As fraud continues to rise in the rental housing market, tenant screening practices are evolving. In an earlier blog, I explored how Observed Data can provide early indicators of income and employment consistency, offering screening companies a way to reduce reliance on costly or time-intensive verification methods.  In this follow-up, I explore two additional tools that strengthen the tenant screening process: Research Verifications and AI-powered Document Review. Used together, these solutions enable a layered approach that boosts both efficiency and prevention of fraud. Modernized Research Verifications Manual employment and income and employment checks—once the standard for tenant screening—are time-consuming and often inconsistent. Traditionally, screening companies had to reach out directly to employers and request proof of employment. While still useful, this method puts pressure on internal resources and is not always scalable.  To streamline manual verification, many organizations are partnering with third-party providers, especially those that take a digital-first approach. Outsourcing allows screening companies to delegate outreach, follow-ups, and fraud detection to specialized teams trained in document validation and employer communication. These services deliver the same insights internal teams would gather, while freeing up in-house resources for more strategic initiatives. By leveraging digital tools such as conversational AI, online forms, and automated workflows—combined with human oversight—digital-first vendors offer a more scalable and cost-effective alternative to fully manual processes. This approach not only reduces operational costs but also shortens turnaround times, helping screening companies respond faster without compromising accuracy or fraud resistance. Key advantages:[MJ1]  Reduces the burden on internal staff Ensures consistency and fraud awareness in document review Provides a reliable fallback when other verification tools return limited data This approach is especially valuable when initial data sources yield incomplete results and further confirmation is required. AI-Enhanced Document Upload and Review Another common scenario in tenant screening is the submission of income documents by the applicant, often in the form of paystubs or bank statements. Manual review of these documents is prone to error and increasingly vulnerable to sophisticated forgeries, including those generated by artificial intelligence. AI-powered document analysis tools are now helping screening companies process uploaded documents more securely and efficiently. These platforms typically work by: Allowing applicants to upload documents through a secure portal Using AI to scan for signs of tampering, fabrication, or inconsistency Returning standardized results that are easier to evaluate and compare By automating the detection of anomalies and potential fraud indicators, these tools reduce the workload for staff while improving the reliability of the review process. Benefits include: Faster review and turnaround times Improved fraud detection capabilities Greater consistency across applicants This method is especially useful when traditional employer APIs are unavailable or when screening companies need additional confirmation beyond initial data sources. A Layered Approach to Verification By combining different verification methods, screening companies can design workflows that adapt to a wide range of applicant profiles and risk scenarios. A layered strategy might include: Starting with an inexpensive source of income or employment data to identify likely matches Using AI-based document review when additional validation is needed Turning to manual research verifications only when necessary This cascading process allows screening companies to control costs while maintaining a strong defense against fraud. It also ensures that higher-cost methods are used only when the earlier steps do not provide enough confidence to proceed. Modern Challenges Require Modern Solutions Fraud in tenant screening is increasing rapidly. According to industry surveys, over 93 percent of screening companies have encountered fraud in the past year, and the majority have dealt with falsified income documentation. Traditional approaches, especially manual review, are no longer sufficient on their own. By rethinking verification strategies and incorporating modern tools like outsourced research verification and AI-enhanced document review, screening companies can reduce risk, improve efficiency, and better prioritize their resources. Learn More For organizations interested in implementing these types of verification tools, several providers—including Experian—offer services designed to support this layered approach. These solutions can help screening companies strike the right balance between cost, compliance, and fraud resistance. To learn more, visit experian.com/verify.

