Credit Lending

Discover how Union Credit and Experian help credit unions reach younger consumers through personalized digital lending experiences.

In this first episode of Ask the Expert, Experian's Jeff Hops, Senior Director of Data Platform and Product, and Erin Haselkorn, Senior Director of Analyst Relations, explore how broader data and new signals can help lenders better understand today’s consumers, while maintaining responsible decisioning. Lending is changing  Interest rates, regulation, embedded finance and AI are reshaping the lending landscape. Consumer behavior is evolving just as quickly. But the core job hasn’t changed. Lenders are still making decisions about people they don’t fully know, and that makes data more important than ever. "There are periods where nothing changes, and periods where it seems like everything changes. We’re in the latter … but the core premise hasn’t changed. You’re still trying to lend to somebody you don’t know."Jeff Hops, Senior Director of Data Platform and Product To make those decisions with confidence, lenders need a strong foundation of identity, history and reliable signals. In a period of rapid change, the quality and completeness of that data become even more critical. A more complex view of today’s consumer What has changed is the consumer. Traditional credit data is foundational but can be further enhanced with visibility on how people earn, manage and move money. Income may come from multiple sources, and financial activity often spans bank accounts, applications (apps) and digital channels. Cash flow data, for example, can provide a clearer view of what’s actually coming into a consumer’s account, beyond what traditional records may show.These additional signals can help lenders better understand: Income variability across multiple earning sources Current financial behavior through cash flow activity Digital and identity-linked activity across channels These signals don’t replace traditional data; they expand it. The result is a more complete and current view of the consumer. From exploration to real-world application The conversation around broader data signals has moved beyond theory. Lenders are no longer just asking whether these signals are useful. They’re asking where, how and under what governance they can be applied across the lending lifecycle. Lenders are actively researching, testing and implementing new data sources across the lending lifecycle. What was once experimental is now operational. Institutions are progressing through a clear path: Research Understanding available signals and use cases Testing Evaluating performance in controlled environments Implementation Applying insights in production Today, alternative data is being used in areas like analytics, channel scoring and decisioning, often within governed environments that allow for safe testing and validation. AI may accelerate this shift by helping institutions identify patterns at scale, but its value depends on the strength of the underlying data: quality, governance, context and clear business use cases. More signal, more responsibility As data availability expands, lenders have access to more granular insights than ever before. That creates opportunity, but also responsibility. The institutions that lead won’t be the ones that use the most data. They’ll be the ones that know which signals to use, how to validate them and how to apply them in ways that are fair, explainable and aligned to consumer outcomes. “Institutions can unlock more granular and powerful decisions, but they have to do it responsibly.”Erin Haselkorn, Senior Director, Analyst Relations The future of lending will be shaped not just by how much data is available, but by how thoughtfully it’s applied. Keeping the consumer at the center of decisioning is essential to building trust and long-term success. Explore alternative data with us A more complete understanding of today’s consumers starts with better data. We help lenders responsibly incorporate broader data signals and advanced analytics into decisioning strategies, enhancing visibility into today’s consumers while strengthening risk assessment and expanding access to credit. Let’s work together to build more confident, more responsible lending decisions. Learn more Contact us About our experts Jeff Hops Senior Director, Data Platform and Product, Experian Jeff Hops is a Senior Director in Experian’s Financial Services and Data business with over eight years of experience driving innovation in credit and data solutions. He has led product development for Experian’s Credit Report and played a key role in launching Ascend Identity Platform™, a leading identity resolution platform. Erin Haselkorn Senior Director, Analyst Relations, Experian Erin Haselkorn is responsible for analyst relations for Experian. She has developed an understanding of key marketing trends across a broad range of verticals. Her market research around data strategy, AI, fraud, identity and data management, paired with her broad Experian product knowledge, gives her a unique understanding of business automation and data trends. Erin is a frequent spokesperson and guest blogger.

We're excited to announce a new digital onboarding portal for community lenders and credit unions to access Experian’s credit reports.

