Utilities are managing elevated arrears, expanding digital service channels and shifting grid demand patterns at the same time. These developments are appearing at key points, including service starts, billing and collections. Energy and utilities industry trends for 2026 reflect how these dynamics are surfacing across the customer lifecycle and influencing broader planning decisions.  Energy and utilities trends shaping the industry The state of energy and utilities 2026 reflects a sector adapting to financial exposure, fraud risk and demand variability across both regulated and deregulated markets. Rising arrearagesArrearage levels across the utilities sector are estimated at approximately $23 billion. Economic uncertainty may be contributing to a rise in arrearages, often reflected in delayed payments, extended repayment plans or variability in monthly collections. Digital expansion introduces new risk considerationsAs utilities expand digital service channels and self-service tools, identity-based fraud risk may appear during digital service starts and account changes, particularly as more interactions shift online. Fraud behaviors are becoming more sophisticatedMore complex fraud patterns, including synthetic identities, name game fraud and prior bad debt, may span multiple points of the customer journey, making risk more difficult to detect. Grid demand uncertaintyIn certain regions, data center expansion may influence load forecasting and long-term infrastructure planning timelines. Data centers consumed approximately 4.4% of U.S. electricity in 2023 and are projected to account for between 6.7% and 12% by 2028, reflecting the potential scale of demand shifts utilities may be evaluating. What these trends signal for utility planning Together, these energy and utilities industry trends 2026 highlight where risk could first emerge. When risk indicators appear during service start, screening before service starts may help reduce downstream exposure rather than relying only on collections-based controls. As more interactions shift online, identity risk may be harder to identify without stronger verification. When fraud spans from service start through collections, visibility across systems becomes more important. As grid demand grows, planning for reliability may require adjustments to how forecasting and infrastructure decisions are informed. Enabling data-driven utility decisions To navigate these energy sector trends, utilities may benefit from a more connected view of identity, risk and customer behavior. Experian supports providers with data-driven energy and utilities solutions designed to help reduce losses, strengthen customer trust and support utility fraud prevention across the customer lifecycle. For a closer look at how these themes are unfolding across the sector, explore our 2026 State of Energy and Utilities Report, which examines each trend in greater depth through data-driven insights and industry examples. Read our first-ever State of Energy and Utilities Report examining the forces shaping the industry this year. Download now

Across agencies, decisions about digital services, staffing and oversight are often tied together. Public sector trends for 2026 reflect how these considerations are shaping modernization efforts and citizen trust today. At the federal, state and local levels, the public sector outlook 2026 highlights how modernization, program integrity, workforce resilience and citizen trust influence how services are delivered and how resources are prioritized. Four trends shaping the public sector in 2026 Agencies are navigating a set of trends that are influencing both strategic planning and day-to-day execution. Fiscal pressure and program integrityBudget volatility and increased scrutiny may elevate the importance of payment accuracy and operational consistency, particularly as eligibility rules evolve and caseloads remain high. This can surface in areas such as eligibility verifications, benefits recertifications or grant administration, where data inconsistencies may have a broader operational impact. Modernization and technology accelerationAs agencies continue public sector modernization, digital access may expand faster than existing controls can keep pace. This is often most visible in online applications, self-service portals and account management tools, where verification processes may not evolve at the same pace as access. Fraud losses across the U.S. have been estimated at approximately $160 billion, highlighting the extent of identity and payment risks present in digital environments. Decisions about identity assurance and fraud prevention can influence how agencies scale online services. Workforce resilienceStaffing constraints and skill gaps may affect processing timelines, oversight capacity and institutional knowledge, potentially contributing to longer review cycles or greater reliance on manual quality checks. Workforce data shows roughly 200,000 federal positions were reduced in the past year, which may influence how agencies approach automation and oversight. Automation and government data analytics can play a more central role in supporting consistency across programs. Citizen trust and digital experienceAs more interactions move online, citizen trust may be influenced by both security and usability. Public sector fraud prevention approaches that apply friction only when risk indicators are present can help agencies maintain accessibility while managing exposure. What these signal for agencies Together, these trends point to a shift in how agencies evaluate risk and prioritize investment. Choices about modernization, staffing and oversight may increasingly shape one another. Approaches that strengthen government program integrity, improve visibility across digital interactions and support informed decision-making may help agencies sustain service levels while managing evolving risk. For a closer look at how these trends are unfolding across agencies, explore our 2026 Public Sector Trends and Impact Report, which delves into each theme in greater depth through data-driven insights and real-world agency use cases. Read our first-annual 2026 Public Sector Trends & Impact Report to understand the forces reshaping agency operations and trust. Download now

