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Why 77% of Financial Institutions See Decision Intelligence as Their 2026 Priority

Written by Amy Sariego on . Posted in Blog.

Why 77% of Financial Institutions See Decision Intelligence as Their 2026 Priority

The financial services industry is experiencing a fundamental shift. Organizations have spent years automating decisions. Now they need those decisions to get smarter.

Our 2026 Global Decisioning Survey reveals the scope of this transition: 77% of senior decision-makers see Decision Intelligence as very valuable for their strategy over the next 2-3 years.

What Decision Intelligence Actually Means

Decision Intelligence represents the evolution from automated decisioning to continuously optimized, AI-driven decision-making that learns and improves.

THE DIFFERENCE:

  • The Traditional Approach:

    Deploy AI models, measure results periodically, update quarterly, manage explainability and governance separately

  • Decision Intelligence Approach:

    Execute decisions at scale, measure outcomes continuously, learn from performance, optimize in real-time within unified platforms that provide transparency, governance, and integration
Organizations are moving quickly:

  • 75%

    are already collaborating on AI-driven decision intelligence

  • 18%

    are exploring partnerships

  • 66%

    are very interested in using AI for strategy implementation and optimization

  • 60%

    plan to invest in AI or embedded intelligence for decisioning in 2026 (making it the top investment priority)

What Organizations Value Most

When we asked which AI features provide the most value, organizations prioritized capabilities that go beyond basic automation:

51%

Ability to leverage generative AI for natural language queries
The democratization of AI insights through conversational interfaces transforms who can access and act on decisioning data. Business users, executives, operations teams, and compliance staff can all interact directly with AI systems using natural language.

92%

of organizations find it important to interact with data quickly using natural language queries.
(62% find it very important, 30% moderately important).

  • 49%

    Real-time decisioning across customer touchpoints:
    Speed and consistency across channels create better customer experiences and reduce operational complexity.

  • 50%

    Transparency and explainability of AI models:
    Organizations need AI they can understand and defend to regulators and stakeholders.

  • 47%

    Integration with existing systems and data sources:
    AI must work with existing infrastructure rather than requiring complete replacement.

The Business Impact

Organizations cite four primary benefits from improved Decision Intelligence:

  • 62%

    cite operational efficiency:

    Automated decision-making reduces manual review, accelerates processes, and lowers costs while improving consistency.

  • 52%

    cite better customer experience:

    Faster decisions, reduced friction, and personalized interactions create superior customer journeys.

  • 58%

    cite improved accuracy of models and strategies:

    Continuous learning and optimization improve predictive performance and business outcomes over time.

  • 56%

    cite faster deployment of new decision strategies:

    Rapid testing and iteration enable organizations to adapt quickly to market changes and competitive pressure.
These benefits compound over time. Organizations that deploy Decision Intelligence don’t just get better decisions today. They build systems that continuously improve.

The Intelligence Loop in Practice

Decision Intelligence creates a continuous cycle:

  • chess

    Shape Strategy

    Design and evolve decision strategy by learning from how decisions actually perform. Strategy is measured through outcomes and continuously refined to balance risk exposure and revenue opportunity.

  • rocket

    Execute Decisions

    Make real-time, data-driven decisions at every customer touchpoint using deep customer understanding, data, context, and decision history.

  • dashboard

    Measure Outcomes

    Connect decisions to business outcomes to see what actually drives risk, revenue, and profitability.

  • learning

    Learn and Optimize

    Get specific recommendations to improve performance based on actual results. Learn from the results over time and continuously refine strategies.
This loop transforms decisioning from a periodic batch process into a continuous optimization system.

The Natural Language Revolution

92% of organizations find it important to interact with data quickly using natural language queries. This represents a fundamental shift.

When business users can interact directly with AI systems using conversation, they build intuition about how these systems work. That understanding improves their ability to provide governance oversight and makes the entire organization more comfortable with AI-driven decisioning.

Natural language querying enables:

  • Business users to explore decisioning data without SQL knowledge
  • Executives to get instant answers to strategic questions
  • Operations teams to investigate anomalies in real-time
  • Compliance teams to audit decisions conversationally
This democratization helps address one of the top implementation barriers: explainability. When more people in the organization can interact with and understand AI systems, those systems become more transparent by design.

Addressing Implementation Barriers

Decision Intelligence approaches help address the barriers preventing AI adoption:

  • Explainability

    Platforms provide visibility into what decisions were made, how they perform, and why. This makes it easier to explain outcomes to regulators and stakeholders.

  • Governance

    Connecting decisions to business outcomes (risk, revenue, customer experience) makes governance more manageable. You measure results and learn from performance rather than monitoring models in isolation.

  • Integration

    Decision Intelligence platforms orchestrate data and decisions across existing infrastructure without requiring wholesale system replacement.

  • Speed

    Organizations can learn from every decision and optimize continuously, addressing the speed challenge that 50% cite as their biggest fraud detection obstacle.

Looking Ahead

The survey reveals clear momentum:

  • 77%

    see Decision Intelligence as very valuable

  • 75%

    are already implementing it

  • 66%

    want AI for strategy optimization

  • 60%

    are investing in 2026 (top priority)
Traditional decisioning optimizes for speed. Decision Intelligence optimizes for outcomes. Organizations that build systems capable of continuous learning will create advantages that compound over time.

