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Learn about some specific Experian solutions that are especially timely for lenders strategizing their response to the COVID Recession.

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Combating fraud requires that you differentiate between first and third party fraud so you can determine the best treatment.

Criminals constantly search and exploit weaknesses. In this digital age, protecting people fuels our commitment to identity protection and fraud prevention.

Implement identity management and account management procedures that are effective and don't affect user experience

Despite rising concerns about identity theft, most Americans aren’t taking basic steps to make it harder for their information to be stolen, according to a survey Experian conducted in August 2017.

To improve the customer experience during the busy holiday shopping season many businesses loosen their fraud criteria.

Experian recently contributed to a TSYS whitepaper focused on the various threats associated with first party fraud. I think the paper does a good job at summarizing the problem, and points out some very important strategies that can be employed to help both prevent first party fraud losses and detect those already in an institution’s active and collections account populations. I’d urge you to have a look at this paper as you begin asking the right questions within your own organization. Watch here The bad news is that first party fraud may currently account for up to 20 percent of credit charge-offs. The good news is that scoring models (using a combination of credit attributes and identity element analysis) targeted at various first party fraud schemes such as Bust Out, Never Pay, and even Synthetic Identity are quite effective in all phases of the customer lifecycle. Appropriate implementation of these models, usually involving coordinated decisioning strategies across both fraud and credit policies, can stem many losses either at account acquisition, or at least early enough in an account management stage, to substantially reduce average fraud balances. The key is to prevent these accounts from ending up in collections queues where they’ll never have any chance of actually being collected upon. A traditional customer information program and identity theft prevention program (associated, for example with the Red Flags Rule) will often fail to identify first party fraud, as these are founded in identity element verification and validation, checks that often ‘pass’ when applied to first party fraudsters.

Learn how to navigate e-commerce merchant challenges in part one of a collaborative two-part series by Experian & Mastercard.

U.S. rental housing market outlook 2026: Analyze elevated mortgage rates, rental supply constraints, affordability pressure, and rising fraud risk. Discover how data analytics, rent reporting, and digital income and employment verification help property managers reduce risk, improve screening accuracy, and make smarter, faster leasing decisions.