In an ever-evolving automotive landscape, where shifting consumer behavior meets fluctuating market dynamics, Experian’s State of the Automotive Finance Market Report: Q2 2025 delivers key insights into how both consumers and professionals are adapting to the changes. This quarter’s report revealed a sharp increase in vehicle refinancing—up nearly 70% from Q2 2024—as consumers capitalized on the more stable rate environment. In fact, after refinancing, the average interest rate went from 10.45% to 8.45%. That shift resulted in their monthly payment dropping by an average of $71. Interestingly, credit unions played a significant role in the refinance surge, increasing their market share from 63.22% last year to 68.33% this quarter, and borrowers who refinanced through credit unions saw their monthly payments decrease by $87 on average. Banks saw a slight dip in their share of the refinancing market year-over-year, going from 22.71% to 21.45%, and borrowers who refinanced through them saved an average of $46 a month. New leaders emerge as the lender market share continues to evolve Taking a deeper dive into the automotive finance market share, banks reclaimed their leading position for total vehicle financing, rising to 27.50% in Q2 2025, from 24.50% in Q2 2024. Meanwhile, captives declined from 30.17% to 26.63% year-over-year, and credit unions slightly increased from 20.35% to 21.04% during the same period. For new vehicles, captives continued to lead at 52.39% this quarter, though it was a drop from 60.74% last year. On the other hand, banks grew from 21.12% to 25.91% and credit unions went from 9.99% to 12.24% in the same time frame. On the used side, banks edged ahead, increasing their share to 28.59% in Q2 2025, from 26.80% last year. Credit unions saw slight growth from 27.59% to 27.63%, while captives declined from 7.83% to 6.40% year-over-year. As affordability remains a key priority, consumers seem to be exploring financing options that offer more favorable terms. While Experian Automotive’s report continues to illustrate the evolving dynamics, these data-driven insights can empower both consumers and industry professionals to make smarter financial decisions. To learn more about automotive finance trends, view the full State of the Automotive Finance Market Report: Q2 2025 presentation on demand.

Income and employment verification fraud is surging in the tenant screening industry, putting traditional verification methods under intense pressure. As economic uncertainty grows and document forgery becomes more sophisticated, it's clear that legacy processes are no longer sufficient. Recent findings highlight the urgency for change. According to the NMHC Pulse Survey, 93.3% of property managers reported encountering fraud in the past year, with 84.3% citing falsified paystubs and fake employment references as the most common tactics. As AI-generated forgeries become increasingly convincing and accessible, relying solely on manual review is proving inadequate. A Shift in Strategy: Toward Smarter Income and Employment Verification Historically, tenant screeners have relied on methods such as manual document review, direct employer contact, payroll APIs, and verification of assets (VOA). While these remain important, they are no longer capable of keeping pace with today’s verification challenges. In response, many screening companies are exploring new income verification tools that offer improved fraud prevention, lower operational costs, and faster turnaround. These innovations include layered approaches that combine observed data, permissioned uploads, and automated fraud detection technologies. Introducing Observed Data in Tenant Screening One emerging solution in the fight against rental application fraud is the use of observed data during tenant screening. This method uses [KA1] collectively sourced insights to assess whether an applicant’s income and employment claims are likely to be accurate. Observed data is drawn from a consortium of financial institutions, lenders, and dealerships. It includes a confidence grade based on actual financial behavior, such as account activity and application history, which are then compiled and analyzed to form a current view of income and employment patterns. [CC2]  These insights are drawn from the latest self-reported data submitted by consumers through loan applications, providing screening companies with a dynamic, data-driven benchmark for verification. Although this method is not FCRA-compliant and cannot be used to approve or deny applications, it is highly effective as an early step in the screening process. A confidence score is often included to help screeners assess how closely an applicant’s stated information aligns with observed trends and can help screening companies to better assess their prioritization queue to determine if more data points are needed. Why Observed Data Matters To combat fraud without driving up costs or slowing down the tenant screening process, screening companies need reliable, efficient tools. Observed data supports this need by offering a faster, more scalable approach to assessing risk. Key benefits include: Early detection of discrepancies in reported income or employment The ability to prioritize high-risk applications for further review A more cost-effective alternative before committing to premium verification services For instance, if an applicant has a strong credit report and clean background check, and observed data supports their stated income, further verification may be unnecessary. If inconsistencies are flagged, screening companies can escalate to tools such as AI document analysis or direct outreach. Fraud Prevention Through Smarter Workflows The use of observed data also aligns with a broader shift toward AI document fraud detection and layered verification strategies. Instead of applying the same tools to every application, screening companies can now implement decision trees that use lower-cost tools first, escalating only when risk or uncertainty increases. This adaptive approach is particularly relevant as screener companies strive to improve accuracy and efficiency at scale. By deploying observed data as a first step, tenant screening professionals can better allocate resources while remaining vigilant against fraud Future Proofing Verificaiton As the income and employment verification landscape evolves, screening companies must move beyond legacy methods and adopt tools that are responsive to today’s challenges. Observed data provides a scalable, low friction starting point that supports smarter decision-making and better fraud detection. Coming to our next blog: We will explore how manual research verifications and AI-powered document upload solutions enhance the effectiveness of modern income verification tools, creating a more resilient and adaptable tenant screening process.  