EBOOK Survey2026

Download the full 2026 Global Decisioning Survey:

Download Survey

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BBVA

Customer Story: BBVA

Written by provenirmulti on . Posted in Customer Story.

BBVA (Banco Bilbao Vizcaya Argentaria) is a leading Spanish multinational banking group and #3 bank in Spain by total assets,founded in 1857. It is headquartered in Madrid, offering a broad range of financial services including retail, commercial, corporate, and investment banking, as well as asset management and digital banking. The bank operates in more than 25 countries with major markets in Spain, Mexico, Turkey, South America. For those countries where it does not have physical presence, it has created “BBVA Digital Banking” , the idea it is to grow globally, the first countries in which it has been launched are Italy and Germany. It is widely recognized for its strong focus on digital innovation, data and AI capabilities, and commitment to sustainability and ESG-driven finance.
  • Industry
  • Region
  • Countries

    Spain, Colombia, Mexico, Peru, Argentina, Turkey

  • Line of Business
  • Solution
  • Module
  • Infrastructure
  • ROI
  • Competition
Customer Timeline
MRRPS
Land$160KTBC
Expand$117KTBC
  • OPPORTUNITY CREATED
    • Pilot Opp created: 02.10.17
    • Pilot Opp Won: 31.10.17
    • Opp Created: 17.03.17
  • OPPORTUNITY WON
    30.06.2018

    • Mexico expansion: 12.07.19
    • Spain expansion: 27.07.20
    • Peru expansion: 22.11.21
    • Client Analysis Corporate: 24.05.22
    • Renewal uplift: 18.07.23
    • Client Analysis Colombia: 12.10.23
    • EWS Colombia: 12.02.24
    • Enterprise agreement: 30.06.24
  • GO-LIVE
    No Information Available
  • EXPANSION
    IN PROGRESS:

    • Cloud Migration all countries
    • App Fraud Retail Banking

    FUTURE:

    • Decisioning platform BBVA Digital Banking: 1 country
    • Decisioning Platform BBVA Digital Banking: 1 country expansion
    • Retail Banking – Global ML models platform deployment & execution
Initial Opportunity Details

Customer Challenge

BBVA wanted to deliver a standardized, world-class digital experience across its global footprint and needed flexible, scalable risk decisioning technology to support consistent processes across thousands of branches and enhance risk decisioning for its commercial and Wholesale business lines. ​

Provenir Impact

  • Standardized Global Decisioning​
    BBVA now deploys a single best-practice process worldwide using Provenir’s platform, able to adjust automatically to local rules and customer variations.
  • Scalable & Automated Risk Processes​
    Provenir supports automated risk decisioning for Wholesale and commercial lending – including analysis, rating, early warning system, limit setting, early warning system and underwriting – replacing manual or inconsistent processes.
  • Operational Efficiency & Flexibility​
    The platform’s microservices architecture gives BBVA autonomy and flexibility to adapt data, models, and processes independently, improving speed and control over decision logic.

Competitors

Existing internal/legacy decisioning systems- lacking flexibility and scalability.

Experian PCO for Retail Banking Globally

Why We Won

BBVA chose Provenir for its flexible, scalable microservices-based decisioning platform that allows BBVA to build standardized global processes that automatically adjust by location, customer type, and business rules, and empowers BBVA to automate client analysis, early warning systems, rating, limit setting, and underwriting. ​

Pain Points

  • Lack of standardized decisioning experience globally
  • Need scalable, flexible technology for risk processes
  • Need automation of decisioning across markets and customer segments
  • Difficulty maintaining consistent customer experience across branches
  • Difficulty to deploy and execute ML models
Customer Growth

  • Current

    BBVA has implemented Provenir’s decisioning engine in all its markets – Spain, Turkey, Mexico, Argentina, Peru & Colombia

    Use cases under current contract in use:

    • Client Analysis
    • Early Warning System
    • Underwriting

    Use cases under current contract not in use:

    • Collections
    • Recovery

  • Expansion

    • Migrate current Provenir Platform to Cloud 2.0 for all countries: We have had several workshops regarding Cloud 2.0 with all the different areas, architecture, engineering, business. We are working internally in a ROI scenario to share with them as per request form the business and engineering. We have done a test along with the engineering team on how to deploy a Python Model in Cloud 2.0 and also form the 12th of Jan they will conduct a POC with access to our sandbox for cloud 2.0. With the results of these POC and ROI we will have all the evidence for the migration. PS Team is actively engaged with the engineering team for BAU, Pythin Model execution testing and POC
    • App Fraud – Retail Business: Current solution at BBVA Feature Space for transactional and app fraud. Information form architecture team that this solution for app fraud is not robust or mature, not enough so they would like to explore different alternatives around this current solution as satellite solution

  • Growth Opportunities

    • Provenir Global Platform for BBVA Digital Banking: We had a meeting with CRO for Digital Banking and a Workshop has already been scheduled for the 2nd of February
    • Provenir Platform – Retail Business ML models deployment & execution. This is a pain that BBVA has shared with us, but we are having difficulties to get to the stakeholders at Retail. We need to get support from the Engineering team after they conduct the POC for Wholesale Business
OTHER CUSTOMER STORIES

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FibaFaktoring

Customer Story: Fiba Faktoring

Written by provenirmulti on . Posted in Customer Story.