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For lenders, the job has never been more complex. You’re expected to protect portfolio performance, meet regulatory expectations, and support growth, all while fraud tactics evolve faster than many traditional risk frameworks were designed to handle. One of the biggest challenges of the job? The line between credit loss and fraud loss is increasingly blurred, and misclassified losses can quietly distort portfolio performance. First-party fraud can look like standard credit risk on the surface and synthetic identity fraud can be difficult to identify, allowing both to quietly slip through decisioning models and distort portfolio performance. That’s where fraud risk scores come into play. Used correctly, they don’t replace credit models; they strengthen them. And for credit risk teams under pressure to approve more genuine customers without absorbing unnecessary losses, understanding how fraud risk scores fit into modern decisioning has become essential. What is a fraud risk score (and what isn’t it) At its core, a fraud risk score is designed to assess the likelihood that an applicant or account is associated with fraudulent behavior, not simply whether they can repay credit. That distinction matters. Traditional credit scores evaluate ability to repay based on historical financial behavior. Fraud risk scores focus on intent and risk signals, patterns that suggest an individual may never intend to repay, may be manipulating identity data, or may be building toward coordinated abuse. Fraud risk scores are not: A replacement for credit scoring A blunt tool designed to decline more applicants A one-time checkpoint limited to account opening Instead, they provide an additional lens that helps credit risk teams separate true credit risk from fraud that merely looks like credit loss. How fraud scores augment decisioning Credit models were never built to detect fraud masquerading as legitimate borrowing behavior. Consider common fraud scenarios facing lenders today: First-payment default, where an applicant appears creditworthy but never intends to make an initial payment Bust-out fraud, where an individual builds a strong credit profile over time, then rapidly maxes out available credit before disappearing Synthetic identity fraud, where criminals blend real and fabricated data to create identities that mature slowly and evade traditional checks In all three cases, the applicant may meet credit criteria at the point of decision. Losses can get classified as charge-offs rather than fraud, masking the real source of portfolio degradation. When credit risk teams rely solely on traditional models, the result is often an overly conservative response: tighter credit standards, fewer approvals, and missed growth opportunities. How fraud risk scores complement traditional credit decisioning Fraud risk scores work best when they augment credit decisioning. For credit risk officers, the value lies in precision. Fraud risk scores help identify applicants or accounts where behavior, velocity or identity signals indicate elevated fraud risk — even when credit attributes appear acceptable. When integrated into decisioning strategies, fraud risk scores can: Improve confidence in approvals by isolating high-risk intent early Enable adverse-actionable decisions for first-party fraud, supporting compliance requirements Reduce misclassified credit losses by clearly identifying fraud-driven outcomes Support differentiated treatment strategies rather than blanket declines The goal isn’t to approve fewer customers. It’s to approve the right customers and to decline or treat risk where intent doesn’t align with genuine borrowing behavior. Fraud risk across the credit lifecycle One of the most important shifts for credit risk teams is recognizing that fraud risk is not static. Fraud risk scores can deliver value at multiple stages of the credit lifecycle: Marketing and prescreen: Fraud risk insights help suppress high-risk identities before offers are extended, ensuring marketing dollars are maximized by targeting low risk consumers. Account opening and originations: Real-time fraud risk scoring supports early detection of first-party fraud, synthetic identities, and identity misuse — before losses are booked. Prequalification and instant decisioning: Fraud risk scores can be used to exclude high-risk applicants from offers while maintaining speed and customer experience. Account management and portfolio review: Fraud risk doesn’t end after onboarding. Scores applied in batch or review processes help identify accounts trending toward bust-out behavior or coordinated abuse, informing credit line management and treatment strategies. This lifecycle approach reflects a broader shift: fraud prevention is no longer confined to front-end controls — it’s a continuous risk discipline. What credit risk officers should look for in a fraud risk score Not all fraud risk scores are created equal. When evaluating or deploying them, credit risk officers should prioritize: Lifecycle availability, so fraud risk can be assessed beyond originations Clear distinction between intent and ability to repay, especially for first-party fraud Adverse-action readiness, including explainability and reason codes Regulatory alignment, supporting fair lending and compliance requirements Seamless integration alongside existing credit and decisioning frameworks Increasingly, credit risk teams also value platforms that reduce operational complexity by enabling fraud and credit risk assessment through unified workflows rather than fragmented point solutions. A more strategic approach to fraud and credit risk The most effective credit risk strategies today are not more conservative, they’re more precise. Fraud risk scores give credit risk officers the ability to stop fraud earlier, classify losses accurately and protect portfolio performance without tightening credit across the board. When fraud and credit insights work together, teams can gain a clearer view of risk, stronger decision confidence and more flexibility to support growth. As fraud tactics continue to evolve, the organizations that succeed will be those that can effectively separate fraud from credit loss. Fraud risk scores are no longer a nice-to-have. They’re a foundational tool for modern credit risk strategies. How credit risk teams can operationalize fraud risk scores For credit risk officers, the challenge isn’t just understanding fraud risk, it’s operationalizing it across the credit lifecycle without adding friction, complexity or compliance risk. Rather than treating fraud as a point-in-time decision, credit risk teams should assess fraud risk where it matters most, from acquisition through portfolio management. Fraud risk scores are designed to complement credit decisioning by focusing on intent to repay, helping teams distinguish fraud-driven behavior from traditional credit risk. Key ways Experian supports credit risk teams include: Lifecycle coverage: Experian award-winning fraud risk scores are available across marketing, originations, prequalification, instant decisioning and ongoing account review. This allows organizations to apply consistent fraud strategies beyond account opening. First-party and synthetic identity fraud intelligence: Experian’s fraud risk scoring addresses first-payment default, bust-out behavior and synthetic identity fraud, which are scenarios that often bypass traditional credit models because they initially appear creditworthy. Converged fraud and credit decisioning: By delivering fraud and credit insights together, often through a single integration, Experian can help reduce operational complexity. Credit risk teams can assess fraud and credit risk simultaneously rather than managing disconnected tools and workflows. Precision over conservatism: The emphasis is not on declining more applicants, but on approving more genuine customers by isolating high-risk intent earlier. This precision helps protect portfolio performance without sacrificing growth. For lenders navigating increasing fraud pressure, Experian’s approach reflects a broader shift in the industry: fraud prevention and credit risk management are no longer separate disciplines; they are most effective when aligned. Explore our fraud solutions Contact us