In today’s digital lending landscape, fraudsters are more sophisticated, coordinated, and relentless than ever. For companies like Terrace Finance — a specialty finance platform connecting over 5,000 merchants, consumers, and lenders — effectively staying ahead of these threats is a major competitive advantage. That is why Terrace Finance partnered with NeuroID, a part of Experian, to bring behavioral analytics into their fraud prevention strategy. It has given Terrace’s team a proactive, real-time defense that is transforming how they detect and respond to attacks — potentially stopping fraud before it ever reaches their lending partners. The challenge: Sophisticated fraud in a high-stakes ecosystem Terrace Finance operates in a complex environment, offering financing across a wide range of industries and credit profiles. With applications flowing in from countless channels, the risk of fraud is ever-present. A single fraudulent transaction can damage lender relationships or even cut off financing access for entire merchant groups. According to CEO Andy Hopkins, protecting its partners is a top priority for Terrace:“We know that each individual fraud attack can be very costly for merchants, and some merchants will get shut off from their lending partners because fraud was let through ... It is necessary in this business to keep fraud at a tolerable level, with the ultimate goal to eliminate it entirely.” Prior to NeuroID, Terrace was confident in its ability to validate submitted data. But with concerns about GenAI-powered fraud growing, including the threat of next-generation fraud bots, Terrace sought out a solution that could provide visibility into how data was being entered and detect risk before applications are submitted. The solution: Behavioral analytics from NeuroID via Experian After integrating NeuroID through Experian’s orchestration platform, Terrace gained access to real-time behavioral signals that detected fraud before data was even submitted. Just hours after Terrace turned NeuroID on, behavioral signals revealed a major attack in progress — NeuroID enabled Terrace to respond faster than ever and reduce risk immediately. “Going live was my most nerve-wracking day. We knew we would see data that we have never seen before and sure enough, we were right in the middle of an attack,” Hopkins said. “We thought the fraud was a little more generic and a little more spread out. What we found was much more coordinated activities, but this also meant we could bring more surgical solutions to the problem instead of broad strokes.” Terrace has seen significant results with NeuroID in place, including: Together, NeuroID and Experian enabled Terrace to build a layered, intelligent fraud defense that adapts in real time. A partnership built on innovation Terrace Finance’s success is a testament to what is  possible when forward-thinking companies partner with innovative technology providers. With Experian’s fraud analytics and NeuroID’s behavioral intelligence, they have built a fraud prevention strategy that is proactive, precise, and scalable. And they are not stopping there. Terrace is now working with Experian to explore additional tools and insights across the ecosystem, continuing to refine their fraud defenses and deliver the best possible experience for genuine users. “We use the analogy of a stream,” Hopkins explained. “Rocks block the flow, and as you remove them, it flows better. But that means smaller rocks are now exposed. We can repeat these improvements until the water flows smoothly.” Learn more about Terrace Finance and NeuroID Want more of the story? Read the full case study to explore how behavioral analytics provided immediate and long-term value to Terrace Finance’s innovative fraud prevention strategy. Read case study

