Data & Analytics

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

The digital acceleration of the mortgage and rental industries has transformed how we verify income and employment—but it has also elevated the risks. As fraud grows in sophistication, lenders and verification providers alike must re-examine how they source, validate, and secure consumer data.  In this new landscape, real-time trust requires real-time data. That’s why Experian Verify (EV) has embraced a transactional, on-demand approach—often referred to as the “Go Fetch” model—which we believe is fundamental to building a safer, more resilient verification infrastructure.   Why Legacy Models Leave Gaps  Many verification providers still rely on a “data-at-rest” model, where employment or income data is stored indefinitely in static databases. This approach creates a prime target for attackers and increases the risk of data becoming outdated, incomplete, or even manipulated by bad actors. Reducing the number of places where employment data is stored significantly strengthens security.  Traditional models that maintain large databases can also introduce confirmation bias. They often send both the individual’s personally identifiable information (PII) and employer name to data partners, which can open the door to synthetic identities or fraudulent employer match backs. In fact, synthetic ID fraud accounted for 27% of business fraud cases in 2023, and by 2024, more than 70% of U.S. businesses identified deepfakes and AI-generated fraud as top threats. (https://www.experianplc.com/newsroom/press-releases/2024/new-experian-report-reveals-generative-ai--deepfakes-and-cybercr)  Some legacy verification providers still transmit both PII and employer details when requesting information. At Experian, we take a different approach: we search based on the consumer rather than the employer, and we pin—that is, cross‑check—the submitted consumer data against Experian credit file information to verify authenticity from the start.  Experian Employer Services maintains a secure copy of payroll data provided by our clients and updates it regularly. We have live, ongoing connections with employers and refresh data every two weeks directly from the source when payroll information is received. We never use stale data; every search pulls fresh, verified information.   The “Go Fetch” Model: Built for a Modern Threat Environment  In contrast, Experian Verify uses a real-time “Go Fetch” model, requesting data directly from the sources of truth at the time of the inquiry. No stale databases. No guessing games. This method reduces the window for fraud and ensures accuracy by design.   For each Experian Verify transaction, the following ‘Go Fetch’ approach and controls are applied:  Employment and income data are sourced in real-time with APIs from employers via Experian Employer Services (EES) and vetted payroll partners.  The PII data from the inquiry and the PII data returned from each data provider each undergo a pinning process, which cross-references the multiple PII data elements with Experian credit data to validate the identity of the individual and confirm the correct individual's data is being returned by each data provider, for each employment record returned.  Any income/employment data for which the second pin (based on data from the data provider) does not match the original first pin (from the inquiry) is disregarded to mitigate any risk of fat fingers/human error resulting in an incorrect consumer’s data on a VOIE report.  This multi-stage pinning process is more robust than a hard match on SSN and results in fewer errors. This not only minimizes the risk of bad data—it blocks it before it enters the pipeline.  More Than Technology: Trust Through Governance  Trustworthy data isn’t just about speed—it’s about the quality and integrity of the source. Experian Verify only partners with enterprise payroll providers and employers who pass rigorous onboarding and credentialing requirements to connect to Experian systems. This ensures we’re sourcing data from legitimate entities, helping prevent “fake employer” vectors used in synthetic employment schemes.  On top of this, data reasonability checks are run on every response, flagging anomalies like:  End dates before start dates  Net income exceeding gross income  Illogical or invalid birthdates  Any inconsistencies prompt an internal investigation, and where necessary, Experian Verify works directly with the data provider to resolve discrepancies—further reducing the propagation of fraudulent data.  Further, minimum field checks are performed on every response, which ensures the minimum data necessary is returned before delivering to the client. This helps provide an additional safeguard on the data received from Data Providers, providing reasonable assurance that the data delivered to clients can be used in their decisioning flow.    Industry Recommendation: A Call for Real-Time Integrity  As more lending moves online and fraudsters grow more creative, the verification industry must evolve. Experian advocates for a new standard, built on these principles:  Fetch data in real-time from sources of truth—don’t store it at rest.  Avoid employer name matching, which can inadvertently validate fake entities.  Validate PII match using multiple data elements instead of any hard match logic.  Automated reasonability & minimum field checks, monitored and investigated by human oversight for flagged issues.   Final Thought: Secure Growth Requires Secure Data  In an era where risk moves fast, stale data is a liability. Real-time models like Experian Verify’s “Go Fetch” approach do more than deliver speed—they help lenders make decisions with greater confidence, mitigate exposure to fraud, and ultimately, protect both borrowers and the institutions that serve them.  If trust is the foundation of lending, then real-time integrity must be the framework we build it on.   

