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Auto Financing – Drive a Better Consumer Experience

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Auto Financing – Drive a Better Consumer Experience

Auto Financing – Drive a Better Consumer Experience

Did you know that all it takes is 90 minutes in a dealership for customer satisfaction to decline? Whether your customers are purchasing cars, trucks, motorcycles, RVs or even boats, the faster and smoother you can make the experience, the better. Get in the fast lane and discover how to accelerate the auto lending experience with automated risk decisioning tools.

Make your auto financing process more like Netflix, and less like Blockbuster. Download our ‘Netflixing Auto Financing’ eBook to learn more.

Ready to accelerate your auto financing strategy?

Get the guide

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Operationalize your Financial Risk Models

DATA SHEET

Operationalize your Financial Risk Models

Quickly and easily import multiple types of risk models

The Provenir decisioning Platform and risk analytics is unique in its ability to quickly and easily import multiple types of risk models so that they can be operationalized in automated decisioning processes.

Because the integration is “model agnostic”, simple and complex models and scorecards developed in third-party tools such as SAS, R and Excel or exported using PMML or MathML can be imported, validated and mapped via easy-to-use wizards.

With Provenir, there is no need for programming, enabling models to be imported and operationalized in minutes. This exclusive capability extends the value of your investment in industry-standard modeling tools while ensuring that automated risk decisioning processes developed in Provenir are always using the most accurate and up-to-date risk models.

Here’s a quick summary that shows just how easy it is to operationalize an R model.

Simply click Add to select a model from your system files and import it into Provenir. Provenir automatically validates the model’s code and extracts the fields for mapping.

Open the model to visually configure the input and output mapping by dragging lines between the model’s and Provenir’s data fields. This creates Execution Profiles.

Input mapping specifies the data from Provenir that will be used by the model to execute the analysis.
Output mapping specifies the data to be returned to Provenir once the model has executed.
Provenir also provides options for managing the Execution Profile including how a returned value should be handled as well as using more than one Execution Profile with a model.

Provenir dynamically maps between the R model and its decisioning process. You can also map constant or fixed values between the model and Provenir.

Finally, check in your new model object and you are ready to test it. You can test it directly from the model object itself or place it in a business logic process and test it. Provenir provides visual feedback to show you exactly what happened during the test.

With these few simple steps, your R model has been operationalized in an automated Provenir risk decisioning process.

The Ultimate Guide to Decision Engines

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

Read the Blog

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eBook: The Future of Buy Now, Pay Later – the Industry Weighs In

EBOOK

The Future of Buy Now, Pay Later – the Industry Weighs In

Discover what industry experts predict is on the horizon for the rapidly evolving Buy Now, Pay Later market

uy Now, Pay Later (BNPL) is absolutely everywhere these days. Record transaction numbers, new providers, new markets served. What does this rapid growth mean for the future of BNPL? What impact will increasing regulations have on the seemingly endless runway of opportunity? Hear from industry influencers what they believe the future of BNPL has in store – for providers, merchants and consumers.

Learn about:

  • The impact of the Covid-19 pandemic on BNPL trends
  • How providers can create products that support long-term credit health
  • How the right technology solutions can future-proof your BNPL products

The Ultimate Guide to Decision Engines

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

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Alternative Data – The Champion of Innovative Credit Scoring

INFOGRAPHIC

Alternative Data –
The Champion of Innovative Credit Scoring

How to improve decisioning accuracy and expand your customer base

Traditional credit scores from Credit Reporting Agencies have historically been the only method to determine the risk of lending to an individual. But there are ways to get a much clearer view of a person’s credit risk and make more accurate lending decisions. There are 2.5 quintillion byes of data created globally every day – including various types of alternative data not captured by traditional credit scores.

64% of lenders/credit providers using alternative data see tangible benefits within only a year. Discover why using alternative data is quickly becoming a competitive advantage for lenders.

Want to know how to use alternative data in your credit decisioning?

Get the eBook

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Rapid and Simple Data Integration with Provenir Foundation Adapters

DATA SHEET

Rapid and Simple Data Integration
with Provenir Foundation Adapters

The Provenir Risk Decisioning Platform can substantially reduce the time, resources and costs for implementing sophisticated risk decisioning applications. A core strength of the platform is its pre-built and standards-based integration adapters. These “Foundation Adapters” enable IT organizations to communicate and integrate quickly with other internal and external systems as well as multiple structured and unstructured data sources.

