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Top Mortgage Lending Trends in the UK and Europe

Top Mortgage Lending Trends in the UK and Europe: Smarter Decisioning for a Changing Market

Navigating evolving market conditions, affordability challenges, and AI-driven risk management

The UK mortgage market is poised for a notable rebound in the coming year, with mortgage lending growth projected to double compared to 2023, according to EY. While this signals renewed optimism, lenders are still navigating complex challenges — rising interest rates, affordability constraints, evolving regulatory pressures, and shifting borrower expectations.

Across Europe, mortgage markets are experiencing varying levels of volatility. Some countries, like Germany and the Netherlands, are facing demand fluctuations due to interest rate adjustments, while others, such as France and Spain, are seeing pockets of resilience amid broader economic uncertainty.

So, how can lenders capitalize on growth while managing risk? By embracing advanced credit and fraud risk decisioning, leveraging alternative data, and integrating AI-driven automation, mortgage providers can ensure they remain competitive in a rapidly changing landscape. Here’s what you need to know.

1. Mortgage Market Rebound: Will Growth Be Sustainable?

After recent turbulence, the UK mortgage market is showing early signs of recovery. The latest data from EY forecasts that net mortgage lending will grow from £11bn in 2023 to £22bn — a significant shift fueled by economic stabilization and a potential slowdown in interest rate hikes. However, growth comes with some challenges:

  • Interest rates remain high compared to pre-pandemic levels, affecting affordability.
  • Consumer confidence is still fragile, with borrowers cautious about long-term financial commitments.
  • Regulatory scrutiny is increasing, with the Financial Conduct Authority (FCA) pushing for fair lending practices and enhanced risk oversight.
Across Europe, trends vary widely:
  • Germany is experiencing weaker housing demand due to tightening credit conditions.
  • France is navigating a slowdown in new mortgage approvals amid regulatory adjustments.
  • Spain and Portugal are seeing a rise in international buyers, stabilizing demand despite domestic affordability challenges.
What do you need to do? To thrive in this landscape, mortgage providers must improve risk assessment capabilities and adopt more dynamic credit and fraud risk decisioning frameworks that can adjust to market shifts in real time.
2. The Affordability Dilemma: Why Traditional Credit Scoring Isn’t Enough
Affordability remains one of the biggest challenges in the UK mortgage market. While lending volumes are set to increase, many borrowers are still struggling with:
  • High living costs and wage stagnation, which impact disposable income.
  • Stringent mortgage stress tests, making it harder for first-time buyers to qualify.
  • Variable rate mortgages, which are exposing homeowners to fluctuating monthly payments.
Traditional credit scoring models (which are heavily reliant on credit history and debt-to-income ratios) often fail to provide a full picture of a borrower’s financial health. That’s why leading lenders are increasingly turning to alternative data like the following to refine their risk assessments:
  • Open banking data: Real-time income and spending patterns can help assess affordability more accurately.
  • Rental payment history: Demonstrates financial discipline, especially for first-time buyers.
  • Utility and telecom payments: Provides additional insights into payment behaviors and financial stability.

By integrating AI-powered risk decisioning, you can analyze alternative data at scale, leading to more inclusive lending decisions and better default risk prediction.

What do you need to do? Move beyond traditional credit scores by adopting AI-driven analytics and alternative data sources to expand lending opportunities without increasing risk.

3. AI and Automation: The Future of Mortgage Decisioning

With mortgage competition increasing and regulatory expectations rising, you can no longer afford slow, manual credit decisioning processes. AI and automation are becoming essential tools for enhancing speed, accuracy, and compliance.

AI is transforming mortgage lending with:

  • Instant Decisioning – AI models process vast amounts of data in real time, reducing approval times from weeks to minutes.
  • Advanced Fraud Detection – AI-powered anomaly detection helps identify fraudulent applications before loans are approved.
  • Improved Regulatory Compliance – AI ensures fair lending practices by providing explainable decisioning frameworks and reducing bias.

But what’s the competitive advantage to AI Decisioning?

