execution without extensive data and data aggregation. Data, preferably varied and from a wide range of data sources (including historical data), is critical to the decision-making process.

All financial services organizations use data to make informed decisions across the customer lifecycle – but having to manually access and integrate data sources is nothing short of a nightmare. Data consumption has evolved, right alongside the decision engines that data feeds into. It’s impossible to make accurate decisions based on business needs without the right data that aligns with the particular criteria set out. Think back to the examples previously discussed – where do you get information on loan payments, credit policies, credit scores, income to debt ratio, age verification, etc.? It’s all about your customer data sources.

These days, more and more lenders are increasingly looking to a wider range of data sources, including alternative data like rental payments, social media interactions, website info, travel data and more, to ensure: 

  • A more accurate view of identity verification
  • A more holistic view of risk and creditworthiness
  • Better fraud prevention

All this data must be accessed, analyzed, and actioned appropriately to help ensure more accurate, automated decisions that provide value to a business. As The Financial Brand said, “Data, by itself, is not a valuable asset. It’s what you do with it that counts.” Having a variety of data available on-demand is essential for enhancing your automated decisioning. Third-party data providers, connected through a centralized platform or marketplace with a single API, can make this data consumption effortless, giving you the ability to access and integrate numerous data sources in minutes. Use that data to test your decisioning workflows, and then iterate and adapt with ease.

AI-Powered Decisioning

The use of artificial intelligence and machine learning is growing. AI in financial services is seen as a $450 billion opportunity. But how can you use AI most effectively in your decision engines? Using AI/ML to power your decisioning process enables:

  • Improved decisioning accuracy
  • Superior fraud detection
  • Enriched customer relationships
  • Improved customer satisfaction
  • Expanded customer base
  • Optimized pricing
  • Revenue growth

McKinsey pointed out that “The continuing advances in big data, digital, and analytics are creating fresh opportunities for banks to improve the credit-decisioning models that underpin their lending processes… the banks (and fintech companies) that have put new models in place have already increased revenue, reduced credit-loss rates, and made significant efficiency gains thanks to more precise and automated decisioning.”

It may seem daunting to try to implement AI into your decisioning processes, but you don’t necessarily need data scientists on your team to make AI impactful. With a technology platform that incorporates both data sources and advanced machine learning into your decision engine, you can make use of advanced decisioning – and get all those benefits listed above.

AI allows you to do things that may be challenging for traditional decision engines, including enabling more approvals for unbanked consumers, adapting to rapidly changing market trends and consumer demands without sacrificing the customer experience, and finding relationships in your data (see? Data is king!) that may be otherwise unseeable. If you do happen to be lucky enough to have data scientists in-house and need to figure out a way to utilize all their expertise in your decision engine or business applications, look for a technology partner that can easily migrate existing models into a user-friendly platform.

What’s the benefit?

While we’re talking about data integrations, automated workflows, data scientists, machine learning… why go to all this trouble? There is immense value in using decision engines in financial services instead of manually trying to make complex decisions around your business processes. Some of the benefits include:

  • Boosted Performance: make decisions faster and more effectively, enabling optimized business performance
  • Increased Profits: lend to more customers, without increasing your risk, allowing for better profit margins
  • Improved Efficiency: save time and resources, with fewer human interventions needed and the ability to make decisions faster
  • Flexibility: change your decision criteria without having to re-do your entire workflow
  • Scalability: easily add more data integrations and new criteria or decision parameters to your workflows as your business grows or the needs of your consumers/the market changes
  • Focused Resources: save your underwriters’ attention and manual intervention for more complex cases
  • Consistency: ensure consistency and stability in your decision-making processes, enabling enhanced customer relationships and reliability in business performance
  • Transparency: get full visibility into what your decision engine is doing and measure performance so you can easily optimize
  • Capture information: manual underwriting requires manual information capture – with an automated decision engine you can easily maintain information on your customers, your decisions, and your overall performance, which you can then feed back into your decision engine for further optimization

Also read: The Essential Guide to Credit Underwriting

Customer experience is more critical than ever. In an age of having everything available on demand (tv shows, rides, food delivery, workouts), your consumers expect speed. On top of that, they value customization. We want Netflix to know exactly what kind of show we’re up for next or appreciate when our Facebook feed is filled with ads that resonate. According to PwC, 80% of consumers rank speed as a key buying factor, and Salesforce says that 76% of consumers expect customized offers. Who has time for that if you’re busy making all your business decisions manually?