For many banks, first-party fraud has become a silent drain on profitability. On paper, it often looks like classic credit risk: an account books, goes delinquent, and ultimately charges off. But a growing share of those early charge-offs is driven by something else entirely: customers who never intended to pay you back. That distinction matters. When first-party fraud is misclassified as credit risk, banks risk overstating credit loss, understating fraud exposure, and missing opportunities to intervene earlier.  In our recent Consumer Banker Association (CBA) partner webinar, “Fraud or Financial Distress? How to Differentiate Fraud and Credit Risk Early,” Experian shared new data and analytics to help fraud, risk and collections leaders see this problem more clearly. This post summarizes key themes from the webinar and points you to the full report and on-demand webinar for deeper insight. Why first-party fraud is a growing issue for banks  Banks are seeing rising early losses, especially in digital channels. But those losses do not always behave like traditional credit deterioration. Several trends are contributing:  More accounts opened and funded digitally  Increased use of synthetic or manipulated identities  Economic pressure on consumers and small businesses  More sophisticated misuse of legitimate credentials  When these patterns are lumped into credit risk, banks can experience:  Inflation of credit loss estimates and reserves  Underinvestment in fraud controls and analytics  Blurred visibility into what is truly driving performance   Treating first-party fraud as a distinct problem is the first step toward solving it.  First-payment default: a clearer view of intent  Traditional credit models are designed to answer, “Can this customer pay?” and “How likely are they to roll into delinquency over time?” They are not designed to answer, “Did this customer ever intend to pay?” To help banks get closer to that question, Experian uses first-payment default (FPD) as a key indicator. At a high level, FPD focuses on accounts that become seriously delinquent early in their lifecycle and do not meaningfully recover.  The principle is straightforward:  A legitimate borrower under stress is more likely to miss payments later, with periods of cure and relapse.  A first-party fraudster is more likely to default quickly and never get back on track.  By focusing on FPD patterns, banks can start to separate cases that look like genuine financial distress from those that are more consistent with deceptive intent.  The full report explains how FPD is defined, how it varies by product, and how it can be used to sharpen bank fraud and credit strategies. Beyond FPD: building a richer fraud signal  FPD alone is not enough to classify first-party fraud. In practice, leading banks are layering FPD with behavioral, application and identity indicators to build a more reliable picture. At a conceptual level, these indicators can include:  Early delinquency and straight-roll behavior  Utilization and credit mix that do not align with stated profile  Unusual income, employment, or application characteristics High-risk channels, devices, or locations at application Patterns of disputes or behaviors that suggest abuse  The power comes from how these signals interact, not from any one data point. The report and webinar walk through how these indicators can be combined into fraud analytics and how they perform across key banking products.  Why it matters across fraud, credit and collections Getting first-party fraud right is not just about fraud loss. It impacts multiple parts of the bank. Fraud strategy Well-defined quantification of first-party fraud helps fraud leaders make the case for investments in identity verification, device intelligence, and other early lifecycle controls, especially in digital account opening and digital lending. Credit risk and capital planning When fraud and credit losses are blended, credit models and reserves can be distorted. Separating first-party fraud provides risk teams a cleaner view of true credit performance and supports better capital planning.  Collections and customer treatment Customers in genuine financial distress need different treatment paths than those who never intended to pay. Better segmentation supports more appropriate outreach, hardship programs, and collections strategies, while reserving firmer actions for abuse.  Executive and board reporting Leadership teams increasingly want to understand what portion of loss is being driven by fraud versus credit. Credible data improves discussions around risk appetite and return on capital.  What leading banks are doing differently  In our work with financial institutions, several common practices have emerged among banks that are getting ahead of first-party fraud: 1. Defining first-party fraud explicitly They establish clear definitions and tracking for first-party fraud across key products instead of leaving it buried in credit loss categories.  2. Embedding FPD segmentation into analytics They use FPD-based views in their monitoring and reporting, particularly in the first 6–12 months on book, to better understand early loss behavior.  3. Unifying fraud and credit decisioning Rather than separate strategies that may conflict, they adopt a more unified decisioning framework that considers both fraud and credit risk when approving accounts, setting limits and managing exposure.  4. Leveraging identity and device data They bring in noncredit data — identity risk, device intelligence, application behavior — to complement traditional credit information and strengthen models.  5. Benchmarking performance against peers They use external benchmarks for first-party fraud loss rates and incident sizes to calibrate their risk posture and investment decisions.  The post is meant as a high-level overview. The real value for your teams will be in the detailed benchmarks, charts and examples in the full report and the discussion in the webinar.  If your teams are asking whether rising early losses are driven by fraud or financial distress, this is the moment to look deeper at first-party fraud.  Download the report: “First-party fraud: The most common culprit”  Explore detailed benchmarks for first-party fraud across banking products, see how first-payment default and other indicators are defined and applied, and review examples you can bring into your own internal discussions.  Download the report Watch the on-demand CBA webinar: “Fraud or Financial Distress? How to Differentiate Fraud and Credit Risk Early”  Hear Experian experts walk through real bank scenarios, FPD analytics and practical steps for integrating first-party fraud intelligence into your fraud, credit, and collections strategies.  Watch the webinar First-party fraud is likely already embedded in your early credit losses. With the right analytics and definitions, banks can uncover the true drivers, reduce hidden fraud exposure, and better support customers facing genuine financial hardship.