  • Higher Approval Rates: More borrowers qualify for mortgages through personalized risk assessment.
  • Reduced Risk Exposure: Predictive analytics detect high-risk applicants before issues arise.
  • Operational Efficiency: Automating credit checks and underwriting reduces costs and processing times.
What do you need to do? Future-proof your mortgage operations by implementing AI-driven decisioning platforms that enhance efficiency while maintaining compliance with FCA and EU regulatory guidelines.
Building a Smarter Mortgage Lending Strategy

With UK mortgage lending growth set to double and European markets shifting, mortgage providers must evolve their decisioning strategies to remain competitive.

By embracing AI, alternative data, and automated decisioning, you can:

  • Expand access to credit while minimizing default risk.
  • Deliver faster, more seamless customer experiences.
  • Ensure compliance with evolving regulatory standards.

As the mortgage landscape continues to change, the lenders that invest in innovation today will be the market leaders of tomorrow.

Ready to future-proof your mortgage lending strategy? Discover how AI-driven decisioning can help you boost approvals, manage risk, and streamline compliance.

Shape the future of your mortgage strategy with AI.

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NEWS: AI Risk Decisioning Leader Provenir to Sponsor Financial Services Events

AI Risk Decisioning Leader Provenir to Sponsor Upcoming Banking and Financial Services Events

Parsippany, NJ – February 19, 2025 – Provenir, a global leader in AI risk decisioning software, today announced its participation and sponsorship of three upcoming banking and fintech events focusing on key topics, including digital banking, banking trends, and policy and regulatory issues.

The events provide Provenir an opportunity to meet with financial services leaders to better understand the challenges they face amidst rising consumer debt, evolving digital banking platforms, and fraud mitigation. According to a recent survey by Provenir, nearly half of all financial services executives are struggling with managing credit risk and detecting and preventing fraud.

Details of the events include:

future digital finance connectFuture Digital Finance Connect 2025

Future Digital Finance Connect 2025
(Feb. 24-25, New Orleans)
The inaugural Future Digital Finance Connect is an exclusive, invitation-only gathering for senior digital and innovation leaders from top big banks, community banks, credit unions, credit cards and insurers. Provenir is a sponsor.

fintech meetupFintech Meetup

Fintech Meetup
(March 10-13, Las Vegas)
Fintech Meetup is the largest and most productive event for networking in the industry, bringing together fintech leaders to network, collaborate, and discuss industry issues. Provenir is a bronze sponsor and will be located at stand #2326.

cba liveCBA Live 2025

CBA Live 2025
(March 17-19, Orlando)
At CBA LIVE, retail banking professionals come to explore regulatory and policy issues, learn new trends, and share ideas that will improve their business strategies and better serve their customers. Provenir is a silver sponsor.

Provenir’s AI Decisioning Platform brings together the power of decisioning, data, and decision intelligence to drive smarter decisions. This unique offering gives organizations the ability to power decisioning innovation across the full customer lifecycle, driving improvements in the customer experience, best-in-class fraud prevention, access to financial services, business agility, and more.
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Customer Story: Charter

charter logo

Charter Communications is a leading broadband connectivity company and cable operator, headquartered in Stamford, Connecticut. With an annual revenue of $55 billion, Charter provides high-speed internet, video, mobile, and voice services to millions of customers across 41 U.S. states.

As a trusted provider, Charter serves 57 million homes and connects 500 million IP devices to its robust network. The company also powers businesses with 300,000 fiber-lit commercial office buildings, ensuring seamless connectivity and innovation. Recognized for excellence, Charter has been ranked #1 in customer satisfaction by JD Power within its peer group, reflecting its commitment to delivering high-quality service and superior customer experience.

  • Industry
  • Region
  • Countries

    United States

  • Line of Business
  • Solution
  • Module
  • Infrastructure
  • ROI
  • Competition

Customer Timeline
Land MRR: $62K
Land PS: $462K
Expand MRR: $100K
Expand PS: $250K
  • Opportunity Created
    June 28, 2024
  • Opportunity Won
    January 21, 2025
  • Go-Live
    Estimated July 2025
  • Customer Expansion
    • Collections/Delinquency Mitigation
    • Portfolio Management (upsell/cross sell)
    • TRMA Sponsorship
    • Case Study
Initial Opportunity Details

  • Customer Challenge

    • Charter has seen application fraud rates spike significantly over the past three years.
    • Antiquated systems prevented Charter from effectively mitigating application fraud
    • Experian FraudNet Solution cost over $1M a year to support and was ineffective.
    • New senior executive team hired to rebuild Charter fraud onboarding infrastructure
    • Charter Data Science team was handcuffed by poor analytics, testing capabilities, and decentralized workflow tools.
  • Provenir Approach

    Profiling Engine

    Aggregation of specific values over a time period.