Fiba Faktoring is a leading non-bank financial institution in Turkey, providing factoring and SME financing solutions. The company focuses on delivering fast, data-driven credit decisions to support small and medium-sized businesses while managing risk effectively.
  • Industry
  • Region
  • Countries

    Turkey

  • Line of Business
  • Solution
  • Module
  • Infrastructure
  • ROI
  • Competition
Initial Opportunity Details

  • Customer Challenge

    Fiba Faktoring needed to improve the speed, consistency, and scalability of its credit decisioning processes. Manual and siloed systems limited automation, slowed decision times, and made it difficult to support business growth.

  • Provenir Impact

    • Operational Efficiency Gains
      Provenir’s decisioning solution delivered a 65% automation rate in credit decisions for targeted SME ticket sizes, significantly reducing reliance on manual processes:
      • Automation eliminated manual bottlenecks
      • Decisions are standardized and consistent
      • Staff time redirected from manual tasks to higher-value work
    • Speed & Productivity Improvements
      Credit decision processing became five times faster, dramatically accelerating service delivery for SME customers and improving internal throughput.
      • Faster time-to-decision improves customer experience
      • Shorter wait times support SME cash flow needs
      • The company can handle higher volumes without additional headcount
    • Workload Reduction & Customer Experience
      The platform delivered a 40% reduction in workload across credit decision processes, enabling strategic risk assessment and improving satisfaction through quicker outcomes.
      • Streamlined workflows reduced operational strain
      • Faster processing led to improved client satisfaction
      • Competitive advantage in the SME financing market

  • Competitors

    Legacy in-house systems
    Manual decisioning processes

  • Why We Won

    • Single, unified decisioning platform
    • Fast time to value and implementation
    • High flexibility and business-user configurability

  • Pain Points

    • Slow credit decision turnaround times
    • Limited automation and scalability
    • Difficulty adapting decision rules quickly
Customer Growth

Growth Opportunities

  • Scalable Operations and Expansion of Offerings
  • The automation foundation positions Fiba Faktoring to scale operations efficiently across higher volumes and broader product sets.
  • Advanced Analytics for Competitive Advantage
  • By integrating advanced predictive models and AI workflows, the company can strengthen risk insights and enhance differentiation in the SME lending market.
  • Enhanced Customer Experience as a Strategic Growth Lever
  • Shorter decision times and data-driven service delivery enable improved customer acquisition and retention.

Expansion

With the core decisioning platform successfully implemented and delivering measurable value, Fiba Faktoring is now progressing toward expanding the use of Provenir’s capabilities to additional strategic areas: ​

  • Predictive Early Warning Systems: Leveraging analytics to detect risk trends proactively
  • Marketing & Pricing Optimization: Using AI insights to refine pricing strategies and product targeting
  • Additional Decisioning Use Cases: Exploring automation across broader internal decision workflows beyond credit decisions
OTHER CUSTOMER STORIES

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newday

Customer Story: NewDay

Written by provenirmulti on . Posted in Customer Story. No Comments on Customer Story: NewDay

NewDay Ltd is a UK-based financial services company focused on responsible consumer credit who have just been acquired by KKR (private equity). Serving over 3.6 million customers, it offers products such as credit cards, instalment finance, and Buy Now Pay Later through brands like Aqua, Marbles, and Fluid, as well as co-branded solutions with major retailers. With £15.5 billion annual spend, 4.4 billion gross receivables, and advanced digital platforms, NewDay combines data-driven underwriting and technology to widen access to credit. Headquartered in London, regulated by the Financial Conduct Authority, and employing over 1,200 staff, NewDay’s mission is simple: help people move forward with credit.​
  • Industry
  • Region
  • Countries

    UK

  • Line of Business
  • Solution
  • Module
  • Infrastructure
  • ROI
  • Competition
Customer Timeline
Projected MRR: $150K
Projected ARR: £1.8m
Expand MRR: £27k
Expand PS: £324k

TCV: $5.4m
  • Renewal Created
    • Relationship since 2019
    • Cloud 2 positioning from early 2024
    • Long time users of Cloud 1 processing ~100 million trns per month
    • Originations / Collections / Customer Management
  • Renewal Result
    • Natural compelling event, however KKR Funding Challenge highlighted
    • Summer 2025
  • Go-Live
    October and November 2025
  • Customer Expansion
    • NEXT: Roll-Out: Fraud, DI, Cloud 2, Simulation
    • FUTURE:
      • Profiling
      • Case Management
      • NewDay Technology Clients
Initial Opportunity Details

  • Customer Challenge

    • Legacy decisioning systems were slow and costly to update.
    • Needed faster processing & delivery cycles (market changes, releases, tests).
    • Required greater internal control over credit decisioning logic and data sources.
    • Aimed for sub-second decisions and more product flexibility.