The Future of Decision Engines

What does the future hold for decision engines? From our perspective, the prospects are bright. Did you know that Forrester recently added Digital Decisioning Platforms to their Wave report? According to Forrester, Digital Decisioning Platforms (DDP) are “an evolution of expert systems, knowledge-based systems, business rules management systems, and decision management systems.” It’s a mouthful, but it’s clear the trajectory is positive when you automate your business decisions. And with the increased acceptance of artificial intelligence and machine learning, the ways in which we can automate decisions will only get more exciting (and profitable).

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Interview: Real-Time Credit Decisioning Solutions that will Enable Organizations to Innovate Faster

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Interview:
Real-Time Credit Decisioning Solutions that will Enable Organizations to Innovate Faster

The Fintech space in India has seen tremendous growth in the last few years. According to a recent report by Bain, the fintech sector in India is expected to grow to $350 billion in enterprise value and will account for nearly 15 percent of Financial Services market cap by 2026. With this, the demand for innovative fintech solutions is also on the rise.

In an exclusive interview with CXOToday, Varun Bhalla, Country Manager – Provenir India, shares his insights on the need for purpose-built technology designed to power decisioning innovation across the full customer lifecycle.

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The Ultimate Guide to Decision Engines

What is a decision engine and how does it help your business processes?

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A Geek’s Guide to Machine Learning (AI), Risk Analytics and Decisioning

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A Geek’s Guide to Machine Learning (AI), Risk Analytics and Decisioning

Introduction

Artificial Intelligence (AI), Machine Learning (ML) – whatever you want to call it, these buzzwords are appearing more and more throughout the business and social world. So what are they and what do they mean?

Despite the growing interest, AI/ML isn’t new at all. In fact, the models themselves have been around since the 1970s and ‘80s. In the financial sector, banks have been using ML to mitigate fraud and detect irregular buyer behaviors and patterns for the last decade or more.

Fraud is a growing concern and is costing the financial sector millions of dollars in losses each year. A 2015 research note from Barclays stated that the United States is responsible for 47 percent of the world’s card fraud despite accounting for only 24 percent of total worldwide card volume. A 2014 Federal Trade Commission report shows that credit cards and other consumer payment methods produced the greatest losses over other types of fraud.

One of the ways in which UK financial firms have tried to reduce fraud is with the implementation of the Chip and Pin system. It was seen as an effective means to prevent and reduce card fraud. But a research paper by Murdoch et al (2010) showed how fundamentally flawed Chip and Pin is.

As technology evolves, so do the cunning methods for perpetrating a fraudulent crime. Financial firms are now relying on sophisticated artificial intelligence software to evolve, adapt and learn in line with the behavior patterns of fraudsters in order to track, detect and prevent fraud far more quickly than traditional methods. The use of AI has also been implemented in industries outside financial services including insurance, retail and telecommunications.

Obviously, it is in the interest of the card issuer or bank to implement strategies to reduce the risk of fraud. Unfortunately, this often requires a compromise between expense and inconvenience to the merchant and the customer. Merchants are at far more risk than the end credit card user as they are ultimately responsible for incurring the cost of a fraudulent purchase and the potential loss of the customer resulting from the bad experience. Other costs to the merchant include direct fraud costs, cost of manual order review, cost of reviewing tools and cost of rejecting orders.

This Provenir report describes the use of AI tools in credit card fraud to mitigate risk. We will be looking at various AI detection methods including Artificial Neural Networks (ANN), Fuzzy Neural Networks (FNN), Bayesian Neural Networks (BNN) and Expert Systems.