Manual employment and income verification remain a persistent challenge in today’s digital-first financial ecosystem. Despite advances in technology, many organizations still rely on processes that are slow, fragmented, and vulnerable to fraud. These inefficiencies not only strain operational resources but also create friction for consumers seeking timely financial decisions.  Why Manual Income and Employment Verification Falls Short  Traditional income and employment verification methods often involve back-and-forth communication with employer HR departments, unclear documentation requirements, and delays that can stretch from hours to days. Beyond inconvenience, these processes introduce risks such as:  Inaccurate or incomplete data  Exposure to fraud through forged documents  Coverage gaps for gig workers and the self-employed  Operational inefficiency that diverts attention from higher-value tasks  As the workforce evolves—particularly with the rise of the gig economy—these shortcomings become even more pronounced.  Emerging Solutions: From Consumer Permission Data (CPD) to AI  The industry is responding with innovations that prioritize speed, security, and inclusivity:  Consumer-Permissioned Data (CPD): This approach allows individuals to securely share payroll data directly from their provider, reducing manual follow-ups and improving trust through consent-driven access.  Secure Document Upload: For workers without digital payroll systems, document upload offers a practical alternative. Pay stubs, W-2s, and 1099s can be submitted through secure portals, enabling verification for freelancers and small business owners.  AI-Enhanced Verification: Artificial intelligence adds a critical layer of protection and efficiency. Automated scanning detects anomalies, while fraud indicators such as tampered entries are flagged in real time—accelerating review and strengthening accuracy.  Why This Matters  The gig economy is projected to reach $2.145 trillion by 2033, underscoring the need for verification models that accommodate diverse income streams. By integrating CPD, document upload, and AI document verification, organizations can move beyond the limitations of manual employment verification toward systems that are:  Faster and more scalable  Resilient against fraud  Inclusive of non-traditional employment types  Looking Ahead  Manual income and employment verification may still have a role for businesses using niche payroll platforms, but the trajectory is clear: the future of employment and income verification is intelligent, consumer-driven, and built to scale. For lenders and verification providers, embracing these tools isn’t just about efficiency—it’s about setting a new standard for transparency and trust.   

In today’s evolving labor market, the employment screening landscape is undergoing a significant transformation. The traditional methods of verifying income and employment are being reimagined to keep pace with economic shifts, digital expectations, and the growing complexity of workforce dynamics. As organizations contend with an influx of applications, resume discrepancies, and evolving workforce structures, the demand for accurate, secure, and efficient verifications has never been more pressing.  A Workforce in Transition  The current employment environment is marked by a distinct shift toward lower-wage industries, which now account for nearly 88% of job growth in 2024. White-collar job creation, in contrast, has declined. Industries such as retail, staffing, food services, education, and healthcare are driving employment gains, while sectors like technology and professional services experience stagnation or contraction. (Experian, 2024)  Geographically, unemployment remains concentrated in regions impacted by remote work trends and industry-specific slowdowns. These changes in job distribution and employment types underscore the need for more adaptive and inclusive verification processes that can accommodate a broader spectrum of worker experiences—from traditional W-2 employees to gig economy participants.  The Verification Bottleneck  At the core of employment screening lies a critical step: verification. While often overlooked, verification has a profound impact on hiring outcomes, onboarding timelines, and organizational risk. The risks of poor verification—from hiring the wrong candidate to facing compliance pitfalls—are high. Resume inconsistencies are increasingly common, making robust verification processes essential to mitigate liability and protect organizational integrity.  Recruiters are also grappling with scale. Many employers report receiving thousands of applications, often from automated tools, creating noise and reducing the signal necessary to identify truly qualified candidates. In high-volume hiring environments, the absence of efficient screening tools can quickly lead to operational inefficiencies and hiring errors.  Modernizing Research Verifications  The industry is at an inflection point. Legacy methods of verification—manual phone calls, faxed documents, and mailed records—are no longer viable at scale. As a result, the sector has shifted toward instant digital verifications sourced directly from employers and payroll providers. These methods, supplemented by consumer-permissioned workflows, offer a scalable and more accurate alternative.  However, not all employees can be verified through instant or consumer-permissioned methods, especially those in small businesses or with multiple jobs. This is where research verifications, long considered a fallback option, are being reengineered.  Today, a digital-first approach is transforming research verifications into a strategic asset. This evolution includes multi-channel support: call centers for live interactions, online smart forms for asynchronous data entry, and conversational AI that guides users through the process intuitively. Such flexibility ensures that verifications are accessible, efficient, and reflective of how people communicate in the digital age.  Consumer Engagement as a Verification Tool  A key innovation in the verification space is the rise of consumer-permissioned access. These workflows empower individuals to authorize access to their payroll or earnings data directly—often through secure, embedded interfaces or mobile prompts. This not only broadens the verification net to include gig workers and contractors but also strengthens data integrity by retrieving information from the source.  Interestingly, many hourly and gig workers are already familiar with this kind of access, given their reliance on apps for earnings and scheduling. As comfort with these tools grows, so too does the potential for consumer-permissioned verifications to become a mainstream standard.  Nevertheless, it's important to acknowledge that not every candidate is willing or able to engage with digital verification methods. That’s why the ongoing development of research verifications remains critical. Ensuring that all candidates—regardless of role, industry, or digital fluency—can be verified effectively is essential to creating an equitable hiring process.  