    • “Grouping of Activity” / “Buckets of Behavior”
    Examples:
    • IP Address 168.192.1.1 has been on 10 transactions over the past 6 hours
    • Location 123 has had a median order amount of $5,222 over the past 180 days
    Python Model Deployment

    Provenir provides the Charter Data Science team a platform to deploy, execute, test, monitor models they build to detect Fraud and Risk.

  • Provenir Impact

    • Reduced customer friction and losses, while optimizing operations through a stable, reliable, and scalable platform to support analytics and reporting needs.
    • Fraud and credit abuse controls prior to order submission will enable more accurate real-time decisioning.
    • $1M immediate annual cost reduction with the elimination of the Experian FraudNet tool.
    • The platform will enable risk assessment functionalities like testing rule performance and fraud decisioning through advanced ML models
    • Centralized Rule and Model Governance
  • Competitors

    Experian (incumbent), FICO, DataVisor, Socure, Visa (risk product) and Pega
  • Why We Won

    • Provenir Solution: Provenir Profiling Engine provided the most compelling/complete solution for Charter
    • Our Team: Fraud Expertise + Implementation Certainty
    • Decision Intelligence and Advanced AI/ML
      Centralized Rules and Model Governance
  • Pain Points

    • Decentralized fraud controls
    • Poor Analytics and Reporting
    • Infrastructure Downtime
    • Inability to leverage AI and Advanced Learning models
Customer Growth

Growth Opportunities

Organic Volume Growth – Charter’s expecting significant geographic expansion over next 3-5 years.

Expansion

  • Portfolio Management/Account Management
  • Collections – Charter has seen a rise in delinquencies and customer churn
Example Decisioning Flows
  • New Application

    Decisioning

    Orders received for two channels:

    1.Ship to Home
    or
    2.In Store

  • Internal/external Data Calls

    Decisioning

    Data Vendors

    • Ekata
    • SentiLink
    • Datafiniti
    • Nuance
    • RevSprings
    • UPS/FedEx
    • Citrix
    • Authentic ID
  • Real-Time Fraud Checks

    Decisioning

    Rules and Lookups

    • Negative List
    • Velocity Checks
    • Email, Billing, Device, Attempts, etc.
    • Feature Aggregation
    • Blacklist
    • Valid/Deceased SSN
    • Fraud Prevention Scenarios
    • SMB Orders
    • Positive Lists
  • Scoring and Risk Models

    Decisioning

    Analytical Models

    • Models built by Charter Data Scientists in KC
    • Champion / Challenge
    • Ongoing Feature Engineering
  • Manual Review Exceptions

    Decisioning

    Alert Review

    • Red / Yellow / Green Risk Assignment
    • Fraud, Credit, Sanctions, Affordability Analyst and Underwriter Reviews
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DATA SHEET: Fraud for Telco

Provenir: Application Fraud for Telcos

Holistic Fraud Detection with Comprehensive Subscriber View
Telcos globally are struggling with increasingly sophisticated fraud attempts fuelled in part by rapid digital transformation and exacting subscriber demands. But how can you stay ahead of evolving fraud tactics while ensuring a seamless customer experience for legitimate subscribers? Discover how Provenir’s Application Fraud solution enables you to detect fraud risk more accurately with a holistic, comprehensive view of your subscribers.
Discover how Provenir’s AI Decisioning can transform your telco business.

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NEWS: 2025 New Global Survey

New Global Survey Shows Nearly Half of Financial Services Executives Struggling to Manage Credit Risk and Detect and Prevent Fraud

AI is playing a prominent role in the revamp of credit risk decisioning
and fraud prevention strategies in 2025

Parsippany, NJ – February 12, 2025 – A new survey shows nearly half of all financial services executives are struggling with managing credit risk and detecting and preventing fraud. The survey also shows many are revamping their credit risk decisioning and fraud prevention strategies in 2025, with AI playing a prominent role.