Executive Summary The July 2025 housing market reveals a landscape of shifting consumer behaviors, evolving lender strategies, and continued strength in borrower performance—especially within home equity. Origination volumes have dipped slightly, but direct marketing, particularly through Invitation to Apply (ITA) campaigns, is accelerating. As key players exit the space, gaps are opening across both marketing and origination, creating clear opportunities for agile institutions. This phase signals both caution and potential. The winners will be those who refine their marketing, sharpen segmentation, and deploy smarter risk monitoring in real time. TL;DR Risk Profile: Mortgage and HELOC delinquencies remain low. Slight increases in 90+ DPD are not yet cause for concern. Mortgage Originations: Modestly down, but marketing remains aggressive. Invitation to Apply (ITA) volumes outpacing prescreen. Home Equity Originations: Stable originations, competitive marketing volumes. ITA volumes outpacing prescreen similar to mortgage. Opportunity: Targeted direct mail and refined segmentation are growth levers in both mortgage and home equity. Risk Environment: Resilient Yet Watchful Experian’s July data shows both mortgage and home equity delinquencies hovering at historically low levels. Early-stage delinquencies dropped in June, while late-stage (90+ days past due) nudged upward—still below thresholds signaling broader distress. HELOCs followed a similar path. Early-stage movement was slightly elevated but well within acceptable ranges, reinforcing borrower stability even in a high-rate, high-tariff environment. Takeaway: Creditworthiness remains strong, especially for real estate–backed portfolios, but sustained monitoring of 90+ DPD trends is smart risk management. Home Equity: Volume Holds, Competition Resets Home equity lending is undergoing a major strategic reshuffle. With a key market participant exiting the space, a significant share of both marketing and originations is now in flux. What’s happening: Direct mail volumes in home equity nearly match those in first mortgages—despite the latter holding larger balances. ITA volumes alone topped 8 million in May 2025. Total tappable home equity stands near $29.5 trillion, underscoring a massive opportunity.(source: Experian property data.) Lenders willing to recalibrate quickly can unlock high-intent borrowers—especially as more consumers seek cash flow flexibility without refinancing into higher rates.   Direct Mail and Offer Channel Trends The continued surge in ITA campaigns illustrates a broader market pivot. Lenders are favoring: Controlled timing and messaging Multichannel alignment Improved compliance flexibility May 2025 Mail Volumes: Offer Type Mortgage Home Equity ITA 29.2M 25.8M Prescreen 15.6M 19.0M Strategic Insights for Lenders 1. Invest in Personalized Offers Drive better response rates with prescreen or ITA campaigns. Leverage data assets like Experian ConsumerView for ITA’s for robust behavioral and lifestyle segmentation. For prescreen, achieve pinpoint-personalization with offers built on propensity models, property attributes, and credit characteristics. 2. Seize the Home Equity Opening Use urgency-based messaging to attract consumers searching for fast access to equity—without the complexity of a full refi. Additionally, as mentioned above, leverage propensity, credit, and property (i.e. equity) data to optimize your marketing spend. 3. Strengthen Risk Controls Even in a low-delinquency environment, vigilance matters. Account Review campaigns, custom scorecards, and real-time monitoring help stay ahead of rising 90+ DPD segments. 4. Benchmark Smarter Competitive intelligence is key. Evaluate offer volumes, audience segmentation, and marketing timing to refine your next campaign. FAQ Q: What does the exit of a major home equity player mean? A: It leaves a significant gap in both marketing activity and borrower targeting. Lenders able to act quickly can capture outsized share in a category rich with equity and demand. Q: How should lenders respond to the evolving risk profile? A: Continue to monitor performance closely, but focus on forward-looking indicators like trended data, income verification, and alternative credit signals. Conclusion The housing market in July 2025 presents a clear message: the fundamentals are sound, but the strategies are shifting. Those ready to optimize outreach by making smarter use of data will seize a disproportionate share in both mortgage and home equity. Want to stay ahead? Connect with Experian Mortgage Solutions for the insights, tools, and strategies to grow in today’s evolving lending environment.  

In the latest episode of “The Chrisman Commentary” podcast, Experian's Alison Bird, Product Owner, and Joy Mina, Director, Product Commercialization, discuss how streamlining the verification process helps mortgage lenders serve more borrowers without sacrificing accuracy. Listen to the full episode for all the details and tune in to the previous episode to learn why price transparency is important in the verification process. Listen now