An Overview of Fraud Prevention and Detection Techniques

The modern information age is flooded with a rapidly growing and astonishingly huge amount of data. In the U.S alone, the total number of credit card transactions totaled 26.2 billion in 2012. The processing of these data sets by banks and credit card issuers requires complex statistical algorithms to extract the raw quantitative data.

These systems work by comparing the observed and collected data with expected values. Expected values can be calculated in a number of ways. For example, a behavior model would look at the way a customer’s bank account has been used in the past, and any deviance from usual purchasing habits would return a suspicion score. This method works by flagging a transaction with a typical score, usually between 1 and 999. The higher the score, the more suspicious the transaction is likely to be, or, the more similarities it shares between other fraudulent values.

Typically, the measures taken to combat fraud can be distinguished into two categories – Prevention and Detection.

  • Fraud Prevention constitutes the necessary steps to prevent fraud from occurring in the first place, with various preventative methods used to deter fraudsters, such as MasterCard SecureCode and Verified by Visa.
  • Fraud Detection, the focus of this report, comes into play once fraud prevention fails. Detection consists of identifying and detecting the fraudulent activity as quickly as possible and implementing the necessary methods to block and prevent the card from being used by the perpetrator again. Issues arise when criminals adapt and change their tactics once they are aware that a prevention method is in place, therefore the need for more intelligent and sophisticated technology which ‘learns’ is essential for the detection of fraud.

The techniques used to detect fraud also fall into two primary classes – Statistical techniques (clustering, algorithms) and Artificial Intelligence (ANN, FNN, Data Mining). Both of these methods still involve mining through the available data and highlighting any anomalies (which can be defined by a set of rules) from the purchasing and transaction data of the customer. The difference is that where we used human analysts to manually search useable knowledge in the past, today we make use by machine learning.

Artificial Intelligence Models

Artificial Neural Networks
Also known as connectionism, parallel distributed processing, neuro-computing and machine learning algorithms, Artificial Neural Networks (ANNs) were first developed during the late 1980s and have since become a fundamental tool in combating fraud. ANNs work by imitating the way the human brain learns, using complex input, hidden, and output layers.

Diagram representing a feed-forward multilayer perceptron | Provenir

Diagram representing a feed-forward multilayer perceptron (the most common type of ANN). (Source: www. oscarkilo.net)

The input nodes retrieve information from an outside source (for credit card fraud detection, this would be the transactional data of a customer’s account) and the output nodes send the results from the neural networks back to the external source. The hidden nodes in-between the input and output nodes have no interaction with the external source and become more complex in their configuration and nature depending on the complexity of the problem at hand.

The various nodes in each layer of the neural network are connected by edges where each edge represents a particular weight between two connected nodes. (In the human brain, these are called synapses.) The information that the neural network learns through supervised or unsupervised learning is stored in these weights.

An example of the way neural networks learn is similar to the way children learn to recognize animals. After seeing a dog, the child can then generalize on various other breeds of dogs, categorizing and defining them as ‘dogs’ without having seen them before.
An important feature of neural networks is that when they learn, they have the option to be supervised or unsupervised.

  • For unsupervised neural network learning, the system makes use of clustering, which groups patterns based on similarity. The two main unsupervised learning methods are Hebbian and Kohonen. Hebbian learning takes place by association, meaning that if two neurons which are on either side of a synapse are activated simultaneously, the strength of that synapse will be increased. Kohonen (also called Self-Organizing Maps) learning takes place by learning the categorization of the input space.
  • For supervised neural network learning (back-propagation), the correct output values for certain input data are determined before starting the algorithm, and the system then learns the function between the paired input and output nodes.

A user can train a neural network by running through examples of past data. The learning process occurs when the output data is compared to that of the ANN’s predicted output. The weights for each connection are then adjusted based on the exampled data, allowing the system to learn new patterns and behavior and improve accuracy without having to be taught or shown it.

Fuzzy Neural Networks

Fuzzy Neural Networks (FNNs) are a branch of hybrid intelligence systems which make use of fuzzy logic together with ANNs to detect fraudulent activity. The idea was first developed and proposed by Zadeh and has since been used and implemented successfully in a variety of industries. The core framework for fuzzy logic is to provide an accurate method for describing human perceptions. Some experts believe that the use of fuzzy rules can provide a more natural estimate as to the amount of deviation from the normal.