  Experian Verify is redefining how lenders streamline income and employment verification; a value clearly reflected in Marcus Bondraeger’s experience at Freedom Mortgage. With access to the second-largest instant payroll network in the U.S., Experian Verify  connects lenders to millions of unique employer records, including those sourced through Experian Employer Services clients, delivering instant results at scale. This reach enables lenders to reduce manual processes, accelerate loan decisions and enhance the borrower experience from the very first touchpoint. Unlike traditional verification providers, Experian Verify offers transparent, value-driven pricing: it charges only when a consumer is successfully verified, not simply when an employer record is found. As lenders navigate increasing compliance requirements and secondary market expectations, they can also rely on Experian Verify’s FCRA-compliant framework, fully supporting both Fannie Mae and Freddie Mac. Combined with Experian’s industry-leading data governance and quality standards, lenders gain a verification partner they can trust for accuracy, security, and long-term operational efficiency. Perhaps most importantly, Experian Verify delivers 100% U.S. workforce coverage through its flexible, automated waterfall: instant verification, consumer-permissioned verification, and research verification. This multilayered approach ensures lenders meet every borrower where they are, whether they’re connected to a large payroll provider, a smaller employer, or require additional document-based validation. As Marcus highlights in the video, this comprehensive and configurable design empowers lenders to build verification workflows that truly fit their business needs while enhancing speed, completeness, and borrower satisfaction. Explore Experian Verify

Fraud is evolving faster than ever, driven by digitalization, real-time payments and increasingly sophisticated scams. For Warren Jones and his team at Santander Bank, staying ahead requires more than tools. It requires the right partner. The partnership with Santander Bank began nearly a decade ago, during a period of rapid change in the fraud and banking landscape. Since then, the relationship has grown into a long-term collaboration focused on continuous improvement and innovation. Experian products helped Santander address one of its most pressing operational challenges: a high-volume manual review queue for new account applications. While the vast majority of alerts in the queue were fraudulent and ultimately declined, a small percentage represented legitimate customers whose account openings were delayed. This created inefficiencies for staff and a poor first impression of genuine applicants. We worked alongside Santander to tackle this challenge head-on, transforming how applications were reviewed, how fraud was detected and how legitimate customers were approved. In addition to fraud prevention, implementing Experian's Ascend PlatformTM, with its intuitive user experience and robust data environment, has unlocked additional value across the organization. The platform supports multiple use cases, enabling collaboration between fraud and marketing teams to align strategies based on actionable insights. Learn more about our Ascend Platform