In today’s digital payments landscape, fraudsters are constantly developing new tactics to exploit vulnerabilities. One of the most common credit card schemes financial institutions and merchants face are BIN attacks. But what exactly is a BIN attack, and how does BIN attack fraud work? What is a BIN attack? BIN attacks, a type of card not present fraud, target the Bank Identification Number (BIN) ­— the first six to eight digits of a credit or debit card number that identify the issuing financial institution. Fraudsters use these digits to systematically generate and test potential card number combinations. The goal of a BIN attack is to discover valid card numbers that can be used for fraudulent transactions. Because BINs are publicly available and consistent across card issuers, they provide a predictable framework for attackers. How does it differ from other types of payment fraud? Payment fraud takes many forms, but BIN attacks stand apart because of their scale and automation. Card testing fraud vs. BIN attacks: Both involve criminals running authorization attempts to identify valid card details. However, card testing typically uses data from a single stolen card, while BIN attacks systematically generate thousands of possible card numbers from a known BIN range. Account takeover fraud vs. BIN attacks: In an account takeover, fraudsters gain access to a customer’s existing account, often through phishing or stolen login credentials. BIN attacks don’t require account access — instead, they exploit card number patterns to guess valid accounts. What are the consequences of a BIN attack? BIN attacks don’t just result in stolen card numbers — they create wide-ranging business risks that can impact operations, revenue and customer trust. For financial institutions and merchants, the ripple effects can be significant: High transaction volumes: BIN attacks are carried out using automated scripts or bots that fire off thousands of transaction attempts per minute. This traffic can overwhelm payment systems, slow down processing and disrupt the checkout experience for legitimate customers. Increased chargebacks: Once fraudsters identify valid cards, they make unauthorized purchases that often result in chargebacks. Both merchants and issuers absorb these losses — merchants lose revenue, while issuers reimburse cardholders. Network and processing costs: Every transaction attempt — even those declined during a BIN attack — still incurs network and processing fees. Merchants and issuers can end up paying for thousands of authorization requests, draining resources. Reputational damage: Today’s consumers expect seamless and secure payments. If they experience frequent declines, blocked cards or fraudulent activity, their trust in the institution or merchant erodes. How to protect against BIN attack fraud Mitigating BIN attacks requires a proactive, layered defense strategy. Financial institutions and merchants should consider: Advanced fraud detection and analytics: BIN attacks generate massive volumes of fraudulent traffic. By leveraging AI-driven analytics and machine learning, institutions and merchants can monitor for unusual transaction patterns, velocity spikes and bot-driven activity. Identity and device intelligence: Fraudsters often hide behind bots, stolen IP addresses and compromised devices. With identity verification and device intelligence solutions, merchants and institutions can better determine whether a transaction is coming from a legitimate customer or a fraudster testing card details. Multi-factor authentication (MFA): BIN attacks succeed on speed and automation, firing off thousands of transactions. MFA can help disrupt this process by requiring additional proof of identity from the customer, such as facial recognition or one-time passcodes. Credit card authentication: BIN attacks exploit the gap between payment credentials and the identity of the person using them. A solution like Experian LinkTM seamlessly connects the payment instrument with the digital identity presented for payment, helping merchants to reduce false declines, fraud and operating expenses. Build a stronger defense against BIN attacks BIN attacks are a growing threat in today’s digital payments ecosystem. But with the right safeguards in place, organizations can stay ahead. Learn how Experian can help you strengthen your fraud defenses to reduce losses and protect customer trust. Learn more

Mid-sized banks are large enough to pursue ambitious growth strategies, like expanding loan portfolios or entering new markets, but not so large that they can withstand major credit losses without consequence. So how do lending organizations manage their credit risk strategies to grow without taking on more risk than they can handle?