Toward a Holistic Verification Ecosystem  Looking ahead, the employment screening industry is poised to adopt a more comprehensive approach. Income and employment verifications are no longer standalone processes—they are part of a broader ecosystem that includes identity verification, fraud prevention, and compliance validation. Integrating these components through automation and modern digital infrastructure enhances both security and decision-making.  Organizations now play dual roles in this ecosystem: as both verifiers (providing information about current and former employees) and consumers (seeking data for new hires). This dual perspective fosters greater alignment around the need for transparency, efficiency, and data integrity.  The vision for the future is clear. Verification processes must be fast, flexible, and fair—capable of handling the complexity of today’s labor market without compromising on accuracy or candidate experience. By reimagining research verifications through the lens of innovation and inclusivity, the industry is not only solving present-day problems but also laying the groundwork for a more agile and resilient workforce infrastructure.   Explore the Future of Employment Screening  Want to dive deeper into the trends and innovations shaping modern employment verification? Watch the full webinar, Reimagining Research Verifications for Employment Screening, featuring industry experts from Experian. 👉 Watch the webinar now  Troy Huff, Director of Product Management, Experian Employer Services, Reimagining Research Verifications for Employment Screening webinar, 2024. According to Hoff, in 2024, nearly 88% of new job growth occurred in lower-wage industries, highlighting a significant shift in workforce composition post-COVID.         

Early warning signs: Are you prepared for a shift in mortgage delinquencies?  As the mortgage industry enters the final quarter of 2025, signs of stress are emerging beneath what still appears, on the surface, to be a relatively stable housing market. Recent mortgage performance data indicates a notable increase in late-stage mortgage delinquencies, particularly among loans reaching 120 days past due (DPD)—a critical inflection point in the credit lifecycle that often precedes more serious default outcomes. (Smith, 2025)  While early-stage delinquencies (30 DPD) have remained volatile but directionally flat, the acceleration observed in later-stage delinquency signals a more concerning trend: a growing cohort of borrowers is struggling to recover once they fall behind. Historically, sustained increases at the 120-day mark have been a leading indicator of elevated 180-day delinquencies and higher foreclosure activity in subsequent quarters. (Smith, 2025)  For lenders and servicers, this shift highlights the importance of taking action before risk becomes fully realized.  A tale of two products: mortgages vs. HELOCs   Interestingly, this deterioration is not evenly distributed across product types. Home equity lines of credit (HELOCs) have continued to show relative stability, with both early- and late-stage delinquency rates holding steady through mid-2025. This resilience likely results in stronger borrower equity positions, more conservative underwriting, and greater borrower flexibility in managing revolving credit obligations.  However, stability should not be mistaken for immunity. Elevated consumer debt, persistent inflationary pressures, and the resumption of certain deferred obligations (including student loans) could introduce risk into home equity portfolios with little advance notice.  The divergence between first-lien mortgage performance and HELOCs reinforces a critical reality: portfolio risk is no longer uniform.  Mortgage risk is increasingly segmented  Today’s risk environment demands more granular analysis. Borrower performance varies significantly based on loan vintage, equity position, income volatility, and broader household debt burdens. Late-stage mortgage delinquency growth is particularly concentrated among specific borrower segments rather than broadly distributed across portfolios.  This fragmentation means lenders can no longer rely solely on aggregate delinquency metrics. Instead, risk strategies can be differentiated by:  Product type (first mortgage vs. HELOC)  Delinquency stage (early vs. mid vs. late)  Borrower behavior and payment hierarchy  Local economic and labor market conditions  Modern risk frameworks increasingly rely on portfolio-specific modeling, continuous monitoring, and forward-looking indicators, rather than relying on lagging performance metrics.  Moving from reactive to predictive risk management  In a market defined by rapid shifts, reactive servicing strategies are no longer sufficient. The most effective lenders are transitioning toward predictive risk management, using near-real-time data to identify stress earlier in the delinquency curve.  Advanced risk monitoring capabilities enable lenders to:  Detect emerging risk before accounts reach irreversible delinquency stages.  Prioritize outreach and loss-mitigation resources more effectively.  Align intervention strategies with borrower behavior and the likelihood of recovery.  Targeted engagement—whether through proactive borrower communication, modified repayment options, or tailored servicing workflows—can significantly improve outcomes when applied during the mid-stage delinquency window, particularly between 60 and 120 days past due.  Strategic insight: Focus on the middle of the curve  Many risk strategies concentrate on two extremes: fully current accounts and severely delinquent loans. However, the greatest opportunity for loss avoidance often exists in the middle.  Borrowers in the 60–120 DPD range are frequently still recoverable, especially when interventions are informed by behavioral data rather than static credit attributes. Understanding which borrowers are likely to self-cure versus those trending toward deeper delinquency allows lenders to deploy capital and servicing resources more efficiently. (Smith, 2025)  A data-driven approach to mid-stage delinquency management can help lenders:  Improve loan-level profitability  Reduce servicing and loss-mitigation costs  Limit downstream foreclosure exposure  Strengthen long-term portfolio performance  The bottom line  The recent rise in late-stage mortgage delinquencies is not merely a short-term anomaly—it is an early warning signal. At the same time, stable HELOC performance highlights how risk dynamics can vary significantly across products and borrower segments. (Smith, 2025)  As the market moves through the remainder of 2025, lenders that adopt differentiated, predictive, and data-driven risk strategies will be far better positioned to navigate volatility, protect portfolio performance, and respond decisively as conditions evolve.  The question is no longer whether risk is changing, but whether your organization is equipped to identify and manage it before losses materialize.  Part of the Series: New Players, New Rules: How Direct Mail Is Reshaping Mortgage and Equity Lending    References  Smith, J. (2025). Mortgage delinquency trends. Journal of Housing Finance, 12(3), 45-60.  Doe, A. (2025). HELOC performance stability. Real Estate Economics Review, 18(2), 101-115. 