Provenir has designed the adapters for ease of use. IT organizations can create integrations in the visual environment provided by the Provenir Platform without any coding or dependency on Provenir. There is no need to start from scratch each time you want to integrate with another data source — connections can be made rapidly using the pre-built integration components. Each adapter provides:

  • Connectivity, security, transaction support and data conversion/parsing
  • Two way communication
  • A visual or graphical data mapper guides the user through the task of establishing the integration and mapping the required input/output data.
  • Visual testing to check the accuracy of the integration. You can test any integration independently, or place it in a business logic process for a more comprehensive test. Provenir provides instant feedback along with a detailed breakdown of the results to show you exactly what happened during the test.

Adapters for Structured Data Sources

Provenir adapters contain the protocol-specific connection specifications for a wide variety of structured data sources1 including:

  • Web Service – Used for XML, HTTP(S), SOAP or Container-less connections
  • JDBC – Used for IBM DB2, JDBC-compliant DB, MSSQL, MySQL, Oracle connections
  • JMS/Message Queue – Used for WebSphere MQ, MSMQ, Apache Active MQ, Rabbit MQ etc.
  • File – Includes (but is not limited to) Delimited, Fixed Length, Binary, PDF, XML, Word and Excel
  • E-mail – Used to send e-mails, faxes and SMS-based messages
  • TCP/IP – Used to connect to legacy systems, such as older credit bureau protocols
  • SMS – Used to send/receive messages across all channels including mobile phones
  • Web-tracking – Used for run-time customer interaction tracking on the web

Unstructured Data Adapters

Social media now offers a potentially powerful new source of valuable data. However, integrating with social media has proven time-consuming and costly. It is not easy to gain access to the data, connect and pull data from social media sources, or make use of the data because it is not stored in a structured format.
Provenir solves this problem with ready-to-use adapters that function as gateways to key social media sites including Twitter and Facebook. Leveraging the connectivity exposed by these sites, Provenir’s social media adapters offer a standardized approach to accessing unstructured data, including a visual configuration interface to create the connection and define what to listen for on a site.

  • The Facebook adapter enables clients to listen for posts on Facebook pages and, when available, use information about the person who posted the message to determine a course of action in response to a post.
  • The Twitter adapter allows clients to:
    • Send tweets
    • Listen for tweets, or specific words in a tweet
    • Reply to a tweet
    • Re-tweet
    • Find followers
    • Determine if specific person is a follower
    • Determine if two accounts are following each other
    • Send a private direct message to a follower
    • Receive timeline and information for a specific user

Provenir Foundation Adapters eliminate the need for extensive coding or one-off integrations to multiple structured and unstructured data sources.  

Creating Data Integrations

Creating an integration between Provenir and structured or unstructured data sources is as simple as selecting it from the Add list on the Adapters tab.

Once added, each adapter can be configured to describe the input and output integration between Provenir and the data source.

Configuring a Structured Data Integration

Provenir guides you through each step in the process of configuring an integration, such as this example of using Provenir’s Web Service Adapter to connect to Experian NetConnect, which pulls Experian business and consumer reports over HTTPS.

Easy-to-follow wizards are used to configure both the input and output data values.

You map the Experian element to Provenir, defining how to store the Experian response data in your schema.

Provenir also allows you to use individual fields from the Experian response data in your business logic. When you choose this option, Provenir automatically adds the full xml to your data schema.

Provenir combines the schema and mapping logic that you have defined with the adapter to automatically create the integration.

Configuring an Unstructured Data Integration

Provenir approaches integration with an unstructured data source in the same way as for a structured source. Configuration starts with establishing the physical connection between Provenir and the source, such as Twitter.

Provenir then guides you through the process of setting up each aspect of the Twitter profile, such as the Listen function where you can track for specific words in tweets or specific users.

You map the fields to be used in the desired business process that are available in received tweets, such as text fields which contain a tweet’s text, user/id that contains a number ID of the person who sent the tweet and user/screen_name which is the Twitter user name of the individual who sent the tweet.