This is the first in a series that will highlight auto marketing trends to help you drive more effective marketing campaigns. With the second half of the year underway, one theme continues to prevail in conversations among auto marketers: measurement. With more focus to prove ROI, optimize campaigns in real time, and understand the full consumer journey, marketers are doubling down on attribution while sharpening their analytics tools.    One of the most widely adopted platforms in this space is Google Analytics 4 (GA4). Since its full rollout, GA4 has replaced Universal Analytics for digital measurement. Its event-based model offers new ways to track behavior and measure performance, especially in complex, multi-touch journeys like auto shopping.  Let’s break down four quick tips to help you unlock the full potential of GA4—plus a quick summary to dial in this type of measurement.  GA4 Tune-Up Tips for Smarter Auto Marketing: 1. Event-Based Tracking Offers Full-Funnel Visibility  Unlike Universal Analytics, GA4 focuses on events (rather than sessions) by tracking actions such as scroll depth, video views, CTA clicks, and more, giving you detailed insights into how users engage with your site. It’s especially helpful for A/B testing and understanding micro-conversions across the buyer’s online journey.  2. Use Clean, Consistent UTM Parameters  UTM parameters tell GA4 “where” your traffic comes from. However, if they’re inconsistent or overly complex, your reports will be too. Use a simple naming convention for channels and campaigns so you can easily see what’s working.  See example chart below:  3. Set Up GTM to Capture the Key Events  Google Tag Manager (GTM) tells GA4 “what” happens once a consumer arrives to your website.  Ensure GTM is set up to record important on-site actions—including page views, form submissions, phone clicks, or test drive bookings.  Start with GTM testing by using Preview Mode and Tag Assistant.   4. Extend Your Data Retention Window  By default, GA4 only stores user-level data for 2 months. If you want to track long buying cycles or compare year-over-year trends, go into your GA4 settings and extend the retention period to 14 months.  GA4 Tune-Up Tips Summary:  GA4 is Google’s enhanced analytics platform, built to give marketers a more flexible, cross-platform view of user behavior by using an event-based model designed for the future of measurement.  With industries like automotive — offline interactions, third-party sites, and long purchase paths are common. GA4 often needs to be supplemented with additional tools or CRM integration to capture the full buying journey. According to Neilsen, measurement of ROI across channels is more important than ever and marketers have an opportunity to fine tune it.  Discover how Experian Automotive can help measure your marketing performance with solutions like OmniImpact for Automotive™ and an Auto Response Analysis.  Next Up...  From personalized follow-ups to omnichannel messaging, forward-thinking retailers are evolving how they communicate with today’s car shoppers, and measurement is just one piece of the puzzle. In our series, we’ll explore another focus for Auto Marketers in the latter half of 2025: Messaging and Communication with your consumers.

Nearly 19 million U.S. households remain unbanked or credit-invisible,1 not due to a lack of financial responsibility but because traditional credit models alone may not include key financial behaviors. These individuals often save, earn and budget wisely, yet conventional scoring systems do not recognize them. We’ve recently partnered with Plaid, the trusted leader in open finance, to change that. Together, we’re putting cash flow underwriting front and center — giving lenders access to real-time, consumer-permissioned financial data that paints a fuller, more accurate picture of creditworthiness. Why cash flow data matters now  In the U.S., many consumers with limited credit histories want to build their profiles but don’t know how. Cash flow underwriting bridges this gap. Cash flow insights reveal real-world financial activity — like income patterns, spending habits and account balances — in real time. This empowers lenders to make smarter, faster and more inclusive credit decisions, while helping consumers gain access to the financial services they deserve. What cash flow insights deliver By incorporating cashflow data into your decisioning strategy, you can: See beyond the score with a richer view of a consumer’s financial health. Accelerate approvals with more accurate and timely insights. Expand access to credit while strengthening portfolio diversity and reducing risk. Download our infographic to see how cash flow underwriting is reshaping lending — and how you can lead the change. Download infographic 1Mullen, C. (2024, November 13). Underbanked US population grows to 14.2%, FDIC finds. Banking Dive. 

Credit decisioning has traditionally relied on static data like credit bureau scores, income statements, and past repayment history. As financial behavior becomes more dynamic and consumer expectations shift toward instant decisions, real-time data is emerging as a powerful tool in reshaping how lenders assess risk.