FNNs, like Expert Systems, make use of IF-THEN-ELSE statements and heuristic rules to handle uncertainty in applications, resulting in better approximate reasoning without the need for analytical precision. The use of traditional IF-THEN-ELSE statements and heuristic rules (see Expert Systems below) has been controversial, and therefore has not been as widely implemented as some of the other AI fraud detection systems.

Expert Systems

Expert Systems saw increased usability and growth during the 1980s with the expansion of computer processing power, programming and AI. It was used in credit card fraud detection by using a rule-based system which proved to be fairly popular when no other intelligent systems were around. These systems were used to imitate and replicate the knowledge of an ‘expert’ person and can be defined into two classes – facts and heuristic.

  • Facts are classified as a quantity of information, such as the credit card transaction history or an individual’s credit rating.
  • Heuristic is where a person of ‘expert’ knowledge defines a set of rules that they would usually follow by protocol as a result of their ‘expert’ experience, education, observation and training.

Expert systems work by taking this human knowledge and transferring it into a logical language that a computer can understand and follow in order to solve a problem. A fundamental part of expert systems is their extensive database of stored rules which are defined by a typical IF-THEN-ELSE format. For example, a rule based system using IF-THEN-ELSE may look like the following:

IF the amount of purchase is greater (>) than $1000 and the card acceptance authorization is through ‘eBay’, THEN raise a suspicion score and require further verification, ELSE approve transaction.

Limitations of Expert Systems however are that they require considerable storage space and rely heavily on extensive programming of expert human knowledge in order to make decisions. Some experts b

Bayesian Neural Networks

These types of networks take a slightly different approach to the general guidelines and rules of learning that are commonly seen in ANNs and FNNs. Typically, Bayesian Neural Networks use Naive Bayesian Classifiers, a simple method of classification, to classify transaction activity.

Bayesian learning can be trained very efficiently in a supervised learning setting and uses probability to represent uncertainty about relationships that have been learnt as opposed to variations on maximum likelihood estimation. Where neural networks try to find a set of weights for each node (process of learning) to best fit the data inputted, Bayesian learning makes prior predictions by means of probability distribution over the network weights as to what the true relationship might be. One study looked at the comparison of using both ANNs and Bayesian Belief Network algorithms in fraud detection, and found that the use of Bayesian Neural Networks, although slower, were in fact more accurate than the use of ANNs alone.

In fact, many believe the use of Bayesian methods to be highly effective in real world data sets as they offer better predictive accuracy. This is supported by research which concluded that the use of Bayesian Neural Networks were far superior and accurate in detecting credit card transactional fraud than Naive Bayesian Classifier.

The Data

The following table compares the research findings to highlight which combination of models provides the highest prediction accuracy.

Summary of the most notable investigations into the use of Artificial Intelligence at mitigating fraud.

The greatest challenge when talking about artificial intelligence/machine learning is actually in understanding what data sets we are looking at, and what model/combination of models to apply. Amazon’s Machine Learning offering is one example of an automated process which analyses the data and automatically selects the best model to use in the scenario. Other big players who have similar offerings are IBM Watson, Google and Microsoft.

Conclusion

Provenir’s clients are continually looking at new and innovative ways to improve their risk decisioning. Traditional banks offering consumer, SME and commercial loans and credit, auto lenders, payment providers and fintech companies are using Provenir technology to help them make faster and better decisions about potential fraud. Integrating artificial intelligence/machine learning capabilities into the risk decisioning process can increase the organization’s ability to accurately assess the level of risk in order to detect and prevent fraud.

Provenir provides model integration adaptors for machine learning models, including Amazon Machine Learning (AML) that can automatically listen for and label business-defined events, calculate attributes and update machine learning models. By combining Provenir technology with machine learning, organizations can increase both the efficiency and predictive accuracy of their risk decisioning.