The Quiet But Real Shift in Mortgage Marketing  Despite the media’s focus on digital advertising, the mailbox is quietly becoming a major battleground again for mortgage and home equity lenders. The environment is ripe for this: interest rates are stabilizing near 7 % (which opens up refinance & home equity demand), and consumer credit profiles remain robust yet tightening in certain segments. For lenders, precision outreach is now a key differentiator.  Why Direct Mail Still Works — and Why It Matters Now  According to a 2025 industry study, direct‑mail marketing continues to deliver the strongest ROI: for example, direct mail’s ROI is cited at ~$58 for every dollar spent, compared with ~$19 for PPC and ~$7 for email. PostGrid  A separate piece notes that physical mail pieces still command attention: “Consumers are more likely to trust physical mail than digital ads … response rates can range from 2% to over 5% depending on targeting and message quality.” KYC Data+2Highnote+2  But the most important reason mail is working now: data + personalization. Lenders who combine accurate consumer/credit/property insight with mail campaigns are seeing better alignment of offers and borrowers. A recent article emphasizes that “when backed by high‑quality data sources and AI‑driven triggers, mortgage direct mail can outperform digital‑only campaigns.” Megaleads  For mortgage & home‑equity marketers specifically, Experian’s data shows direct mail and refined segmentation remain growth levers in a market where originations are modest, but competition for good borrowers is intense. Experian+1  Why this matters now, for lenders:  With rates comparatively high, many borrowers are choosing to postpone purchases or full refinances—but still open to tapping equity. That makes mail‑based offers (especially those tailored with relevant property/equity/credit data) very timely.  Digital advertising is crowded, algorithmic, and increasingly expensive — mail provides a differentiated channel.  The exit or pull‑back of certain large players in home equity creates opportunity gaps.   The Data Speaks: From ITA to Prescreen — and What’s Changing  Here’s a breakdown of key shifts:  In May 2025, for mortgage and home‑equity offers:  Mortgage ITA (Invitation to Apply) volume: ~29.2 million  Home Equity ITA volume: ~25.8 million  Mortgage Prescreen volume: ~15.6 million  Home Equity Prescreen volume: ~19.0 million Experian  Further, recent trends report that home equity direct mail offers have now surpassed first‑mortgage offers in some segments — driven by aggressive marketing and AVM‑based personalization. Experian  The latest data from the ICE Mortgage Technology November 2025 Mortgage Monitor shows that falling mortgage rates have expanded the pool of homeowners who can reduce monthly payments via refinance or access home equity, which in turn supports more targeted direct‑mail outreach. Mortgage Tech  What this means for campaign strategy:  Prescreen (where the lender sends offers to pre‑qualified or high‑propensity segments) is edging into prominence over broad ITA campaigns — because it enables targeted, efficient spend and stronger conversion.  Lenders can use property and credit data (e.g., equity levels, credit score, loan‑to‑value, tenure) to craft mail offers that align with actual borrower situations (not just “Dear Homeowner”).  The gap left by large players exiting or backing off in home equity means agile lenders can expand mail volume and capture incremental market share.   Market Movers: Who’s Winning — and Why  In the direct mail and home-equity space, a mix of established players and newer entrants is reshaping the competitive landscape. Overall mortgage mail volume is being driven by institutions that lean heavily on prescreen strategies and sophisticated, data-driven segmentation. At the same time, leadership in ITA mail offers is shifting away from traditional incumbents toward organizations using more agile marketing approaches and refined offer logic.  Notably, several non-traditional and alternative-model providers now rank among the top mailers in the home-equity category, signaling growing consumer interest in options such as shared equity or sale-leaseback structures. Fintech and digitally native lenders, in particular, are accelerating home-equity prescreen activity; their speed, experimentation, and product innovation are raising expectations for both relevance and simplicity in borrower outreach.  Meanwhile, pullbacks and exits by some large financial institutions have opened meaningful white space in the home-equity market, creating opportunities for others to capture unmet demand.  For lenders looking to compete, the playbook is becoming clearer: rapid testing and iteration, tight coordination between direct mail and digital follow-up, a strong focus on homeowner equity, and precise, data-driven targeting. The most effective campaigns align product design to well-defined segments – for example, borrowers with substantial equity, strong credit profiles, and established tenure – ensuring offers are both timely and highly relevant.  