  • Provenir Impact

    • Speed & Agility:
      • Speed of Change Reduced by 80%
      • NewDay can now implement multiple credit decisioning changes within the same sprint.
      • Sub-Second Decisioning
      • Credit decisions are now delivered in under 1 second, enabling rapid customer feedback and better experience.
      • Impact: Faster market response and improved competitiveness.
    • Internal Control & Cost Efficiency: Enhanced Internal Control​
      • Business users can add data sources and update strategy without reliance on external vendors.
      • Reduced Operational Costs
      • Lower external costs for managing data items and system changes.
      • Quicker Onboarding
      • New hires familiarize faster due to intuitive decisioning UI.
      • Impact: More self-sufficiency, faster internal execution, and better resource allocation.
    • Competitive Advantage & Customer Experience:
      • Improved Customer Management & Collections
      • More control over limit strategy changes and refined customer decisioning.
      • Award-Winning Implementation
      • NewDay won the 2024 FSTech Award for Best Use of IT in Consumer Finance for tech innovation – powered by Provenir.
      • Impact: Enhanced customer experience, strategic differentiation, and industry recognition.

  • Competitors

  • Why We Won

    Provenir was chosen because its flexible AI-powered decisioning platform met all of NewDay’s requirements:

    • Enabled faster delivery cycles and autonomous configuration.
    • Integrated seamlessly with NewDay’s extensive data lake.
    • Supported full lifecycle decisioning from origination → collections.

  • Pain Points

    • Long release cycles and slow system updates.
    • Heavy reliance on external teams for change implementation.
    • Limited real-time testing and model deployment capabilities.
    • Inefficient credit decision support with big data sources.
Customer Growth

Growth Opportunities & Expansion

  • Fraud expansion through fraud profiling and 3rd party data integration (Focus in a future session)
  • Professional Services and Analytics opportunities – support for migration and beyond
  • Case Management
  • NewDay Technology Platform – Provenir White labelling for 3rd party use – LBG, Debenhams are live today, working towards more growth.
OTHER CUSTOMER STORIES

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RytBank

Customer Story: Ryt Bank

Written by provenirmulti on . Posted in Customer Story. No Comments on Customer Story: Ryt Bank

Ryt Bank is a Malaysia-based digital bank backed by YTL Group and Sea Limited. It positions itself as the first AI-powered bank, using its Ryt AI assistant (built on Malaysia’s ILMU LLM) to let you chat to pay bills, transfer money, and manage your account, targeting young professionals and frequent travelers with a simple, app-driven experience and transparent fees.
  • Industry
  • Region
  • Country

    Malaysia

  • Line of Business
  • Solution
  • Module
  • Infrastructure
  • ROI
  • Competition
Customer Timeline
Land MRR: $6,500 USD
Land PS: $16K USD
Expand MRR: ~$10K USD
Expand PS: $80K USD
  • Opportunity Created
    26th May 2023
  • Opportunity Won
    12th May 2025
  • Go-Live
    20th July 2025
    Technical Go-Live

    30 th August 2025
    Full Go-Live

  • Customer Expansion
    • Future: Property & Infrastructure-Linked Products
Initial Opportunity Details

  • Customer Challenge

    As a newly launched AI-powered digital bank, Ryt Bank needs to onboard and serve customers in seconds while maintaining robust risk controls and regulatory compliance. Early processes rely on a mix of internal systems, manual reviews, and hard-coded rules, making it difficult to support rapid product launches, dynamic pricing, and personalised credit decisions. This fragmentation slows time-to-yes, drives up operational effort, and limits the bank’s ability to fully leverage data and AI across the customer lifecycle. Ultimately, this impacts Ryt Bank’s ambition to scale quickly and deliver a seamless digital experience.

  • Provenir Impact

    • Smarter, AI-Driven Risk Decisions
      By combining Provenir’s decisioning platform with Ryt’s own AI models, Ryt Bank can assess creditworthiness in real time using a broader set of data points. This delivers more accurate approvals, reduces risk exposure, and supports consistent, data-driven decisions across the retail portfolio.
    • Faster Turnaround and Fully Digital Journeys
      End-to-end automation – from KYC and fraud checks to bureau calls and decision execution – has significantly reduced manual intervention, enabling near-instant decisions for onboarding and credit requests. This improves straight-through-processing rates, shortens time-to-yes, and enhances customer conversion in Ryt’s mobile-first channels.
    • Policy Compliance and Scalable Decisioning
      The solution enforces Ryt Bank’s credit, risk, and regulatory policies through configurable rules and strategies, ensuring consistent compliance with internal standards and Malaysian regulations. At the same time, it provides a flexible, scalable foundation to rapidly introduce new products and tweak policies as the bank grows.

  • Competitors

    FICO

  • Why We Won

    • Digital-Bank Ready, Cloud-Native Platform
      Provenir provides a modern, cloud-native decisioning platform designed for high-growth digital banks, supporting real-time decisions for onboarding, cards, and PayLater in a single environment.
    • Speed to Market and Business User Autonomy
      Our low-code configuration and reusable components allow Ryt Bank’s teams to rapidly design, test, and deploy strategies without heavy IT dependency, accelerating product launches and change cycles.