Since 1996, The Internal Revenue Service (IRS) has issued more than 27 million individual taxpayer identification numbers (ITINs) –⁠ a 9-digit number used by individuals who are required to file or report taxes in the United States but are not eligible to obtain a Social Security number (SSN). Across the country, ITIN holders are actively contributing to their communities and the U.S. financial system. They pay bills, build businesses, contribute billions in taxes and manage their finances responsibly. Yet despite their clear engagement, many remain underrepresented within traditional lending models.  Lenders have a meaningful opportunity to bridge the gap between intention and impact. By rethinking how ITIN consumers are evaluated and supported, financial institutions can: Reduce barriers that have historically held capable borrowers back Build products that reflect real borrower needs Foster trust and strengthen community relationships Drive sustainable, responsible growth Our latest white paper takes a more holistic look at ITIN consumers, highlighting their credit behaviors, performance patterns and long-term growth potential. The findings reveal a population that is not only financially engaged, but also demonstrating signs of ongoing stability and mobility. A few takeaways include: ITIN holders maintain a lower debt-to-income ratio than SSN consumers. ITIN holders exhibit fewer derogatory accounts (180–⁠400 days past due). After 12 months, 76.9% of ITIN holders remained current on trades, a rate 15% higher than SSN consumers. With deeper insight into this segment, lenders can make more informed, inclusive decisions. Read the full white paper to uncover the trends and opportunities shaping the future of ITIN lending. Download white paper

Growth, risk and the rise of "hidden" business accounts As inflation remains elevated and early signs of labor market cooling emerge, the credit card landscape is entering its next phase. Over the past few weeks, policy actions and discussions around potential interest-rate caps have driven increased uncertainty across the credit card industry and broader global markets. Lenders face a careful balancing act: capturing growth opportunities while maintaining disciplined risk oversight. Our second annual State of Credit Cards Report explores the macroeconomic forces influencing the market, key shifts in originations and delinquency trends, and lender mix. New this year, the report also digs into an often‑overlooked segment: business accounts hidden inside consumer credit card portfolios. Additionally, the report offers actionable strategies to help lenders segment risk and drive disciplined growth more effectively. Key insights include: 30+ DPD delinquency rates remained above pre-pandemic levels in 2025, underscoring the need for disciplined asset‑quality monitoring. Fintechs continue to gain ground, posting a 71% YOY increase in account originations.  Business accounts masked in the consumer credit card universe represent roughly 14% of balances and are more than 50% larger than the business card universe — a material segment with distinct risk and profitability dynamics that many lenders are not explicitly managing today. The report also outlines practical strategies to: Identify and segment business behavior within consumer portfolios. Align underwriting and account management with actual usage patterns. Capture targeted growth while protecting long‑term portfolio performance. Ready to dive deeper? Download the full 2026 State of Credit Cards Report to uncover insights that can help your organization manage risk more precisely and grow with confidence. Download report

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