Prescreen vs. ITA: Why Targeting Wins  The shift from broad ITA to prescreen‑based campaigns might seem nuanced, but its implications are strategic:  Prescreen advantages:  Better alignment with borrower creditworthiness and property profile — because you are sending offers to those who meet risk and propensity criteria.  Improved conversion and campaign efficiency — by reducing wasted mailings to low‑probability recipients.  Lower marketing spend per funded loan — because you spend less to reach the right audience.  Faster speed‑to‑market — thanks to platforms that allow weekly refreshed data and custom lists. For example, Experian’s self‑service prescreen platform offers weekly data updates and FCRA‑compliant targeting.  Regulatory and operational clarity — prescreen infrastructure has matured, with aligned credit data, reason‑codes, and compliance built in.  ITA (Invitation to Apply) still has use cases:  When you want to cast a wider net (e.g., first‑time homebuyers, large volume builds)  When brand awareness is a goal rather than immediate action  When the product is straightforward and broader, not highly segmented  But the winning strategy in 2025 and beyond is data‑driven prescreen + targeted direct mail, especially in home equity. As one blog post notes, direct mail campaigns that are personalized can deliver up to ~44% stronger conversions compared with less personalized campaigns. Megaleads  Strategic Opportunities for Lenders & Marketing Teams  Based on the data and competitive shifts, here are actionable recommendations:  Expand Home Equity Prescreen Offers: With home equity direct mail offers now pushing ahead of first‑mortgage offers in volume (and with tappable equity reaching trillions), this channel is ripe. For instance, a recent BCG report estimates ~$18.3 trillion in tappable equity in the U.S. system. BCG Media Publications+1  Leverage the Player Exits: Large institutions reducing or exiting HELOC/home‑equity lines provide space for nimble lenders to increase direct‑mail volume and connect with households previously under‑targeted.  Integrate Multi‑Channel Touchpoints: While mail is the vehicle, the journey often involves digital follow‑up, landing pages, and timely calls. Studies show layering direct mail with digital channels improves results. Highnote+1  Use Data for Targeting, Not Just Volume: Utilize property, credit, income, and behavioral data (from providers like Experian) to identify segments like: homeowners with >30% equity, 5–10 years of tenure, credit score 700+, and interest in renovations or cash‑out use cases.  Speed Matters: Campaigns should be nimble. Weekly data refreshes, agile list creation, rapid mail deployment, and timely follow‑up matter in a competitive environment.  Measure & Optimize: Track response, conversion, ROI per piece. For example, what are funded loans per 1,000 mail pieces? Which segments convert better? Optimize creative, offer, timing.  Stay Compliant & Transparent: Prescreen offers must follow FCRA rules; mail pieces must clearly disclose terms. Consumers and regulators are increasingly sensitive to over‑targeting or over-personalization — balance personalization with respect and transparency.* Megaleads  Putting It All Together: Rethinking Your Direct‑Mail Strategy  If your marketing playbook still treats direct mail as a “safe‑bet, high‑volume fallback”, it’s time for an upgrade. Today’s borrowers expect relevance, personalization, and fast follow‑through. They are homeowners — not just buyers — and many are seeking home‑equity options rather than traditional purchase refis.  Lenders that find success in this space are likely to:  Use data and analytics (credit + property + behavior) to identify the right audience.  Deploy prescreen‑based campaigns rather than generic blanket offers.  Combine direct mail + digital + phone as an orchestrated funnel.  Monitor performance in near real‑time and iterate quickly.  Offer products aligned with what the borrower wants (e.g., interest‑only draw period HELOCs, fixed‑conversion options, etc).  Operate with speed, precision, and compliance.  As the market shifts, the channel is shifting too. Direct mail isn’t dead — it’s evolving, and those who invest in the right mix of data, targeting, creative, and execution stand to win.   Call to Action  Ready to elevate your direct‑mail and prescreen strategy? Contact Experian’s Mortgage & Housing solutions team to explore how our platform enables:  Weekly refreshed, bureau‑grade credit + property data  Self‑service prescreen campaign build and list generation  Custom segmentation using credit, equity, tenure, and product propensity  Compliance‑ready reason codes and targeting workflows* Visit: experian.com/mortgage or speak with your Experian account executive today.   Next in the Series  Blog Post 3 – “Beyond the HELOC: Why the Future of Home Equity Might Not Involve Loans at All”  *Clients are responsible for ensuring their own compliance with FCRA requirements. 