  • Pain Points

    • Need for instant, consistent decisions across onboarding
    • Difficulty orchestrating multiple data sources and analytics in one place
    • Limited agility to test and roll out new strategies, products, and risk policies
    • High operational overhead from manual reviews and fragmented workflows
Customer Growth

Growth Opportunities

Data Science Initiative: Collaboration with ILMU

Initial discussions have commenced between Ryt Bank, ILMU (YTL’s AI lab) and Provenir’s Data Science team to explore how ILMU’s LLM can be embedded into Provenir decisioning. This early collaboration focuses on use cases such as conversational credit applications, smarter risk insights, and automated policy explanations, laying the foundation for future AI-powered decision intelligence across Ryt Bank’s products.

Expansion

Property & Infrastructure-Linked Products

As YTL expands its townships, transport, and utilities footprint, Ryt Bank can create embedded financial products that are tightly linked to YTL’s property and infrastructure ecosystem. This includes tailored financing for YTL developments, bundled offerings that combine housing, utilities, connectivity, and banking, as well as subscription-style payments for transport and community services—all managed through the Ryt app. Such offerings deepen ecosystem stickiness, unlock new recurring revenue streams, and position Ryt Bank as the primary financial layer across YTL’s integrated developments.

OTHER CUSTOMER STORIES

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Columbia Credit Union

Customer Story: Columbia Credit Union

Written by provenirmulti on . Posted in Customer Story.

Columbia Credit Union is a member owned financial co-op serving over 100K members and managing over $2 billion in assets. Founded in 1952, CCU provides a full suite of personal & business financial services, including checking/savings, consumer + auto loans, credit cards, Home services, and SMB lending. CCU is known for their strong community focus & are recognized for their deep commitment to member services. Credit Unions like CCU are focus on strong member experiences and financial inclusion for the geography and members they serve.
  • Industry
  • Region
  • Countries

    United States

  • Line of Business
  • Solution
  • Module
  • Infrastructure
  • ROI
  • Competition
Customer Timeline
Land MRR: $13,200
Land PS: $170K
Land DS: $0
Expand MRR: ~$17.5K
Expand PS: $84K
Expand DS: $71K
  • Opportunity Created
    August 6, 2020
  • Opportunity Won
    June 24, 2021
  • Go-Live
    Late 2020, Technical Go-Live

    Unknown Full Go-Live

  • Customer Expansion
    • In Progress:
      • Deposits New Account Opening – Fraud Checks
      • Account Management
      • Deposits New Account Opening Cross-Sell Model (Data Science)
      • Indirect Auto loan portfolio analysis and optimization (Data Science)
    • Future:
      Collections, SMB Lending, HELOC, Case Management
Initial Opportunity Details

  • Customer Challenge

    • Digital transformation, move to automated underwriting to reduce cumbersome onboarding and loan process and create a more frictionless experience for Members
    • Auto, Personal Loans, and Credit Cards will be focus 1st.
    • 4,500 apps / month, where only 20% / 900 are auto approved. 40% approved, with around 425 approvals per month. Biggest channel is auto dealer indirect channel.
    • Improved and enhanced member communication
      • Ability to automatically send “notifications” and/or “text messages”
      • Ability for two way communication with applicant via text messages

  • Provenir Impact

    • Automated Underwriting Process By implementing Provenir solutions in conjunction with incumbent Meridian Link, CCU could greatly increase their automated approval rates. This improved customer satisfcation, removed unnecessary friction for good users, and streamlined the UW process.
    • Reporting The ability to Easily generate “out of policy” reports to include the reason the loan was approved/declined was a significant piece for CCU.Ingesting the decision information based on where loan failed in the auto decision process provided insights for future improvement within the workflow
    • Member Communication Utilizing decisioning and data insights from Provenir to communicate value to their member community. Ability to automatically send “notifications” and/or “text messages” Ability for two way communication with applicant via text messages​

  • Competitors

    Meridian Link, NCINO

  • Why We Won

    • Speed to change / time to market.
    • The ability to auto decision based on numerous “if-then” scenarios – Ease of updating auto decision criteria
    • Object-oriented solution design enabled more complex, multi-threaded decisioning strategies
    • Reporting:
      • Easily generate “out of policy” report to include reason the loan was approved/declined
      • Decision information based on where loan failed in the auto decision process

  • Pain Points

    • Current automated approval at 20%; wants to get to 70%.
    • Limited member communication
    • Incumbent vendor’s slow and friction-filled delivery experience
Customer Growth

Growth Opportunities

TBD

Expansion

TBD

OTHER CUSTOMER STORIES

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Dotz

Customer Story: Dotz

Written by provenirmulti on . Posted in Customer Story. No Comments on Customer Story: Dotz

Dotz was founded in 2000 with the goal of connecting consumers and retailers through a points-based loyalty program. Over the years, the company expanded its customer base and diversified its services, becoming a digital platform that delivers benefits directly to users.

In April 2022, Dotz announced the acquisition of 49% of the credit fintech Noverde, which specializes in credit solutions for individuals through B2B2C partnerships. This acquisition strengthened Dotz’s financial services strategy and expanded its product portfolio, including personal credit, cards and BNPL solutions.