From advanced machine learning to generative intelligence and model governance, Provenir helps you maximize value, minimize risk, and accelerate ROI — all on a single platform.

Provenir AI

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The History of Lending

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The History of Lending

Technology and the Democratization of Lending

Did you know that the earliest form of Buy Now, Pay Later dates back to the 19th century, when consumers were able to purchase expensive goods (like furniture and farm equipment) on installment plans? While modern lending is often thought of as, well, modern, some of the technologies that impact our current financial services landscape have much older roots. Check out the infographic for some interesting factoids on the history of lending, the rise of modern technology, and just how far we’ve come in the world of lending.

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Ten Fintechs Using Alternative Data for Financial Inclusion

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Ten Fintechs Using Alternative Data
for Financial Inclusion

Ensuring the Underbanked and Underserved Have Access to Credit

At one point, it was impossible for people to buy things without having cash in hand, right then and there. And then dawned the age of credit. While credit has taken many forms (layaway plans and credit cards, instalment plans and payday loans, mortgages and Buy Now, Pay Later products), one thing has remained constant: to get credit, you need to qualify for it.

As fintechs and credit providers evolve, so has the way lenders handle their credit risk decisioning. A traditional credit score (based on things like credit history, payment history and debt ratio) is no longer the only way to evaluate creditworthiness – and, it naturally precludes a large number of people who may not have much of a credit history to evaluate (i.e. minorities, recent immigrants, younger consumers, the financially underserved and others who are new to credit).

This is where alternative data comes in. A broad term that essentially refers to all credit data not currently reported via traditional credit scores, this type of data strengthens a person’s ‘profile’ and provides a more robust, comprehensive view of the risk associated with lending to them. The types of alternative data keep growing, but the term includes things like rental payments, utility records, social media presence, telco data and open banking info.

Also, read: What is Banking as a Service (BaaS)?

Financial Inclusion and Supporting SMEs

Using alternative data and deeming more people creditworthy is clearly good for business—it means organizations can more accurately predict risk and say yes to more people and enables lenders to grow and scale their business in a way that traditional data might not allow. But there’s more to it than that. Not only is alternative data good for business, it’s good for their consumers also. Companies all over the world are finding unique and inspiring ways to use alternative data to promote greater financial inclusion for thin-file/no-file clients (also known as the underbanked/unbanked), and to support greater access to credit for SMEs/MSMEs.

While this list is in no way comprehensive (there’s just too many amazing organizations doing awesome things) – here are ten unique companies using alternative data for the greater good.