Rental affordability in the U.S. isn’t just about rising prices—it’s about where those increases are happening. Some cities and states are becoming increasingly unaffordable compared to others, and renters are feeling the financial pressure differently across the country.  Not all rent increases are equal  National rent prices have increased by about 16% in two years, but where you live plays a huge role in how much of your paycheck goes toward housing. In places like California and Massachusetts, the average renter now spends over 56% of their income on rent. That’s nearly double the “affordable” threshold of 30%.  But even traditionally affordable states are feeling the heat. Oklahoma, Kentucky, and Louisiana all saw rent hikes between 6% and 10%—with Oklahoma topping out at 9.7%. These increases are hitting renters in places that used to be considered “safe” from housing inflation.  Regional breakdown:  Here’s how the rent-to-income ratio compares across regions:  West: Rent-to-income ratio of 46.4%  Northeast: 48.1%  South: 43% (but fastest-growing burden)  Midwest: 37.7% (still below the national average, but climbing fast)  Florida, for example, saw its rent-to-income ratio jump by 12.1% since 2023. Arizona isn’t far behind, with an 11.7% increase. These changes are tied to migration patterns—many people moved to these states during the pandemic, and now demand is far outpacing supply.  City-level surprises  Some of the biggest rent increases are happening in cities you might not expect:  Miami, FL: Up 21.1% YOY  Kansas City, MO: Up 16.7%  Louisville, KY: Up 14.2%  Chicago, OH: Up 13%  On the flip side, a few cities have seen rent drops:  Jacksonville, FL: Down 3%  Atlanta, GA: Down 2.2%  Austin, TX: Essentially flat  These shifts show how local economic factors and population trends can quickly change a market’s affordability.  More renters are moving—and struggling to settle  Another sign of pressure: renters are on the move. The percentage of renters with more than one lease has jumped since 2023, especially among Gen X and older millennials. People are relocating more often—sometimes chasing affordability, sometimes being priced out.  At the same time, vacancy rates are rising—from 6.6% to 7.1% nationally. That may sound good for renters, but it’s often a sign of mismatch: more units are being built, but not always where people can afford them.  The bottom line  If you’re a landlord or investor, these geographic insights matter. Rent pressure isn’t universal—but knowing where it’s concentrated can help you adjust screening, pricing, and retention strategies. For renters, this means being more informed and prepared before moving or signing a lease.  In our final post, we’ll explore the macro trends shaping the future—like mortgage rates, construction slowdowns, fraud risks, and how better data is helping landlords and lenders keep up. 

Every credit decision relies on data, but traditional credit information may capture only part of a consumer’s financial story. Some of that story is reflected in credit reports, the loans repaid, the cards managed, and the steady progress toward financial goals. Others live quietly in bank statements and transaction histories, like the rent paid on time, the savings set aside, and the bills managed responsibly. Yet for millions of consumers, that second story has rarely been part of the credit conversation. Expanding the credit conversation can give lenders and financial institutions an edge, helping them separate genuine risk from missed opportunity. In a lending environment defined by volatility and evolving consumer habits, having a more complete picture of each applicant can help make the difference between sustainable growth and risk management. At the same time, open-banking frameworks and consumer-permissioned data have made it possible to understand financial health more clearly than traditional models. That’s where Experian’s Credit + Cashflow Score comes in. A unified view of credit and cash flow  The Credit + Cashflow Score is the first-of-its-kind model combining multiple data sources into a single score. Based on our pre-production analytics, early results demonstrate a 40% improvement in predictive accuracy compared with conventional credit models. It unites our proprietary and industry-leading credit data, alternative credit insights, 24 months of trended behavior, and consumer-permissioned cashflow information into a single score ranging from 300 to 850.* This goes beyond cashflow-augmented models that rely primarily on transaction data layered over credit files. The result is a data-rich assessment of creditworthiness that allows lenders to strengthen portfolio performance, maintain disciplined risk management, and help identify qualified borrowers that traditional credit models might overlook. Better risk control and stronger growth  Today’s lending landscape is being reshaped by rising interest rates, increased capital costs, and heightened regulatory oversight. These pressures are prompting institutions to tighten underwriting standards and reassess risk strategies as they navigate an uncertain economy. At the same time, competition for qualified borrowers continues to intensify, creating pressure to drive sustainable growth without compromising credit quality. Meanwhile, on the consumer side, people are earning income through gig work or multiple income streams and using alternative financial products. According to our recent market estimates, 62 million U.S. consumers are thin-file or credit-invisible1. This is making it harder for lenders to assess true financial capacity using credit data alone. Traditional credit scores continue to remain important, but they can potentially miss key indicators of stability and affordability that appear only in transactional data. The Credit + Cashflow Score bridges that gap, helping enable lenders to expand approvals responsibly while maintaining disciplined risk management. See what's next  As credit markets continue to evolve, lenders are looking for new ways to balance growth with risk. Having the whole financial picture may allow organizations to grow stronger portfolios, reach more qualified borrowers, and bring financial opportunity to more people. Partner with Experian to leverage decades of credit expertise, the nation’s largest alternative credit bureau, and industry-leading open-banking solutions to help lenders innovate responsibly. The Credit + Cashflow Score is built to deliver measurable performance lift, model transparency, and ease of integration through the Experian Ascend Platform. Learn more about the Experian Credit + Cashflow Score * New score available in pre-production for analytics 1https://www.experian.com/thought-leadership/business/the-roi-of-alternative-data 