Mortgage rates remain elevated by historical standards: the average 30-year fixed rate ended 2025 at 6.15% (Freddie Mac’s PMMS), after spending much of the year closer to 7% (52-week high ≈ 7.04%) (Freddie Mac, 2025; Mortgage News Daily, 2025). At the same time, the Federal Reserve’s December 2025 Summary of Economic Projections signaled a modest easing path into 2026 (median fed funds projection 3.4% at end-2026), reinforcing expectations of lower borrowing costs ahead rather than an immediate return to pre-2022 conditions (Federal Reserve, 2025). Affordability pressures persist and vary widely by metro and region: rent-to-income ratios in many Midwestern markets are below 30%, while parts of the Northeast (e.g., New York City) exceed 50% of income for a typical renter household (Moody’s Analytics, 2023; 2025). Given this fragmentation, national averages no longer provide sufficient guidance. Lenders need a data-driven playbook that translates insight into action across the lending lifecycle.  Pillar 1: Borrower insights  Today’s renter profile skews younger: Gen Z already accounts for ~30.5% of renters and, together with younger millennials (under 35), represents over half of the rental population (Experian, 2025). Zillow’s Consumer Housing Trends Report similarly shows Gen Z makes up 25% of all renters and 47% of recent movers—evidence that the next cohort of first-time buyers is emerging from today’s rental pool (Zillow Research, 2024). Traditional credit files can miss reliable payment behavior. Both Fannie Mae and Freddie Mac now consider positive rent payment history in automated underwriting—using bank or payroll-verified data to augment limited credit histories—improving access for qualified renters (Fannie Mae, 2025; Freddie Mac, 2025). Data-driven edge: Broader borrower views—incorporating verified rent payments, student loan performance, and alternative credit signals—help identify “hidden prime” consumers and responsibly expand the addressable market.  Pillar 2: Operational efficiency  Margin pressure is persistent, and manual income/employment verification remains a top pain point: manual methods can take 30 minutes to several days, raise costs, and increase drop-offs (MeridianLink, 2025). Modern VOE/VOI solutions—e.g., Mastercard Open Finance (Finicity/Argyle), Truework—deliver GSE-accepted digital verifications that reduce friction, lower per-loan costs, and provide rep/warranty relief when validations succeed ( Mastercard; Business Wire/Morningstar). Data-driven edge: Verification and documentation automation enables speed, consistency, and scalability without proportional staffing or risk increases.  Pillar 3: Geographic precision  Affordability is deeply local. The national rent-to-income ratio has recently eased back toward ~27–30%, but disparities persist: several Midwest markets track below 30%, while New York City reaches ~67% and Miami exceeds 40% (Moody’s Analytics, 2023; 2025). Recent rent reports also show metros like Miami ranking as least affordable and others (e.g., Austin) more affordable for typical renter incomes, underscoring the need for metro-level targeting (Realtor.com, 2025). Data-driven edge: Market-level data—local affordability, migration, inventory, and labor trends—helps focus growth where demand is most likely to convert and perform over time.  Pillar 4: Refinance readiness  Refinance activity is muted but not gone. With rates dipping from 2025 highs, millions are positioned to benefit: as of Nov. 2025, about 4.1 million mortgage holders were “in the money” (≥ 75 bps savings), including 1.7 million highly qualified candidates; the cohort could grow toward ~5 million with small additional rate declines (ICE Mortgage Technology, 2025). Homeowners also held $11.2 trillion in tappable equity entering Q4 2025, supporting additional refinance and home-equity lending opportunities (ICE Mortgage Technology, 2025). Data-driven edge: Segment portfolios by rate sensitivity, pre-model operational capacity, and streamline digital processes to capture volume quickly while preserving experience.  Bringing it together  These four pillars—borrower insights, operational efficiency, geographic precision, and refinance readiness—form a unified framework for outperforming peers in today’s housing market. Lenders that operationalize this approach will be better positioned to: • Serve more borrowers responsibly by leveraging verified rent and payroll data to expand access (Fannie Mae; Freddie Mac). • Manage risk with greater precision through automated verifications and underwriting validations (Mastercard). • Build sustainable regional strength by deploying resources in metros where affordability and demand align (Moody’s; Realtor.com). • Capture refinance demand at scale as candidates and tappable equity expand when rates ease (ICE Mortgage Technology). The housing market is shifting—not back to what it was, but toward something more fragmented and data-dependent. Lenders who build strategy on insight rather than instinct will define the next generation of market leaders.  References  Experian. (2025, January 10). The shifting demographics of today’s renters. https://www.experian.com/blogs/insights/the-shifting-demographics-of-todays-renters/  Federal Reserve Board. (2025, December 10). Summary of Economic Projections (Table PDF). https://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20251210.pdf  Freddie Mac. (2025, December 31). Primary Mortgage Market Survey® (PMMS®) weekly data. FRED series MORTGAGE30US. https://fred.stlouisfed.org/series/MORTGAGE30US/  Fannie Mae. (2025, January). FAQs: Positive rent payment history in Desktop Underwriter. https://singlefamily.fanniemae.com/originating-underwriting/faqs-positive-rent-payment-history-desktop-underwriter  ICE Mortgage Technology. (2025, November 10). November 2025 Mortgage Monitor (press release & report). https://mortgagetech.ice.com/resources/data-reports/november-2025-mortgage-monitor  Mastercard. (2024, June 25; updated September 23, 2024). How data-enabled income and employment verifications deliver smarter, seamless financial experiences. https://www.mastercard.com/us/en/news-and-trends/Insights/2024/data-enabled-income-and-employment-verifications-deliver-smarter,-seamless-financial-experiences.html  MeridianLink. (2025, April 8). Instant verification: Rethinking income and employment tools. https://www.meridianlink.com/blog/its-time-to-take-a-new-look-at-income-and-employment-verification-tools/  Moody’s Analytics. (2023, November 27). 30% of income on rent remains the norm in U.S. metros (Data story). https://www.moodys.com/web/en/us/insights/data-stories/q3-2023-us-rental-housing-affordability.html  Moody’s CRE. (2025, March 11). Q4 2024 housing affordability update. https://www.moodyscre.com/insights/cre-trends/q4-2024-housing-affordability-update/  Mortgage News Daily. (2026, January 2). Freddie Mac mortgage rates—weekly survey (historic table). https://www.mortgagenewsdaily.com/mortgage-rates/freddie-mac  Realtor.com Economics. (2025, October 14). September 2025 rental report: Rental affordability improved compared to a year ago. https://www.realtor.com/research/september-2025-rent/  Zillow Research. (2024, October 14). Renters: Results from the Zillow Consumer Housing Trends Report 2024. https://www.zillow.com/research/renters-housing-trends-report-2024-34387/ 