These are among the key findings from the survey of nearly 200 key decision makers at financial services providers globally to understand their risk decisioning and fraud challenges across the customer lifecycle, decisioning investment priorities, and AI opportunities. The survey was conducted by Provenir, a global leader in AI Decisioning solutions.

Over half of all respondents plan to invest in risk decisioning solutions and AI/embedded intelligence in 2025 and beyond. At present, nearly 60% of respondents say they find it difficult to deploy and maintain risk decisioning models. 55% of executives recognize the value of AI to make streamlined strategy decisions, and in its ability to provide AI-powered performance improvement recommendations, and 53% see the value in the ability to automatically tune models to make better, more accurate decisions.

Key priorities for customer and account management are real-time, event-driven decisioning (65%), eliminating friction across the customer lifecycle (44%), and increasing customer lifetime value (44%).

Over half of respondents agree the biggest data challenge they face is being able to easily integrate data sources into decisioning processes.

Survey insights also reveal the pitfalls of operating multiple decisioning systems across the customer lifecycle. 59% of respondents say this is causing a lack of seamless data flow and unified insights, while 52% say it creates operational inefficiencies. Additionally, 28% said it contributes to an inconsistent customer experience.

When asked about data and fraud, 37% say they struggle with effective data orchestration for application fraud prevention, specifically in not being able to easily ingest and integrate new data sources, while 36% are challenged in using AI and machine learning for fraud prevention. Nearly one-third of respondents agree that the most important aspect for comprehensive fraud strategies is the ability to break down data silos between fraud and credit risk teams.

“Financial institutions are keenly aware of today’s increasingly complex threat landscape and must adopt new approaches for improved risk decisioning and fraud prevention across the customer lifecycle while providing frictionless and personalized customer experiences,” said Carol Hamilton, Chief Product Officer, Provenir. “With an AI decisioning platform more closely aligning credit and fraud risk teams, financial services executives can ensure holistic, end-to-end decisioning with a complete view of customers across the entire lifecycle.”

The survey was conducted November-December 2024; respondents were based in North America, EMEA, Latin America and Asia Pacific, holding the titles of manager, director, vice president, or above.

The full report of the survey findings can be found here.

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Survey: 2025 Global Risk Decisioning Survey

Survey: 2025 Global Risk Decisioning Survey

What are the key challenges and priorities for financial services providers in 2025 and beyond?
Provenir surveyed nearly 200 key decision makers at financial services providers globally, including Chief Risk Officers, CEOs, VPs, Senior Directors, Managing Directors, Decision Scientists, Heads of Risk, IT, Fraud and more.

The results highlight:

  • Their risk decisioning and fraud challenges across the customer lifecycle
  • Decisioning investment priorities
  • AI opportunities
Get the insights now.
Ready to shape the future of your decisioning with AI?

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BLOG: Unlocking Success in Poland’s Lending Revolution

Thriving Through Change: Unlocking Success in Poland’s Lending Revolution

Adapting to Rising Rates, Evolving Borrower Needs, and the Power of Technology in a Dynamic Market
  • Mark Collingwood
    Vice President, Sales

Poland’s economic landscape is undergoing significant change, with rising inflation and interest rates (as of December 2024, the annual inflation rate increased from 4.7% to 4.8% the month before, indicating persistent inflationary pressures). Likewise, mortgage interest rates are also on the rise, with the average rate in the country reaching 7.16% in late 2024, up from just 2.27% in December of 2022. While this economic shift presents both challenges and opportunities for lenders in Poland, one thing is clear – to navigate this evolving environment successfully, financial services providers must look to innovative and agile approaches that address changing borrower needs while still effectively mitigating risk. In this blog, we’re looking more closely at this shift, and how you can ensure your business thrives amidst uncertainty.

The Impact of Economic Shifts on Lending in Poland

There’s notable turbulence in Poland’s economy, driven by persistently high inflation and elevated interest rates. At the end of last year, inflation remained high, impacting consumer purchasing power and financial stability. And mortgage rates, which have exceeded 7% for many borrowers, adds further strain to household budgets, making lending challenging for both consumers and lenders. With rising costs like this, potential homebuyers are forced to reassess affordability, which then has the domino effect of slowing down the mortgage market and reshaping the overall lending landscape.