Financial services leaders are dealing with numerous pressures at the same time. These growing challenges for financial services organizations include sophisticated fraud, rapid Artificial Intelligence (AI) adoption without clear regulatory direction, rising customer expectations and the need for compliant, sustainable growth. Businesses are rethinking how they manage risk, growth and customer trust. These financial industry challenges are no longer confined to internal risk teams. They directly impact long-term customer loyalty. How organizations navigate these challenges will determine how effectively they deliver value to their customers. We’ve outlined the six challenges for financial services oranizations that consistently rank highest among industry leaders today. Challenge 1: Fraud is becoming harder to detect and eroding customer trust 72% of business leaders expect AI-generated fraud and deepfakes to be major challenges by 20261 As fraud tactics evolve quickly, driven in part by AI, customers are being targeted through identity-based attacks from account takeovers to synthetic identities and misuse of personal information. When these threats go undetected, or when legitimate activity is incorrectly flagged, the result isn’t just financial loss. It’s a breakdown of trust. Organizations that want to stay ahead must move beyond isolated fraud controls. By embedding identity management and monitoring into the customer experience, organizations can move from reactive fraud response to proactive identity protection. Identity theft protection and monitoring help organizations turn fraud prevention into a visible, trust-building experience for customers — offering early alerts, guidance, and peace of mind when identity risks arise. Challenge 2: AI decisions must be trusted by customers, not just regulators 76% of businesses say implementing responsible AI is one of their biggest challenges2 As AI becomes more embedded in financial services, it shapes the experiences customers see every day. From credit decisions to eligibility outcomes and personalized offers. While AI can drive faster and more inclusive decisions, it also introduces a new expectation: customers want to understand why a decision was made. Responsible AI is no longer just about regulatory compliance. It’s about delivering outcomes that feel fair, consistent and easy to understand. When decisions appear unclear, confidence erodes. When organizations can clearly explain outcomes, not just internally, they build confidence across regulators, partners and customers. This allows AI to scale responsibly while reinforcing trust in every interaction. Financial wellness tools such as credit scores, reports and education help make AI-driven decisions more transparent, giving customers clarity into outcomes and confidence in how their financial health is assessed. Challenge 3: Digital experiences are failing to deliver clarity and confidence 57% of U.S. consumers remain concerned about conducting activities online3 Customer confidence is affected by day-to-day interactions such as onboarding, payments and issue resolution. Inconsistent decisions, unclear outcomes and friction in digital journeys can quickly erode confidence and increase confusion, disengagement and abandonment. Financial services leaders will need to rebuild and strengthen confidence. Improving key decision points with better data and analytics helps ensure customers receive timely insights, understandable outcomes and meaningful guidance, turning everyday interactions into opportunities to build stronger relationships. By delivering ongoing financial wellness insights and education, organizations can replace confusion with clarity — helping consumers better understand their financial standing and stay engaged over time. Challenge 4: Gen Z continues to raise the bar It's no secret that Gen Z stands out for its strong preference for digital financial services and digital interactions, but Gen Z is also pushing the envelope on financial wellness. 48% of Gen Z report that they do not feel financially secure, indicating strong demand for financial support and tools4 Their expectations for instant decisions, seamless digital experiences, transparency and tools that help them manage their financial lives are quickly becoming the baseline. To meet and exceed these expectations, financial institutions will need to support real-time, data-driven decisioning that adapt to individual needs. Delivering modern, app-like financial experiences, without compromising risk management. Increasingly, organizations are meeting Gen Z expectations by offering financial wellness and protection tools through employee benefits, supporting everyday financial confidence beyond traditional compensation. Challenge 5: Limited data limits meaningful consumer engagement 62 million U.S. consumers are thin-file or credit invisible under traditional credit scoring.5 Growth will always be a priority, but it must be responsible and inclusive. Traditional credit data alone often provides an incomplete picture of consumer financial behavior, limiting visibility and making it harder to confidently expand access. By incorporating alternative and expanded data, organizations can gain a more holistic view of consumers. This broader perspective supports smarter decisions, personalized insights and more inclusive engagement, which enables growth while maintaining compliance and managing risk responsibly. Expanded data supports more personalized financial wellness experiences, enabling organizations to provide relevant insights, responsible access and guidance tailored to individual consumer needs. Challenge 6: Disconnected decisions create inconsistent customer experiences Increasingly, fintech leaders are moving toward unified risk and decisioning strategies to deliver more personalized experiences6 While customers interact with a single institution, decisions are often made across disconnected data sources, systems and teams. These silos create inconsistent experiences, slow responses and operational complexities that customers feel directly through conflicting messages and uneven outcomes. Experian helps organizations break down these silos by unifying data, analytics and decisioning across the enterprise. When data incidents occur, integrated experiences enable faster data breach resolution, helping consumers understand what happened, take action, and recover with confidence. Looking ahead These challenges for financial services organizations are not emerging; they’re already here and reshaping how financial institutions engage with consumers. Leaders who proactively address financial industry challenges by connecting data, analytics, and responsible AI are better positioned to deliver trusted, transparent and meaningful experiences. Learn More References:1. https://www.experian.com/blogs/insights/2025-identity-fraud-report2. https://www.techradar.com/pro/businesses-are-struggling-to-implement-responsible-ai-but-it-could-make-all-the-difference3. https://www.experian.com/blogs/insights/2025-identity-fraud-report4. https://www.deloitte.com/global/en/issues/work/genz-millennial-survey.html5. https://www.experian.com/thought-leadership/business/the-roi-of-alternative-data6. https://us-go.experian.com/2025-state-of-fintech-report?cmpid=IM-2025-state-of-fintech-report-livesocial-share

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