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

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

Financial security has become one of the most pressing concerns in today’s workforce. Rising living costs, higher debt, market volatility and an ever-growing threat of identity theft are putting pressure on employees across every income level. For employers, this shift presents both a challenge and an opportunity: how to meaningfully support employees’ financial well-being in a way that drives engagement, loyalty and long-term success. The reality is clear. Traditional benefits alone are no longer enough. While a steady paycheck, insurance coverage, and retirement plans remain essential, employees increasingly expect their employers to play a more active role in helping them manage day-to-day finances, build credit confidence and protect their identities. When financial stress goes unaddressed, it impacts productivity, mental health and retention, and employers feel the effects just as strongly as their people do. Why fragmented benefits fall short Many organizations offer pieces of financial protection, but those offerings are often disconnected. Identity protection may stop at basic monitoring and alerts. Credit education is frequently limited to static resources that don’t reflect real-life financial behavior. Financial wellness tools, when available, are often treated as optional perks rather than foundational benefits. The problem isn’t a lack of tools; it’s a lack of connection. Employees don’t need more standalone solutions; they need integrated support that meets them where they are and evolves with their financial lives. The rise of all-in-one financial protection Forward-thinking employers are redefining their benefits strategies by adopting a holistic approach to financial well-being. The new standard combines three essential pillars into a single, cohesive experience: Credit education helps employees understand their credit profiles, build healthier habits and make informed financial decisions that unlock better opportunities. Financial wellness tools provide personalized guidance for budgeting, saving, managing debt and planning for the future, reducing stress and improving confidence along the way. Identity protection safeguards employees against fraud and cyber threats with proactive monitoring, alerts and hands-on recovery support when it matters most. When these elements work together, employees are better equipped to protect their paychecks, secure their identities and plan for long-term stability. The result is a workforce that feels supported, empowered and engaged. Turning financial well-being into a strategic advantage At Experian®, we believe financial well-being should be a strategic advantage, not an afterthought. Our all-in-one employee benefits solutions are designed to deliver measurable impact, from improved credit outcomes and reduced financial stress to stronger engagement and retention. By partnering with us, employers can offer a seamless, scalable and trusted experience that supports employees through every stage of their financial journey, while reinforcing their commitment to employee well-being. Download the full report Want to learn more about how credit education, financial wellness and identity protection come together to create a stronger benefits strategy? Download our report to explore the data, insights and strategies shaping the future of employee financial benefits and how your organization can lead the way. Download now