On top of economic pressures, the regulatory environment in Poland is tightening its grip to ensure financial stability. The Polish Financial Supervision Authority (KNF) plays a pivotal role, introducing policies to strengthen risk management and promote financial resilience. Some of these initiatives include enhanced creditworthiness assessments and stricter compliance measures, with the aim to mitigate systemic risks while encouraging responsible lending practices.

But these regulations can present operational challenges for lenders. Balancing regulatory compliance with providing accessible, competitive loan products can be tricky – highlighting the importance of both efficiency and innovation in navigating lending in complex economic situations. Collaboration with regulatory bodies, paired with strategic investments in decisioning technology, will be essential for lenders who want to future-proof their lending strategy.

Evolving Borrower Dynamics: Embracing Flexibility and Digital Innovation to Stay Competitive

Borrowers in Poland are increasingly seeking alternative financing solutions that provide greater flexibility and personalization. Traditional, rigid lending structures are out. Instead, driven by consumers’ desire for financial products that align with their own unique needs and circumstances, budget-conscious borrowers are now prioritizing loan options that offer more adaptable terms and personalized services. To meet these shifting demands, you have to embrace the opportunity to develop and offer:

  • Flexible Loan Products: Options like adjustable-rate mortgages and payment holidays help borrowers seeking more adaptable repayment plans.
  • Personalized Financial Solutions: Tailor loan offerings to individual borrower profiles to enhance customer satisfaction and loyalty.
  • Digital Accessibility and User-Friendly Platforms: Invest in intuitive digital platforms, keeping in mind the implementation of the European Accessibility Act (EAA), which mandates accessibility requirements for products and services (including digital interfaces).

How do you accomplish this? By leveraging advanced technologies, especially artificial intelligence (AI) and machine learning (ML), to transform your credit assessment and fraud detection processes.

AI-driven systems can process vast amounts of financial data in real time, utilizing advanced ML algorithms to identify patterns and anomalies that indicate a borrower’s potential credit risk. Predictive models can analyze spending behavior, transaction history, and even social media data, enabling more accurate credit risk assessments – and more informed lending decisions.
And when it comes to that ever-present thorn in the side of lenders everywhere, fraud, AI/ML offers critical help. Analyzing extensive datasets quickly allows these systems to detect unusual patterns and behaviours that can signal fraudulent activity, allowing for prompt intervention. Fraud detection strategies that incorporate AI have even been shown to improve accuracy in distinguishing between human errors and genuine fraud attempts, reducing unnecessary interventions and false alarms (and saving you time and people-power in the process).

Using advanced technologies like AI/ML is helping to drive digital transformation in lending, and allows for more customer-centric processes:

  • Adoption Rates: Poland is leading central Europe’s digital transformation, with many financial institutions having invested in digital transformation initiatives, recognizing the importance of digital transformation and reflecting a commitment to modernizing operations and enhancing service delivery.
  • Rise of Digital Banking: Digital banking has become the primary channel for financial transactions for many Poles. In 2024, online banking penetration in Poland reached 65%.
  • Successful Digital Lending Initiatives: Poland has witnessed the emergence of innovative digital lending platforms that streamline the borrowing process. For instance, the mobile payment system BLIK allows users to make instant payments and withdraw cash using their standard mobile banking app, enhancing the efficiency and convenience of financial transactions.
  • Streamlining Loan Applications and Approvals: The adoption of AI and digital platforms has revolutionized the loan application process. Automated systems enable quicker approvals by efficiently analyzing applicant data, reducing the time from application to disbursement.
  • Building Trust and Engagement: User-friendly digital platforms enhance customer experience, fostering trust and engagement. Features like personalized dashboards, real-time notifications, and responsive customer service contribute to higher customer satisfaction and loyalty.

Embracing strategies like these will allow you to position yourselves more competitively – all while you enhance operational efficiency, improve risk management, and deliver superior customer experiences.