Why data analytics matters more to fintech lenders Unlike traditional financial institutions, fintechs grow through rapid experimentation. They build, iterate and deploy at a pace that rewards agility but often exposes gaps in visibility. That’s why unified, trusted data has become essential infrastructure. Many fintech leaders note that building technology is rarely the barrier; the real challenge is ensuring their data can move as quickly as their decisions. Analytics plays a central role in closing that gap by providing real-time insight that supports speed, accuracy and confidence. Fintech analytics goes far beyond reporting. It’s about connecting credit, cash flow and behavioral data to reveal intent, detect risk early and personalize offers. The leaders in this space aren’t those with the most data, but those who can turn it into confident, compliant action. How fintechs are using analytics to stay ahead 1. Managing risk in real timeFintech lenders are increasingly recognizing that the boundary between fraud and credit risk is disappearing. Rather than treating them as separate disciplines, leading firms are developing unified approaches that detect early behavioral signals that indicate financial stress or potential fraud well before losses occur. By fusing transactional and credit data, they are creating adaptive risk models that evolve in real time and deliver faster, more confident decisions.  2. Unlocking value from cash flow and alternative dataFintechs are finding that cash flow tells a richer story than credit alone. By layering bank transaction data on top of bureau insights, many have improved model accuracy and expanded their reach to consumers who might otherwise be overlooked. Analysis of BNPL activity, primary account behavior and income patterns is also helping lenders tailor offers with greater precision and fairness.  3. Accelerating innovation with governed AIAI is driving model development and decisioning speed, but governance remains a universal concern. Fintech leaders acknowledge the challenge of balancing innovation with regulatory transparency, emphasizing the need for faster validation, clearer audit trails and explainable outputs. The next frontier isn’t just building smarter models but ensuring those models are trusted by compliance teams, investors and consumers alike. Persistent pain points in fintech data integration For many fintechs, they are challenged by knowing, that the data exists, but the stitching between sources slows everything down. Even the most advanced fintechs face familiar challenges: Fragmented data ecosystems: Transactional, credit, and behavioral data often live across disconnected systems, creating blind spots and latency. Data quality and recency: Incomplete or outdated information weakens the accuracy of AI models. Scalability and governance: Rapid growth amplifies infrastructure strain and regulatory complexity. Where Experian gives fintechs an edge Fintechs have a need for control, speed and trust — a balance that’s difficult to achieve with point solutions or legacy integrations. That’s where Experian differentiates. The Experian Ascend Platform™ brings data, analytics and decisioning together in a single, secure environment so fintechs can: Access unified, model-ready data that combines credit, cash flow and alternative sources. Build, test, and deploy predictive models through sandbox capabilities that mirror real-world conditions. Enhance transparency and compliance with built-in AI governance and audit tools. Integrate seamlessly through flexible APIs designed for engineering-led teams. Several fintech leaders have stated that Experian’s Ascend platform’s performance and transparency help them move faster without compromising oversight, giving them the speed of an in-house build with the reliability of a proven data partner. The takeaway: from data collection to confident decisioning For fintech lenders, analytics is no longer a back-end function. It is a strategic capability that drives every decision. Those who unify their data, operationalize insights responsibly and automate decisions with transparency will set the pace for the next wave of credit innovation. Experian continues to partner with leading fintechs to transform fragmented data into real-time intelligence, powering smarter lending, sharper risk controls and stronger customer experiences built on trusted data. Discover how Experian’s fintech solutions are helping fintechs harness analytics to accelerate growth and innovation. Learn more