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

As the U.S. housing market enters a new phase, the 2026 State of the U.S. Housing Market Report from Experian provides a data-driven overview for lenders, servicers, and property managers. This article synthesizes findings related to mortgage originations, affordability pressures, home equity utilization, credit risk, and generational sentiment, with implications for lender strategy in 2026 (Experian, 2026).  Mortgage market in flux: Opportunity amid transition  The mortgage market presents mixed signals. Rate moderation in late 2025 contributed to renewed demand, while the product mix continued to evolve. Conventional loans remained dominant at approximately 72% of originations, yet Veterans Affairs (VA) loans experienced the highest growth between 2023 and 2025, reaching 10.8% market share (Experian, 2026).  At the same time, second mortgages and home equity lines of credit (HELOCs) gained momentum as homeowners sought liquidity without refinancing out of historically low interest rates. This trend reflects growing demand for equity-based solutions that preserve favorable first-mortgage terms (Experian, 2026).   Pull-through challenges: Only 34% of inquiries become loans  Conversion efficiency remains a key challenge. Only 34% of first-mortgage hard credit inquiries resulted in a completed mortgage origination, highlighting friction between borrower interest and loan fulfillment (Experian, 2026).  Consumer research reinforces this gap. In an Experian survey, 50% of respondents reported that understanding what they could qualify for would be the most helpful step in their homeownership journey, suggesting that improved prequalification tools could materially increase pull-through rates (Experian, 2026).   Affordability pressure goes beyond the mortgage  Between 2021 and 2025, property taxes increased by 15.2%, while non-tax escrow costs—primarily homeowners' insurance—rose by 67.4% nationwide (Experian, 2026).  State-level variation further complicates affordability assessments. Florida recorded the highest average non-tax escrow expenses at $430 per month largely due to sharp increase in home insurance costs. California, by contrast, exhibited the highest average property tax burden at $626, largely driven by elevated home values despite lower statutory tax rates (Experian, 2026). These dynamics underscore the importance of holistic cost modeling, particularly for first-time buyers.   Home equity: A lender’s growth frontier  Home equity remains a significant growth opportunity. An estimated 96.2 million consumers reside in owner-occupied homes, with substantial portions owning their homes outright or holding more than 20% equity (Experian, 2026). HELOC usage is increasing, particularly among younger borrowers, 50% of whom utilize more than 60% of their available HELOC credit, compared with 36% of older borrowers (Experian, 2026).  Market share shifts are also notable. Fintech lenders experienced a 140.2% increase in HELOC originations from 2023 to 2025, significantly outpacing banks and credit unions. These gains suggest that digital-first experiences and streamlined workflows are increasingly decisive factors for borrowers (Experian, 2026).   Risk and resilience: What credit and property data reveal  Overall delinquency rates eased slightly; however, near-prime and prime borrowers demonstrated early signs of stress, particularly within first-mortgage portfolios (Experian, 2026).  Property-level risk is also intensifying. Flood exposure increased by 3.7% nationally, with 26.4% of Florida homes identified as at risk. Rising exposure has contributed to escalating insurance costs, further affecting affordability and credit performance (Experian, 2026).  From a credit hierarchy perspective, secured debt—especially mortgages and auto loans—continued to show the lowest delinquency rates. In contrast, student loans and credit cards exhibited higher delinquency risk, particularly among financially constrained renters and homeowners (Experian, 2026).   Generational optimism versus macroeconomic constraints  Despite affordability headwinds, consumer optimism persists. Approximately 47% of renters believe they will be ready to purchase a home within four years, increasing to 67% within eight years (Experian, 2026).  Structural constraints remain significant. Roughly 70% of homeowners hold mortgage rates below 6%, contributing to limited housing inventory as current owners remain rate-locked. With 30-year mortgage rates still above that level and a softening labor market, even modest increases in unemployment could further pressure affordability (Experian, 2026).   Implications for lenders  Experian’s analysis highlights several strategic priorities for housing industry stakeholders:  Expand access to credit. Incorporate alternative data sources, such as cash-flow analytics and rental payment history, to responsibly extend credit to underserved but qualified borrowers (Experian, 2026).  Capitalize on equity demand. Develop HELOC offerings that are fast, flexible, and digitally enabled to meet the needs of equity-rich, rate-locked homeowners (Experian, 2026).  Enhance risk precision. Integrate credit, property, and behavioral data to identify emerging risk early, particularly among near-prime segments, and to support more accurate pricing and portfolio management (Experian, 2026).   Conclusion  The 2026 housing market reflects a complex interplay of macroeconomic pressure, shifting borrower behavior, and growing reliance on home equity solutions. Agility and data-driven decision-making will be essential for lenders navigating this environment. The 2026 State of the U.S. Housing Market Report offers critical insight to support growth while managing risk in an evolving landscape (Experian, 2026).  📘 Access the full report here: Experian 2026 State of the U.S. Housing Market Report  References  Experian. (2026). 2026 state of the U.S. housing market report. Experian.     