  1. Bankly – In Nigeria, Bankly helps their users digitize and grow their cash in a safe, sustainable manner. Using technology and human touchpoints to digitize cash, they are able to generate data to create a digital/financial identity, which ensures their thin-file customers gain access to broader financial services including credit and insurance. Seventy-five percent of their users identify as underbanked, including such underserved populations as farmers, market traders, artisans and transport workers who are often paid in cash and can’t easily access traditional banking services.
  2. Davinta – Indian-based Davinta is an AI-based digital platform focused on offering credit and other financial products to people living in rural areas. The company leverages data from both traditional and alternative channels to recommend tailored financial products to their customers. To date, Davinta has acquired nearly 15,000 registered users, the vast majority (12,000) of which are women. As they say, they are not just another financial inclusion enterprise, but endeavor to “create wholesome social inclusion of the larger Indian society towards equal life opportunities.”
  3. Esusu – This American company uses rental payment data to help underserved populations build credit history. Serving low to moderate income households in the U.S., their proprietary platform reports rent payments to the three major credit bureaus in the region, allowing customers to build credit and unlocking future opportunities that may have otherwise been out of reach.
  4. Fairbanc – Headquartered in the United States but operating in Indonesia, Fairbanc offers a highly-scalable closed-loop credit platform for micro-merchants, enabling them to access the supply chain and more easily purchase fast-moving consumer goods. With a focus on financial inclusion for women, Fairbanc has access to a customer base of 650,000 unbanked micro-merchants in Indonesia, with nearly 260,000 of them being women. Their AI/ML platform analyzes transaction data and history to grant instant digital credit lines; and with their ‘Pay Later’ API integrated directly into Unilever’s order-taking tables, merchants need only a basic phone to participate.
  5. Fundfina – Operating in India, Fundfina is a financial marketplace powered by open banking architecture and machine learning analytics. Focused on MSMEs, the organization partners with local financial institutions to serve more than 150,000 customers across India, who would otherwise find it difficult to access traditional credit thanks to a lack of credit history. Combating the slow, complex lending process that is typical in India, Fundfina enables thin-file credit assessments through its proprietary digital engine (they’ve developed their own credit scoring method, TrueScore, looking at transactional data and payment history), curating the most appropriate financial products and even offering cashflow management tools to promote financial literacy.
  6. First Circle – One of the first fintech companies to be licensed by the Securities and Exchange Commission (SEC) in the Philippines, First Circle was founded to empower SMEs by helping to bridge the credit gap found for small businesses in the region. With various growth programs available, revolving credit lines, and mobile-first applications processes, First Circle aims to help customers who often have no credit data or fixed collateral available, many who have been forced to work with predatory lenders in the past.
  7. Oriente – Based in Hong Kong, Oriente has built a digital-first infrastructure designed to ignite economic opportunity for unbanked consumers and underserved merchants. Using real-time alternative data and insights, Oriente enables thousands of merchants to increase conversion rates while lowering risks. Their proprietary identity infrastructure uses AI and machine learning to make it hassle-free for unbanked consumers to get digital credit, and even enables them to build their credit profile if they pay on time.
  8. Paycode – Designed for those in remote, rural areas, South Africa’s Paycode provides financial services technology solutions to unbanked citizens, using biometric data collection for identity verification and to securely authenticate banking transactions. By partnering with local financial institutions, their complete alternative banking and payment platform has been able to create low-cost bank accounts for first-time users, with over 4 million end-users across 8 countries so far.
  9. TiendaPago – An innovative fintech operating in Mexico and Peru, TiendaPago targets ‘Mom and Pop’ businesses for financial inclusion, providing closed-loop working capital financing. Their mobile-based platform uses data related to inventory purchases to assess creditworthiness of merchants, ensuring that merchants can pay distributors for the correct amount of inventory they need to adequately provide for their customers and grow their business. Merchants typically have limited cash funds available to pay distributors, resulting in higher price points for inventory and limiting sales.
  10. ZigWay – Based in Myanmar, Zigway aims to help low-income families gain more access to household essentials in an affordable way. Offering a monthly subscription service that enables households to purchase quality staples like rice and cooking oil in bulk, they provide savings of up to 20 percent for participants. Using a proprietary, machine learning-based credit scoring model, ZigWay is able to offer participants flexible payment plants. They even promote accessibility and inclusion by empowering ‘Super Users’ to help register their neighbors, request services and make payments on their behalf. To date, they’ve piloted their services with over 500 customers, delivering enough food for over a million meals.

The story of alternative data – what it means, how it’s utilized, who uses it – will keep changing and evolving as more and more fintechs and data providers find unique ways to incorporate it in their risk decisioning processes. That is, if they can efficiently access it. When we surveyed 400 fintech decision-makers globally, the stats on using alternative data were pretty staggering:

  • 60% said access to alternative data sources is limited and 74% said data of any kind is not easily accessible, while 60% found it a challenge that they don’t have a centralized view of data across the customer lifecycle
  • 70% said data not being easily integrated into their decisioning solution was an impediment to using alternative data, and 51% said it simply wasn’t accessible in their organization

But the value of using alternative data for credit decisioning is clear – not only does it enable a more complete view of your customers, it also allows for greater financial inclusion, better access to credit for SMEs/MSMEs, and it can help you grow your business in ways you may never have imagined. If you find it challenging and costly to select, access, and use the right data at the right time to make accurate, inclusive decisions, check out how Provenir Data can help. Take control of your data, all from one centralized, easy-to-access global data platform, and never worry about how to integrate alternative data sources again.

Discover how Provenir Data can help you incorporate alternative data into your credit risk decisioning and encourage greater financial inclusion.

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