Riding the Risk Wave: Smart Strategies for Lending Success in Poland

The strain that high inflation and interest rates places on borrowers increases the risk of loan defaults, whether those loans are mortgages or otherwise. When things are shifting, reactive strategies are no longer sufficient. But adopting a more proactive risk management approach, powered by advanced technologies and strategic partnerships, can help you get (and stay) ahead of these pressures:

  • Strengthen Borrower Assessments

    Enhance underwriting processes by integrating AI-driven tools that evaluate real-time borrower data for more accurate risk profiling.
  • Offer Flexible Repayment Options

    Payment holidays or loan restructuring options can support borrowers facing temporary financial challenges, helping to prevent defaults.
  • Adopt Early Warning Systems

    Proactive monitoring of repayment behaviors can flag potential issues early, allowing for timely interventions and tailored borrower support.
  • Real-Time Analytics and Predictive Modelling

    Tools like Provenir’s AI Decisioning platform empower lenders with the ability to analyze data streams in real-time, identify emerging risks, and predict future trends. This enables precise adjustments to lending strategies before problems escalate.

  • Balance Growth with Risk Mitigation

    Sustainable growth requires a dual focus on expanding lending portfolios while maintaining robust risk controls. Leveraging predictive analytics ensures lenders can scale responsibly without exposing themselves to unnecessary risks.

  • Partner With Technology Providers

    Partnerships with tech companies drive innovation, offering solutions for automating credit assessments, fraud detection, and compliance processes.
  • Regulatory Collaboration

    Working with regulatory bodies, such as the Polish Financial Supervision Authority (KNF), ensures compliance with evolving rules and builds trust with stakeholders.
Managing risk in Poland’s uncertain lending environment requires lenders to stay ahead of challenges through innovation, collaboration, and proactive strategies. By leveraging real-time analytics, fostering partnerships, and aligning with regulatory frameworks, lenders can strike the delicate balance between growth and risk mitigation, ensuring long-term success in an ever-changing market.

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KNF Initiatives

The KNF is spearheading efforts to enhance Poland’s financial infrastructure, ensuring the industry can adapt to current challenges:

  • Digital Infrastructure Improvements: Investments in digital infrastructure, including secure data-sharing platforms, streamline operations and improve resilience.
  • Data-Sharing Frameworks: By encouraging transparency and collaboration among financial institutions, KNF initiatives reduce risks while fostering a culture of shared accountability.

Rising to the Occasion: Lending Strategies for Poland’s Future

There is a lot of positivity on the horizon for Poland – the outlook for 2025 is strong, with the Organisation for Economic Co-operation and Development (OECD) projecting a GDP growth rate of 2.4%. This expansion will help invigorate the lending market, and the country’s digital economy is already on a rapid ascent, thanks to the widespread adoption of e-commerce, mobile payments, and online banking tech. The digital economy is predicted to reach $87 billion this year, and over $130 billion by 2030. With a tech-savvy population that is increasingly looking for innovative financial solutions, the runway of opportunity for lenders that adapt to these preferences is long and healthy.

To fully take advantage of what digital transformation in Poland has to offer, consider these strategies:

  • Stay Agile in Adapting to Economic and Regulatory Changes:
    The dynamic nature of Poland’s economy and regulatory environment means you need to remain flexible and responsive. Implementing adaptive business models and staying informed about policy shifts are crucial for sustained success.
  • Leverage Technology to Prioritize Customer Needs and Experiences:
    Embracing digital tools can enhance customer interactions and streamline operations. For instance, the rise of neobanking in Poland is projected to grow by 10.86% between 2025 and 2028, reaching a market volume of $35.82 billion by 2028.
    This trend underscores the importance of digital accessibility and user-friendly platforms in meeting customer expectations.
  • Develop Sustainable, Customer-Focused Lending Practices:
    Offering personalized financial products that cater to individual borrower profiles can foster customer loyalty and drive growth. Flexible loan options and transparent communication are key components of a customer-centric approach.

Poland’s lending market presents a challenging yet promising landscape. Lenders who embrace digital transformation, proactively manage risk, and prioritize borrower-centric innovation will not only navigate economic uncertainties but also seize opportunities for growth. One of the best measures of future-proofing success? The right technology partner.

Provenir’s AI Decisioning platform is uniquely positioned to empower lenders in Poland to thrive in this dynamic environment. By harnessing the power of AI and machine learning, our platform enhances fraud detection, streamlines credit risk assessment, and delivers real-time insights to help you make faster, more informed decisions.