The U.S. rental housing market has offered a clear window into broader economic pressures shaping household finances. Renting is no longer a short-term phase for many Americans; it has become a longer-term reality across generations. Rising housing costs, elevated interest rates, and persistent debt burdens are reshaping who rents, how long they rent, and the financial resilience of the rental population. For landlords, lenders, and housing stakeholders, understanding these shifts is essential not only for near-term risk management but also for anticipating how today’s renters will influence tomorrow’s housing demand.  A rental market increasingly defined by younger households  Younger Americans continue to dominate the rental landscape. More than half of U.S. renters are now under the age of 35, with Generation Z accounting for approximately one-third of the total rental population, according to Experian’s 2025 State of the Rental Housing Market report. While renting has always served as a starting point for younger households, the length of time spent renting is increasing. High home prices, ongoing student loan repayment obligations and mortgage rates that remain well above pre-2022 norms have delayed the transition to homeownership for many first-time buyers. As a result, renting has shifted from a temporary necessity to a longer-term financial strategy, often by default rather than by choice.  At the same time, renting is no longer confined to younger demographics. Business Insider reports that since 2023, the population of renters aged 44 and older has grown, reflecting a combination of affordability constraints and evolving lifestyle preferences.  Rent growth continues to outpace income  Affordability remains the defining challenge of the rental market. Experian data shows that average monthly rent has increased steadily over the past two years, rising from approximately $1,520 in early 2023 to roughly $1,760 by early 2025. Over the same period, the average renter’s income has stagnated or declined slightly, hovering near $51,600 annually. The combined effect of rising rents and softening income is a widening affordability gap. The national rent-to-income (RTI) ratio now averages 46.8%, far exceeding the 30% threshold commonly used to define housing affordability, according to Experian’s 2025 analysis.  Credit profiles reflect mounting financial pressure  As housing costs rise, renters’ financial health is increasingly under strain. Experian’s rental market insights indicate that more than half of renters now fall within Near Prime or Subprime credit tiers, representing a meaningful increase since 2023. This shift does not necessarily signal declining financial responsibility. Instead, it reflects younger and thinner credit files, higher overall debt balances, and sustained cost-of-living pressures. Experian also reports that renters paying more than $1,000 per month have experienced a double-digit increase in negative payment activity over the past two years.  Understanding payment priorities when budgets tighten  When households face financial strain, trade-offs become unavoidable. According to payment hierarchy data published by the Consumer Financial Protection Bureau (CFPB), renters tend to prioritize auto loans first, followed by personal loans and student loans. Rent payments and unsecured revolving credit, such as credit cards, often fall lower on the priority list. This dynamic helps explain why rent delinquencies can rise even among renters who remain current on other financial obligations.  Why Experian?  As the rental market evolves, having a clear, data-driven view of renter behavior is more critical than ever. Experian helps landlords, lenders, and housing stakeholders understand shifting demographics, affordability pressures, and payment priorities through trusted data and advanced analytics. With deeper insight into today’s renters, businesses can better manage risk, uncover opportunity, and prepare for what’s next in housing demand.   

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.