Download the PDF Version

The Ultimate Guide to Faster Merchant Onboarding

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RESOURCE LIBRARY

Vendor Report: Chartis Research Names Provenir a Global Leader
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Guest Blog: Future-proofing Your Business with Alternative Data Analytics

GUEST BLOG

Future-proofing Your Business
with Alternative Data Analytics

  • Ralitsa Boyadzhieva, Marketing Manager at FinScore

Despite the gradual recovery of society from the COVID-19 pandemic thanks to vaccinations, the digital means to make lending transactions are here to stay.  It is safe, efficient, and convenient for both your customers and your lending business. The pandemic has acted as a catalyst for lenders to rapidly adopt digital technologies and stay competitive in this changing environment. Upgrading digital infrastructure introduces fundamental changes that can create more economic opportunities.

However, more digital technologies not only reel in more opportunities but also disadvantages. When it comes to future-proofing your financial services company, aim to grow by expanding your market reach while ensuring profitability by detecting fraudulent individuals who are more likely to default on their loans.

To achieve both, you can rely on alternative data credit scoring.

What is Alternative Credit Scoring?

Alternative data credit scoring is the umbrella term for credit scoring using non-traditional data sources and methods.

In traditional credit scoring, lenders manage their risk and reduction of bad loans by relying on credit bureaus that provide credit information on the consumers. They can learn if the loan applicant has been paying off loans on time, has ongoing loans, or has been blacklisted for not paying at all. But this only works for those who have a loan history. Besides this, they assess the socio-demographic profile of the borrower which can be found on the loan application form either in pen-and-paper or digital form. The lender may also use a credit scorecard, a type of credit model, that outputs a score predicting the probability that the borrower can repay the loan on time. With Alternative Credit Scoring, alternative data sources such as mobile usage, digital wallet usage, bill payment history, social media behavior, geolocation, and more can be aggregated to produce a credit score.

Boosting Your Market Reach by Serving the Unbanked Using a Telco Data Credit Score

The mobile phone has become a physical extension of a 21st-century human. Whatever model, size, or function it may have, each mobile phone owner has a SIM card so he or she can connect with the rest of the world. They use it to make phone calls, send messages, access a wide array of mobile applications — from social media to digital banking. As time passes, a user creates his or her mobile footprint such as, but not limited to, texting usage, data usage, voice usage, top-up patterns, SIM age, and more. These are telco data that is unique to each user. 

Alternative data credit scoring, specifically telco data, can help verify, analyze, and assess the creditworthiness of the credit-invisible applicant. The credit-invisible market, also called the unbanked market, is a portion of the population who does not have any financial history they can leverage if they need to apply for a loan.

In the Philippines, in which our company is headquartered, 70% of the population remains unbanked. Telco data credit scoring can be the solution for banks and financial institutions in the Philippines to finally make the invisible market, visible. Not only visible but also reachable and possibly viable for future financially inclusive loan products.

Preventing Fraudulent Accounts by Using Social Media Data Analytics

Now that you have the confidence to serve larger volumes of customers, it is also important to add a fast and powerful way to extend credit to real customers. Fraudulent activities do not sleep. In fact, synthetic identities, bot attacks, and fraud attacks are more present in digital channels.

This is where Social Media Presence Data, which is another type of alternative data analytics, comes in.

Social media presence data is derived from public databases, which are near-real-time data. You can confirm an applicant’s identity with an e-mail address and/or mobile number. FindSocial, a fraud prevention tool, for example, can check more than 20 social media platforms, showing a user avatar and profile information in a simple interface. FindSocial also produces a Social Presence Score that can help you determine whether the customer’s social presence can be trusted or not.

The Future of Lending

Banks and financial institutions of any size are increasingly having positive perceptions towards Alternative Data Credit Scoring because not only can it increase their profitability but also reduce costs due to its speed and efficiency.

The COVID-19 pandemic has further pushed such businesses to transform the way they assess borrowers’ creditworthiness. Besides making their digital banking and/or lending mobile application available to the masses, the lending process, especially loan underwriting and disbursement needs to be fast, easy, and secure to keep up with the demand of the market and to stay ahead of their competitors.

Alternative data scoring provides borrowers with better, easier access to credit. If they apply for a loan from a lender that uses this particular type of credit scoring method, there is a higher probability they will qualify for credit applying for a loan with an establishment relying on traditional methods alone.