Discover how our AI decisioning platform can help you drive operational efficiency, mitigate risk, and foster stronger customer relationships.

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BLOG: Shaping the Future of Decisioning

Shaping the Future of Decisioning: How These Leading Financial Services Providers are Making Bold Moves to Win Big with AI

The use of artificial intelligence (AI) has changed the entire world, in both big and small ways. Financial services is now increasingly looking to AI when it comes to risk decisioning – everything from whether to approve a loan application or increase a credit limit to fundamental decisions on whether a ‘customer’ is a fraud or not. Whether you are looking to streamline credit evaluations or improve customer experiences, the results are clear – big wins happen when organizations are ready to make bold moves in their adoption of AI. Harnessing the power of AI allows you to achieve measurable gains in efficiency, accuracy, and agility – and shape the future of decisioning. We’re looking at ten financial services providers around the globe who are leveraging AI to transform their operations, mitigate risks, and deliver exceptional value to their customers.

commbank

Commonwealth Bank of Australia (CBA)

An Australian multinational bank, CBA is one of the leading banks in the region, serving more than 17 million customers. With a recent mammoth investment in advanced tech (the bank spends about $1 billion per year on growth-focused technology), CBA has integrated AI across various operations including fraud detection and customer service. They are using it to resolve 15,000 payment disputes lodged by customers every day (reducing call center waits by 40%), and in some cases have reduced the time it takes to approve small business loans to under ten minutes thanks to AI.

jpmorganchase

JPMorganChase

Serving millions of customers in over 100 global markets for more than 200 years, JPMorganChase has long been on the cutting-edge of using tech in its business. Now, the company is using an advanced AI system to automate key aspects of the loan approval process, using machine learning to analyze various data points to enhance the speed and accuracy of credit assessments. Overall, the company is focused on using AI for a variety of efficiencies across the business, with chief executive Jamie Dimon claiming AI tech could cut the working week to only 3 ½ days.

bank of america

Bank of America

One of the world’s leading financial institutions, Bank of America serves everyone from individuals and small businesses to massive corporations and governments with a full range of banking and investment products and services. Recently, it has invested over $3 billion in Generative AI capabilities to enhance operations, and its AI-powered fraud detection system has been able to reduce credit card fraud losses by 45% (which translated to an estimated $500 million saved in 2024 alone).

bmo

BMO

As part of Canada’s tightly controlled banking landscape, BMO is one of the country’s top financial institutions (and the 8th largest bank in North America by assets), offering 13 million customers a variety of products and services. BMO has been utilizing AI to improve report creation times and operational efficiency, recognizing streamlined processes with improvement to revenue and significant cost savings. The use of AI has been able to reduce manual effort on BMO’s equities team from more than four hours a day to less than one, freeing up time for more strategic tasks.

Schroders Capital

Schroders Capital

UK-based Schroders Capital is the private markets investment division of Schroders, with $97 billion in assets under management across private equity, private debt, and more. In 2024 they announced the launch of their Generative AI Investment Analyst (GAiiA) platform, aimed at improving accuracy and speeding up analysis of large volumes of data, and allowing their investment specialists to focus more strategically on delivering value to clients.

capital one

Capital One

Known for revolutionizing the credit card industry with data and tech, Capital One is one of the most recognized banking brands, serving over 100 million customers in a variety of locations. And now, they are also leading in AI adoption among large banks in the Americas and Europe. Their significant investments in AI help them understand customers’ needs and have greatly enhanced their decision-making processes. They are also using AI for real-time fraud prevention and detection, using advanced algorithms to handle evolving fraud threats and reduce false positives.

itau

Itaú Unibanco

As the largest bank in Brazil, Itau Unibanco has been at the forefront of digital transformation in the region, investing heavily in AI to enhance customer service and operational efficiency. In using AI, they have been able to personalize customer interactions, improve credit scoring, and enhance fraud detection and prevention, resulting in robust financial performance and their continued market dominance.