  • Industry
  • Region
  • Countries

    São Paulo​ Brazil​

  • Line of Business
  • Solution
  • Module
  • Infrastructure
  • ROI
  • Competition
Customer Timeline
Land MRR: $16,289
Land PS: $137,905
Expand MRR: ~$21K
Expand PS: $70K
  • Opportunity Created
    July 6, 2024
  • Opportunity Won
    April 30, 2025
  • Go-Live
    Last week of October Technical Go-Live

    1st week of November Full Go-Live

  • Customer Expansion
    • In Progress: DS – Ongoing discussions (risk model, fraud and offer hyper-personalization)
    • Future: Case management for suspected and investigated fraud
    • Future: Credit recovery initiatives (collection)
Initial Opportunity Details

  • Customer Challenge

    The company currently operates with a legacy solution that requires significant effort from the technology team while providing minimal autonomy to business areas. This setup limits agility, hinders the achievement of strategic goals and reduces alignment with corporate directives.

    There is a need to enhance customer portfolio management by channeling clients into the Financial Services funnel to drive profitability. In addition, the company plans to expand its portfolio with the launch of new products, such as Personal Loan, BNPL (Buy Now, Pay Later) and a proprietary Credit Card, strengthening its growth strategy and revenue diversification.

  • Provenir Impact

    • Accelerating Customer Base Monetization Provenir enables the integration and orchestration of data from multiple sources, allowing greater personalization of financial product offers to Dotz customers. With faster and more accurate decision-making, Dotz can expand cross-sell and up-sell opportunities, increasing conversion into higher-margin products such as BNPL and proprietary credit cards. The platform becomes a cornerstone of Dotz’s strategy to transform into a Financial Services Hub, positioning the company as a leader in customer loyalty with strong monetization through financial services.
    • Risk Reduction and Improved Credit Quality The use of AI and machine learning enables more precise credit decisions, with greater ability to assess risk profiles in real time. This translates into lower delinquency rates, improved operational efficiency, and greater predictability of results. Dotz will strengthens its credibility with financial partners and investors, consolidating its position as a reliable and sustainable platform in the medium and long term.
    • Agility and Innovation in Product Launches Provenir’s low-code solution enables agile workflow development, providing autonomy for rapid adjustments without heavy reliance on IT. Dotz gains speed in testing, adapting, and launching new financial products, staying aligned with market trends and consumer needs. This positions Dotz as an innovative and competitive player, capable of scaling new business models and creating differentiation against traditional banks and emerging fintechs.

  • Competitors

    Oscilar

  • Why We Won

    • Strength and Strategic Alignment
      Provenir has distinguished itself through its robustness as a company, with extensive international experience and a comprehensive solution that is fully aligned with the client’s current needs and prepared to sustain long-term growth.
    • Robust Solution with AI
      Provenir’s decisioning platform is fully scalable, enabling the agile development of workflows, integrated orchestration with internal systems, databases, alternative data sources, and bureaus—ensuring greater efficiency, operational flexibility and agility in addressing new demands.

  • Pain Points

    • Pricing
    • Fast implementation
    • Flexibility in building strategies
    • Easy integration with other systems and databases
    • AI functionality
Customer Growth

Growth Opportunities

Case Management for Suspected Fraud

We are organizing a meeting with Dotz’s new Head of Fraud Prevention to explore the adoption of Provenir’s Case Management solution to support the investigation of suspected fraud cases. With this initiative, Dotz will benefit from faster and more automated processes, greater accuracy in risk identification, a significant reduction in financial losses and strengthened governance and customer trust, creating a stronger foundation for sustainable business growth.

Credit Recovery Initiatives (Collection)

Our expansion project includes the development of new debt collection use cases supported by Provenir’s decisioning platform. This initiative will enable greater automation and intelligence in credit recovery processes, with personalized strategies, dynamic customer prioritization, increased recovery rates, reduced operational costs and stronger customer relationships.

Expansion

Data Science Initiative

We are in discussions with Dotz regarding the development of customized models for credit, fraud and offer personalization. The Provenir Data Science team conducted preliminary studies using historical customer data to challenge the current model. The results were satisfactory and very promising.

This initiative aims to improve decision intelligence, automate insight extraction and drive smarter, data-driven strategies.

Example Decisioning Flows
  • Application

    Step 1

    • Portal/App
    • Core Systems and Data
    • Application Submission/Amendment
  • Eligibility

    Step 2

    • Blacklist Data
    • Fraud & ID Data
  • Credit Checks

    Step 3

    • History Data
    • Bureau Data
    • Alternative Data
  • Analytics

    Step 4

    • PD Model Analytics
  • Decisioning

    Step 5

    • Recommend & Highlight
    • Eligibility/Rules/Affordability
OTHER CUSTOMER STORIES

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FNBO

Customer Story: FNBO

Written by provenirmulti on . Posted in Customer Story. No Comments on Customer Story: FNBO

First National Bank of Omaha (FNBO) is a privately owned financial institution headquartered in Omaha, Nebraska. Founded in 1857 by brothers Herman and Augustus Kountze, it is the oldest national bank in the United States west of the Missouri River. FNBO operates as a subsidiary of First National of Nebraska, Inc., a bank holding company primarily owned by the Lauritzen family.