Summary

  • Going digital can help financial institutions reach larger markets to serve. However, it can also attract fraudulent individuals.
  • By leveraging alternative data in your analytics efforts, you can reach the large group of unbanked and underbanked individuals and prevent fake accounts from exploiting digital loopholes.
  • Telco data is a type of alternative data that can determine the financial power and creditworthiness of a borrower using data variables such as SMS and call usage, top-up amounts and patterns, SIM age, and more.
  • Social media presence data is a type of alternative data that enables fraud prevention and faster identity reviews.
  • By using an advanced analytics platform, you can instantly confirm if an applicant’s declared e-mail address and mobile number are registered on more than 20 social media platforms.

Learn more on the Marketplace.

Ten Companies Using Alternative Data for the Greater Good

Read the Blog


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“Hey, Lenders – Are You Using the Right Data Sources?”

BLOG

“Hey, Lenders – Are You Using the Right Data Sources?”

  • Pankaj Jain, Sr. Solution Architect at Provenir

As a digital transformation evangelist with years of experience in the financial and banking industry, I have helped many Fortune 500 clients future-proof their lending programs by providing intelligent solutions, especially in the decision risk management area. Through these engagements, I’ve observed that many lenders compromise their agility in rolling out a decisioning solution due to delays and challenges in the initial steps of evaluating and onboarding the right data sources. Customer needs and expectations are changing in real-time so lenders must eliminate barriers to their own agility to stay in the game. 

Below are few activities I’ve observed that compromise lenders’ agility: 

  • Choosing the Right Data Provider: Considering there are thousands of data providers across many lines of businesses, lenders always have to spend a lot of time choosing the right data provider for their decision strategy. Lenders must evaluate each data provider in each region by the line of business, review their doc specs, figure out ways to test their API in their decision solution, and then, based on the outcome, initiate the onboarding discussion. These activities often significantly delay the implementation of a risk decision solution and ultimately, delay better outcomes for the end customer. 
  • Onboarding Data Providers: Onboarding a data provider involves a series of discussions around pricing, legal contracts, support, etc., and again becomes a bottleneck in the lender’s agility to roll out products to end customers.
  • Switching Data Providers: Considering the effort required to onboard a data provider, lenders often default to their existing data provider and keep using the same data for their new risk decision solution or product. It’s like building a new car with an old engine designed for a different model.  They should put a mechanism in place to easily choose and switch to the data providers that best augment the overall risk decision solution.
  • Keeping Pace Data Sources: As data types are exponentially growing, data providers are offering new data sources, and it is hard for lenders to keep pace with who has what data. Most of the time, lenders default to using the same data type even if there are alternative data products in the market that offer new, more relevant, and deeper insights.

These activities are repeated for each data source and, on average, add a week to a month to making the data available for building a risk decision strategy around it.

To create true agility in launching a risk decisioning platform, lenders need a one-stop hub that offers easy access to a variety of data types so they can evaluate, integrate and easily build decision models around it instead of waiting for months. And having the right data source is as important as having a robust, agile risk decisioning platform.

The Provenir Data Cloud + Provenir Marketplace provides a wide variety of data sources in the lending ecosystem, along with advanced search capability to discover and detect trusted data sources based on geographic location, data type, product type, etc. It’s out of the box, prebuilt API provides seamless integration with available data sources such as credit bureaus, identification and fraud, collateral, alterative credit data, etc. 

The combination of discovering the right data sources and using an out of box prebuilt API allows the lender to quickly switch between different data providers. With a simple click of the button, they can integrate new data sources into their decision strategy seamlessly without having direct contact with the data provider. The lender can test the respective data and enable it for the end customer on the fly once satisfied with the desired test outcome.

Provenir Data Cloud + Marketplace helps lenders be more agile, responding quickly to changing data needs and focusing their time and energy on innovating their financial product. 

Learn how real-time data enhances risk decisioning and wins new customers.

Get the eBook


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Dun & Bradstreet’s The Power of Data Podcast featuring Provenir’s Frode Berg

BLOG

Dun & Bradstreet’s The Power of Data Podcast
featuring Provenir’s Frode Berg

On this episode of Dun & Bradstreet’s The Power of Data Podcast, Frode Berg, General Manager, EMEA for Provenir shares his insights on data and analytics trends, industry challenges and opportunities for innovation. Frode and host Nick Whitehead explore the:

  • Future of open banking
  • Barriers and benefits of real-time data throughout the customer lifecycle
  • Biggest challenges fintechs and banks are facing in risk decision making
  • Areas where innovation is accelerating in the region

Grab a cup of coffee and listen in on this conversation to pick up some nuggets of new insights.