Santander

Santander Bank

One of the largest financial institutions globally, Santander Group features over 170 million customers in Europe and the Americas, 3.5 million shareholders, and over 200,000 employees. Faced with the threat of rising loan defaults, Santander has adopted a more proactive approach with the use of AI-powered predictive analytics. Using AI models that digest a combination of historical data and real-time account monitoring, they are able to identify and intervene earlier, offer tailored advice to customers, and optimize their resource allocation for improved efficiency.

dbs

DBS Bank

Based in Singapore, DBS Bank is a multinational organization, and one of the largest banks in Asia, with over 40,000 employees in 19 markets. Widely recognized for their digital transformation efforts, DBS Bank is using AI for credit risk assessment, personalized marketing, and enhanced customer service experiences through the use of AI-powered virtual assistants. With their AI-driven strategies, they have improved customer satisfaction and increased operational efficiency, contributing to their reputation as a market leader.

cimb

CIMB

Malaysia-headquartered CIMB is actively incorporating AI into its banking services, using advanced analytics and machine learning models for credit scoring, fraud detection, and chatbots for enhanced customer engagement. Thanks to AI, CIMB (the fifth largest banking group in ASEAN with over 26 million customers, and a world leader in Islamic finance) has been able to make more accurate credit assessments and improve fraud detection rates across a variety of business lines.

Whether you are looking for faster, more accurate credit assessment, the ability to better keep up with evolving fraud threats, or the capability to offer more personalized, tailored experiences for your customers, AI is what is going to get you there. The organizations highlighted here are just some of the companies leading the way, demonstrating how leveraging AI decisioning is a necessity for future-proofing your growth. With Provenir’s AI Decisioning Platform, financial services providers can leverage advanced analytics, machine learning, and real-time insights to make faster, more accurate decisions across the entire customer lifecycle. It can be daunting to think about implementing AI, but there are immediate steps you can take now to start taking advantage of the opportunities AI offers.

Ready to shape the future of decisioning with AI?

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Roundtable: Transform Onboarding with Data Agility, Real-Time Decisioning, and Seamless Integration

Live Roundtable: Transform Onboarding with Data Agility, Real-Time Decisioning, and Seamless Integration

The Ritz-Carlton Jakarta, Indonesia

20th February 2025
11:00am – 2:00pm
The Ritz-Carlton Jakarta, Indonesia

Why Attend?

Indonesia’s digital economy is booming, with a projected value of $146 billion in 2025. However, challenges such as fraud, compliance burdens, and inefficient onboarding processes threaten to slow this momentum.

This roundtable will provide insights into:

  • Accelerating onboarding processes while maintaining accuracy and compliance
  • Leveraging data agility to adapt to evolving fraud patterns and customer needs
  • Streamlining workflows with centralized data integration and real-time decisioning

What to Expect:

  • Insights on Onboarding Challenges:

    Learn how to tackle customer drop-offs, fraud threats, and compliance complexities specific to Indonesia.
  • Data Agility in Action:

    Discover how agile data models and flexible data sources enhance decision-making and adaptability.
  • Simplified Integration:

    Understand how a single API streamlines workflows by accessing global and local data sources.
  • Fraud Mitigation Strategies:

    Explore real-time decisioning tools to prevent fraud while maintaining a seamless customer experience.
  • Operational Excellence:

    Gain actionable tips to automate workflows, reduce costs, and scale onboarding processes for growth.
  • Indonesia-Specific Strategies:

    Uncover practical approaches to addressing unique onboarding challenges in Indonesia’s financial landscape.
  • Adapting to Market Demands:

    Learn how data agility can help businesses stay ahead of evolving fraud patterns and market trends.
  • Networking Opportunities:

    Connect with industry leaders and peers to share insights and best practices.
Agenda:
  • 11am – 11:30am

    Arrival and Networking
  • 11:30am – 11:45am

    Opening Remarks – Overview of Indonesia’s onboarding challenges.
  • 11:45am – 12:30pm

    Keynote Presentation – “Transforming Onboarding in Indonesia’s Digital Economy”
  • 12:30pm – 1:30pm

    Interactive Roundtable and Lunch – “Future-Proofing Onboarding with Data Agility”
  • 1:30pm – 2:00pm

    Closing Remarks

Seats are limited for this exclusive roundtable. Don’t miss this opportunity to gain valuable insights and network with industry leaders.

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