FNBO has over $32 billion in assets and employs approximately 4,500 people across eight states: Nebraska, Colorado, Illinois, Iowa, Kansas, South Dakota, Texas, and Wyoming.

  • Industry
  • Region
  • Countries

    United States

  • Line of Business
  • Solution
  • Module
  • Infrastructure
  • ROI
  • Competition
Customer Timeline
Land MRR: $61,341.90
Land PS: $400K
Expand MRR: $24,204
Expand PS: $360K
  • Opportunity Created
    October 2023
  • Opportunity Won
    May 2024
  • Go-Live
    Unsecured Consumer Loans, April 2025

    Consumer Credit Card, November 2025

  • Customer Expansion
    • NEXT: Small Business Credit Card,
      Customer Management
    • FUTURE:
      • Auto Loans
      • Home Equity Loans & Lines of Credit
      • Collections
      • Multi-bureau Waterfall
      • Application Re-decisioning
      • Fraud Risk Decisioning Waterfall
      • Document Verification
      • Zest Migration/ AI Model Support
      • Payment Verification
Initial Opportunity Details

  • Customer Challenge

    • Migrating from legacy platforms that required frequently updates, upgrades, patches and maintenance costs
    • Testing capabilities were very limited
    • Onboarding and testing new data sources difficult, time consuming and costly
    • Complex decisioning strategies were impractical given solution design, requiring inefficient workarounds that weighed on SLAs

  • Provenir Impact

    • Return to Growth: After the challenges brought on by COVD-19 and the inflationary and high-interest rate environments that resulted, FNBO can now invest for growth by more rapidly testing and deploying multi-faceted risk strategies for their high-growth unsecured credit card product lines that are sold through strong retail partnerships through the USA, optimizing price and controlling for credit and fraud risk
    • Improve Lending Efficiency: Limitations of legacy systems prevented FNBO from intelligently waterfalling through alternative bureau, fraud & other data sources, decisioning on multiple applicants, & re-processing applications upon receipt of new information. Now lending operations are streamlined, false positives reduced, & automation increased, leading to higher volumes that exceed pricing & lending standards.
    • Full 360º View of Lending Operations: The Provenir unified platform now allows administrative governance of risk strategies across lines of business, allowing shared components to be deployed for multiple products and enhanced in a more agile fashion, allowing FNBO to move faster than previously and re-deploy human resources to higher return activities vs. on maintenance of credit risk decisioning systems.

  • Competitors

    Experian

  • Why We Won

    • Cloud-native solution reduced / eliminated costly maintenance
    • Strong testing and deployment capabilities
    • Object-oriented solution design enabled more complex, multi-threaded decisioning strategies
    • Unified platform for all decisioning made customer management, collections and other lines of business easy to migrate onto the platform

  • Pain Points

    • Migrating from legacy platforms that required frequently updates, upgrades, patches and maintenance costs
    • Testing capabilities were very limited
    • Onboarding and testing new data sources difficult, time consuming and costly
    • Complex decisioning strategies were impractical given solution design, requiring inefficient workarounds that weighed on SLAs
Customer Growth

Growth Opportunities

FNBO plans to expand the platform into Account Management and Collections as its two near-term strategic initiatives, and will expand its use into new lines of business including small business credit card, auto lending, home equity and other lines of business.

Additionally, several areas of opportunity for optimization have arisen in re-evaluating certain business workflows and decisioning strategies, including but not limited to multi-bureau waterfalls that features a new primary bureau, fraud risk decisioning waterfalls to support stronger onboarding with less friction and more fraud assurances, migration from Zest for ML scoring to internal use of advanced analytics, document verification in new account opening processes for consumer and small business banking, and others.

Expansion

The collaborative, on-demand relationship developed between FNBO and Provenir to implement products and consult on a wide-range of topics necessitate a more flexible support model. As a result, Provenir is proposing a bespoke support subscription that includes implementation resources, training, data science and business consulting to both expand the product and maximize its impact on the bank’s top- and bottom lines.

The bespoke support subscription adds $24,000+ in MRR and allows FNBO to tap into up to 4,000 hours over 42 months to tackle a broad range initiatives that directors at the bank have indicated are its top priorities.

Example Decisioning Flows
  • Initialize Data

    Step 1

    • Initialize Data
    • Initial Trasnformation
    • Initial Calculations
  • Critical Field Check

    Step 2

    • Require field checks
    • Checking Missing or Null
  • Eligibility Check

    Step 3

    • Product Eligibiltiy Check
    • Knockout Rules
  • Fetch Acct Data

    Step 4

    • Call FNBO to get Acct Data
  • Duplicate Application Check

    Step 5

    • Check if duplicate app
  • Duplicate Account Check

    Step 6

    • Check for duplicate accounts
  • Delinquency Check

    Step 7

    • Check for delinquency
  • Aggregate Exposure Check

    Step 8

    • Calculate Aggregate Exposure
  • Internal Fraud Check

    Step 9

    • Run a check against internal fraud database
  • External Fraud Check

    Step 10

    • Call Iovation, Socure Fraud
    • Check for Fraud
  • KYC Check

    Step 11

    • Call Socure KYC
    • Verify Applicant
  • Final Decision

    Step 12

    • Final Decision
    • Final Trasnformation
  • Save Data Model to DB

    Step 13

    • Save Data Model to DB
  • Initialize Data

    Step 1

    • Initialize Data
    • Initial Trasnformation
    • Initial Calculations
OTHER CUSTOMER STORIES

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MFG

Customer Story: MFG

Written by provenirmulti on . Posted in Customer Story.