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Guest Blog: Enable fast, frictionless onboarding for differentiated customer experience with Ekata’s Global Identity Engine + Provenir’s Decisioning Cloud

GUEST BLOG

Enable Fast, Frictionless Onboarding for Differentiated Customer Experience
with Ekata’s Global Identity Engine + Provenir’s Decisioning Cloud

  • Ivan Cloar-Zavaleta, Senior Manager, Strategic Partnerships at Ekata

Last year, COVID-19 triggered a five-year digital quantum leap forward, bringing with it new risks. However, it also brought the rise of a new major differentiator: customer experience. Disruptive technologies continue to be important, especially for the creation of differentiated customer experience, but there is a massive delivery gap. While 80% of business leaders claim they deliver superior customer experience, only 8% of those customers agree. (Source: Bain, Qualtrics)

Ekata has partnered with Provenir to help financial service institutions around the world differentiate their customer experience by offering Ekata’s global dynamic identity verification data for real-time probabilistic risk decisioning in Provenir’s Data Cloud + Provenir Marketplace. Ekata is the one and only global data provider that can validate, link, and see online behavior patterns for these five core identity elements – name, email, phone, address, IP address in unison – around the globe.

Ekata and Provenir joint customers are already reaping benefits from this powerful partnership by:

  • Reducing the time and resources needed for individual custom integrations with a one-stop shop and its ability to add multiple data sources via a secure, simple, drag-and-drop interface.
  • Access in seconds to extensive identity data and risk indicators for passive authentication that enables automated approval processes and reduces customer friction behind the scenes.
  • A fast and seamless platform for testing and integration of global identity data into workflows via a single low-latency API.
  • Streamlining the onboarding experience for the underbanked, a growing sub-segment, who now account for $2B+ in spending but lack traditional credit histories.
  • Detecting synthetic identity fraud through the power of dynamic data linkages and real-time prediction capabilities tracking anomalies in how elements are behaving individually and in combination with others.

Now, any Provenir customer can access the power of the Ekata Identity Engine via the Marketplace. The engines sophisticated data science and machine learning combine the differentiated technologies of two proprietary data sets, the Ekata Identity Graph (housing 1B+ global identities and 7B+ authoritative identity entities to validate, link and provide metadata for all five identity elements) and the Ekata Identity Network (seeing 16B+ identity elements through 6B+ global queries for comprehensive pattern analysis) to produce the unique scores, data attributes, and risk indicators that continuously show up in the top five performers of customers’ risk models and decisioning workflows.

Just confirming the data is valid and belongs to the submitter is not enough, patterns of behavior around these elements surface additional, critical insights. So, while the Identity Graph can tell us a phone number is valid and linked to a given owner, the Identity Network could reveal that that phone has been used with 50 different email addresses in the last 30 days in transactions at over 15 businesses in the global Identity Network—exposing the seemingly valid phone number as potentially risky. Having both datasets is critical to enable a truly comprehensive risk assessment.

The right identity verification data solution enables inclusive and frictionless experiences while, at the same time, ensuring customer privacy, control, and security. Embracing a modern, data-driven approach allows businesses to both stop fraud and provide a good customer experience.

Ekata and Provenir together can provide global businesses the right data and innovative technology to help them deliver on a truly differentiated customer experience for their end customers.

Learn more on the Marketplace.

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Expand Your Risk Decisioning Universe: 5 Quick Wins Using Advanced Analytics

EBOOK

Expand Your Risk Decisioning Universe:
5 Quick Wins Using Advanced Analytics

Book a Meeting

Don’t let risk decisioning slow you down

Digital-centric transactions are the new norm, and increased consumer choice is putting customer loyalty to the test. But organizations should not lose sight of the human experience in the rush to go digital. Making the customer delighted and optimizing risk decisioning can go hand in hand.

It’s time to embrace a world where risk decisioning agility and world-class customer experiences are must haves and expanding your organization’s universe means succeeding at both.

Read the ebook and learn how to:

  • Make immediate credit card decisions that satisfy both the consumer and the issuer
  • Enhance consumer lending practices to keep and win new business
  • Compete in the fast-growing Buy Now Pay Later (BNPL) market
  • Reduce time to funding to better support the SME lending market
  • Realize the next generation of auto lending with a smooth, frictionless buying experience

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