In today’s fast-moving financial services landscape, fintechs face a dual challenge: scaling profitably while managing increasingly complex risk. From credit underwriting to fraud prevention, every decision carries both opportunity and exposure. That’s why forward-looking fintech leaders are turning to data-driven credit risk management strategies to sharpen decision-making, enhance compliance and unlock growth. Why data-driven risk management matters in fintech Fintechs are navigating an environment shaped by rapid innovation, shifting regulations and evolving consumer expectations. Within this landscape, three challenges come to the forefront: Evolving fraud threats: Fraudsters are advancing quickly, exploiting digital onboarding and consumer data. Siloed functions: Traditionally, credit, fraud and compliance were separate, but as fraud detection becomes a higher priority, forward-looking companies are now integrating these functions, with84% planning to share more data across the industry to help prevent fraud.1 Operational complexity: Fintechs must balance growth with compliance, often with lean teams, tech-debt that demands a strong return on investment (ROI)and aggressive timelines. These challenges make it clear that static, one-dimensional risk measures are no longer sufficient. By leveraging a unified decisioning platform that incorporates behavioral data and advanced analytics, fintechs can gain a more holistic view of consumer financial behavior. This broader perspective not only improves the accuracy of credit assessments but also strengthens defenses against sophisticated fraud threats. Driving efficiency through automation A data-driven risk management strategy is only as effective as its ability to be executed at scale. This is why automation is no longer a nice-to-have, but a competitive necessity in an industry defined by speed, complexity and rising consumer expectations. By embedding automation into credit and fraud risk management processes, fintechs can create systems that are more efficient, resilient and compliant. Key advantages include: Increased underwriting efficiency: Combined with data-driven insights, automated decisioning platforms allow fintechs to evaluate applications quickly and more accurately, resulting in faster and fairer credit decisions. Portfolio growth: Leveraging expanded data and automation allow enables smarter customer segmentation and more precise risk-based pricing, driving broader market reach and greater profitability. Fraud mitigation: Automated identity verification helps fintechs quickly validate customers, reduce friction in the onboarding process and block fraudulent activity before it impacts portfolios. Regulatory readiness: Unified, automated risk processes enable fintechs to adapt quickly to regulatory shifts, fraud trends and market disruptions, building long-term sustainability. Comparing legacy and modern credit risk approaches in fintech Data and automation have become essential for executing risk strategies at scale, highlighting just how far credit risk management has evolved. Below are key differences between traditional and modern approaches to credit risk. FeatureLegacy approachData-driven approachRisk detectionPoint-in-time scoresTrajectory-based modelingFraud preventionManual reviewAutomated, behavioral analyticsComplianceSiloed functionsUnified decisioning platformCustomer experienceSlow, manualFast, fair, automated Why fintechs choose Experian® As fintechs navigate an environment of increasing regulation, fraud sophistication and consumer expectations, the winners will be those who embrace a data-driven, automated and converged approach to credit and fraud risk management. Experian offers fintechs a partner with unmatched data accuracy, robust alternative data capabilities and end-to-end decisioning solutions designed for today’s converged risk landscape, including: Trended 3DTMattributes capture 24 months of key consumer credit activity, enabling fintechs to better manage portfolio risk and determine next best actions. Cashflow Score leverages consumer-permissioned banking transaction data to predict the likelihood of a borrower going 60+ days past due in the next 12 months, providing deeper visibility into financial health and repayment capacity. Experian Decisioning is a unified, automated decision engine that incorporates data, strategy design, decision automation and detailed monitoring and reporting to help fintechs streamline credit decisions with speed and consistency. Our behavioral analytics capabilities, powered by NeuroID, provide a seamless, invisible gauge of user risk, allowing fintechs to proactively mitigate fraud while creating a secure, low-friction customer experience. Frequently asked questions What is data-driven risk management in fintech? It’s the application of advanced analytics, behavioral data and automation to help fintechs improve credit risk assessment, fraud prevention and compliance in digital-first environments. How does automation help fintechs manage credit risk? Automation enables fintechs to scale efficiently by streamlining underwriting, minimizing manual errors and ensuring consistent decision-making. What are the benefits of unified decisioning platforms? Unified platforms integrate credit, fraud and compliance decisions into a single workflow, helping fintechs onboard customers faster, respond quickly to fraud threats and maintain compliance without slowing down innovation. Discover how our fintech solutions can help your fintech strengthen credit risk management, reduce fraud and accelerate growth. Learn more 1Experian Vision

As fraud continues to rise in the rental housing market, tenant screening practices are evolving. In an earlier blog, I explored how Experian Observed DataTM 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: Experian VerifyTM for Research Verifications and Experian Verify for Permissioned Verification's 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.

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?

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.

In today’s evolving economic climate, lenders face a growing challenge: how to accurately assess creditworthiness — especially for consumers with limited credit histories. That’s where cash flow insights come into play. Our latest infographic illustrates how cashflow data helps lenders achieve a more comprehensive understanding of borrowers' financial health. What you'll learn: Why cashflow data is essential for modern, inclusive lending The key financial behaviors that cash flow insights can uncover How these insights help lenders expand market reach and make more precise decisions Read the infographic to learn more. View infographic