Management Financial Group. It’s a group of companies uniting leading providers of non-bank financial services in Europe since 2005. HQ is in Bulgaria. Operating in Ukraine, Romania, Poland, Spain, North Macedonia and Croatia. MFG has more than 8300 employees and associates in over 450 offices.

MFG provides short-term, flexible B2C and B2B loans, revolving and instalment plan credit cards, and other financial and insurance services to underserved and underbanked sectors, as well as the general public. They believe in providing financial access for everyone.

MFG targets to expand the territory and Provenir to continue to be the backbone of entering in new countries.

  • Industry
  • Region
  • Countries

    Sweden, Finland, Denmark, Norway

  • Line of Business
  • Solution
  • Module
  • Infrastructure
  • ROI
  • Competition
Customer Timeline
Land MRR: Avg €30K
Land PS: N/A
Expand MRR: Avg €3-5K
Expand PS: €55K
  • Opportunity Created
    2019
  • Opportunity Won
    March 2019
  • Go-Live
    July 2019
    Renewed 5yrs June 2024
  • Customer Expansion
    • In Progress: Cloud 2.0 Migration
    • Future: Data Science Services
OTHER CUSTOMER STORIES

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traton

Customer Story: Traton

Written by provenirmulti on . Posted in Customer Story.

Traton Financial Services operates as a finance provider for the wider Traton Group, one of the world’s largest commercial vehicle manufactures. Traton comprises of 4 major brands – Scania, MAN, International Financial and VW Bus & Trucking.

Traton Financial Services’ primary role is to provide financial options that help drive the growth and strategic goals of each business unit.

Today, Traton Group has circa 105 thousand employees, spread over 100 countries globally.

  • Industry
  • Region
  • Countries

    Sweden, Finland, Denmark, Norway

  • Line of Business
  • Solution
  • Module
  • Infrastructure
  • ROI
  • Competition
Customer Timeline
Land MRR: €10K
Land PS: €194K
Expansion MRR: €29K
Expansion PS: €500K
Future MRR: ~€ 20K (TFS)
Future PS: €250K
  • Opportunity Created
    April 2020
  • Opportunity Won
    February 2021
  • Go-Live
    Scania Italy January 2024
    Scania Australia May 2024
    MAN Italy May 2024
    MAN Spain Jan 2025
    MAN Portugal June 2025
  • Customer Expansion

    In Progress

    • Discussions around Cloud 2 and adoption in other geographies
    • Subscription Services – driving self sufficiency.

    Future

    • Broaden discussions into Fraud
    • Leverage success to drive across the wider VW Group
Initial Opportunity Details

  • Customer Challenge

    Our journey began with Scania who were looking to replace a fractured legacy of disparate systems across their global business units with a modernized singular decisioning platform to support their TOM. They were focusing on removing customer friction from the sales process and supporting a move towards a single Global Customer View.

    Following the merger into Traton FS, Provenir was selected as the group standard as they looked to address a larger problem: how to create a unified, consistent customer experience across the group. We are now in the process of supporting the central team drive this standard to the global business units.

  • Provenir Impact

    • Improve operational efficiency through Digitalization & Automation of the customer onboarding and credit processes
    • Improve CX and conversion rates through customization and real time decisioning
    • Provide better overview, control and risk governance through a structured global platform
    • Support growth through improved flexibility, speed and scalability

  • Competitors

    Experian, FICO

  • Why We Won

    Data-Orchestration / Integration:

    • We demonstrated the ease in which we can automate 3rd party calls to provide a single view of the customers data, integrating into various systems globally.

    Re-Use for accelerated value:

    • Traton’s ambition for a global harmonisation of their credit systems meant re-use was essential for their business to scale. This was a clear differentiator for us in the process.

  • Pain Points

    • Slow transactions with too much customer friction
    • No Consistency – bad global standard
    • Lack of Global and Local Customisation
Customer Growth

Short-Term Growth Opportunities

Self-Sufficiency:

  • Driving the adoption of a subscription service that will provide their centralised team with access to enablement materials and collaboration with wider PS / DS teams.

New Business Units

  • Expansion into Thailand & Malaysia. These units are run by the team in Australia, where we are already live, and provide us the opportunity to consolidate the APJ triton business units onto a single instance, separate from the existing global infrastructure.

Expansion

We are engaging with Traton on expansion into other regions, where Data Residency laws are making it challenging for the local business units to leverage the existing global solution. Each deployment across into new regions ensures that the Provenir solution becomes a more integral component of their global architecture.

OTHER CUSTOMER STORIES

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