Lending fraud – what is it? Lending fraud is a deceptive practice in which individuals or entities intentionally provide false or misleading information during the loan application process to secure credit or financial gain. This can include using fake identities, inflating income, forging documentation, or applying for loans without the intention of repayment.   The consequences are significant: lenders suffer financial losses, consumers experience identity theft or damaged credit scores, and the economic system bears increased risk and regulatory scrutiny. Loan fraud is a growing concern across consumer, commercial, and mortgage lending sectors, affecting institutions of all sizes. How do I safeguard my organization from loan fraud?    Preventing lending fraud is a complex, ongoing challenge that requires a multi-layered and holistic approach. As fraud tactics become more sophisticated, especially with the rise of generative AI and digital lending channels, financial institutions must continually evolve their defenses.  Strong identity verification is the first line of defense. Lenders should implement advanced authentication tools beyond basic KYC (Know Your Customer) checks. This includes biometric verification, document verification, and device intelligence —technologies that assess the authenticity of the user and the device used during the application process. These tools can help detect synthetic identities — false identities created using a blend of real and fabricated information — increasingly used in loan fraud schemes.  Another crucial strategy is real-time data analytics and behavioral monitoring. Lenders can quickly identify anomalies that may indicate fraudulent activity by analyzing applicant behavior, credit history, device usage patterns, and geolocation data in real time. For example, if an applicant submits multiple loan applications from different IP addresses in a short time frame, that could raise a red flag for potential lending fraud.  Employee training and awareness are also essential. Frontline staff must be equipped to identify warning signs, such as inconsistencies in application documents or rushed, high-pressure loan requests. Regular fraud prevention training helps employees stay alert and aligned with the organization’s risk management protocols.  57% of financial institutions reported direct fraud losses exceeding $500,000 in the past year, with 25% exceeding $1 million.1 Consumers reported losing more than $12.5 billion to fraud in 2024, which represents a 25% increase over the prior year.2 In addition, robust internal controls and auditing mechanisms are critical in prevention. Organizations should regularly audit loan origination processes and investigate unusual approval patterns to detect insider fraud or systemic vulnerabilities.  Finally, consumer education is a vital, often overlooked, aspect of combating loan fraud. Lenders should provide resources to help customers understand the risks of identity theft, encourage them to monitor their credit reports regularly, and empower them to report any suspicious activity. A well-informed customer base can be a valuable early warning system for fraud.  With digital lending becoming the norm, preventing lending fraud means staying ahead of increasingly tech-savvy fraudsters. Leveraging data, technology, and education together builds a stronger, more resilient fraud defense framework.  Lending fraud + Experian – How we can help  With access to the industry’s most advanced fraud detection and identity verification tools, partnering with us gives you a potent edge in combating lending fraud. As a global leader in data, analytics, and technology, our comprehensive and accurate sets of consumer information enable you to spot risks that might be invisible through conventional means. Our approach combines rich data insights with powerful machine learning algorithms, delivering fraud prevention tools that are intelligent, scalable, and highly adaptive.  Our fraud detection technologies are designed to protect every stage of the lending lifecycle. From real-time identity verification and multi-factor authentication solutions to behavioral biometrics and device intelligence, so you can detect synthetic identities, manipulated applications, and other forms of loan fraud before they lead to financial loss.  In an era where trust is currency, partnering with us doesn’t just help protect against lending fraud — it enhances your reputation as a secure, responsible lender. You gain the confidence of your customers by providing safe, streamlined lending experiences while meeting compliance requirements and reducing operational risk. With us, you’re not just reacting to fraud—you’re anticipating it, preventing it, and confidently growing your business.  Learn more 1State of Fraud Benchmark Report. Alloy. (2024). 2New FTC Data Show a Big Jump in Reported Losses to Fraud to $12.5 Billion in 2024. Federal Trade Commission. (2025, March 10). 

In 2025, home equity lending has re-emerged as a central theme in the American financial landscape—an evolution not driven by hype, but by hard data, economic realities, and consumer behavior. As homeowners grapple with inflation, rising consumer debt, and a persistent affordability crisis in housing, the home equity line of credit (HELOC) is gaining traction as a practical, flexible, and often misunderstood financial solution.

Data breaches continue to be a reality for organizations across industries, and the complexity of responding to them is only increasing. From AI-driven fraud to third-party exposures, the risk landscape is shifting fast. Having a modern and tested response plan is essential to containing the damage, protecting your customers, and preserving your organization’s reputation when a breach occurs. Experian’s eleventh annual Data Breach Response Guide draws on decades of breach support experience. It offers practical strategies and insights for navigating the moments that matter most: the first hours after a breach and the days that follow. The 2025–2026 guide explores: How AI is shaping new breach and fraud patterns Where organizations are most vulnerable, including third-party and supply chain weak points Consumer expectations and how they influence crisis response How prepared organizations are reducing impact and protecting trust What is required to build a modern, effective breach response plan Organizations with a tested plan can potentially reduce the cost, impact, and long-term consequences of a breach. From real-world case insights to crisis communication templates, this guide is designed to help teams act quickly and confidently. Download the 2025–2026 Data Breach Response Guide to learn how you can strengthen your breach preparedness, reduce risk exposure, and build resilience against the next wave of cybersecurity threats. Download guide

Experian is proud to be a Thought Leadership Sponsor at this year’s Federal Identity Forum & Expo (FedID)! We’re bringing the latest innovations in fraud prevention, identity verification, and behavioral analytics – all designed to help government agencies protect access, ensure trust, and stay ahead of evolving threats.