Alternative fuel vehicles continued to gain momentum in the fourth quarter of 2025, driven by expiring electric vehicle (EV) tax credits and a growing preference for options that bridge the gap between full electric and traditional gasoline vehicles. According to Experian’s Automotive Consumer Trends Report: Q4 2025, alternative fuel vehicles accounted for 38.6% of new retail car registrations in the last 12 months, with 11% battery electric (BEV) and 27.6% hybrids and plug-in hybrids (PHEVs). This signals that the narrative about growth in consumer interest for alternative fuel is increasingly towards hybrids, not just full EVs. Taking a deeper dive, the Toyota Camry Hybrid led all alternative fuel car models, coming in 31.7% in Q4 2025. Rounding out the top five were Tesla Model 3 (19%), Honda Civic Hybrid (10.1%), Honda Accord Hybrid (9%), and Toyota Prius (5.3%). Interestingly, the Toyota Camry also stood out as the top model in both new and used car markets in Q4 2025, holding 12.2% of new car market share and 6.3% of used car market share. The Honda Civic ranked second in new car market share, coming in at 10.5% this quarter, while the Honda Accord secured the second spot in the used car market at 5.8%. The prominence of these vehicles leading both new and used car markets reflects a combination of strong new-vehicle sales and sustained demand in the secondary market. Data in the report also revealed strong loyalty within Toyota and Honda, with significant inflow between the two brands. For instance, 38.4% of Toyota Camry buyers replaced their vehicle with another Camry in Q4 2025, and 39.7% of Honda Civic buyers replaced it with another Civic. These trends reinforce the value of dealers monitoring evolving consumer preferences and aligning inventory with vehicles that offer fuel efficiency and flexible powertrain options as the market continues to shift. To learn more about car insights, view the full Automotive Consumer Trends Report: Q4 2025 presentation.

Discover how Experian’s Mortgage Loan Performance dataset reveals current second lien balances that materially impact MBS prepayment speeds, CLTV accuracy, and call protection. Learn why this new loan-level data meets the New, Material, and Significant criteria to move agency MBS markets and improve investor modeling precision.

  As vehicle prices and interest rates continue to evolve, both consumers and lenders are recalibrating their approaches to affordability and long-term sustainability. This shift has resulted in the subprime segment growing to its largest share of total finance market for subprime in the fourth quarter since 2021. According to Experian’s State of the Automotive Finance Market Report: Q4 2025, subprime borrowers accounted for 15.31% of total vehicle financing, an increase from 14.54% in Q4 2024. To understand why the subprime space is evolving, we took a deeper dive into the affordability picture and how changes in pricing and interest rates are influencing both consumer decisions and lender strategies. In Q4 2025, the average loan amount for a new vehicle increased $1,882 from the prior year to $43,582, and the average interest rate for a new vehicle went from 6.34% last year to 6.37% this quarter. As a result, the average monthly payment increased from $746 to $767 in the same time frame. On the used side, the average loan amount increased $872 year-over-year, reaching $27,528 in Q4 2025. However, despite the average interest rate declining from 11.63% to 11.26% during the same time, the average monthly payment grew $9 from last year to $537 this quarter. These changes are prompting thoughtful adjustments across the automotive ecosystem. Consumers are comparing financing options more carefully and adjusting loan terms when necessary to prioritize the cost of ownership. Lenders are also focusing more on payment flexibility and how long-term borrowers are performing as they leverage it for central pillars of strategies to stay ahead of the ever-evolving market. To learn more about automotive finance trends, view the full State of the Automotive Finance Market Report: Q4 2025 presentation on demand.

The mortgage industry is adapting to a structural shift. Experian’s 2026 State of the U.S. Housing Market Report shows a market in transition. Conventional loans account for 72% of originations, FHA 17.5% and VA 10.8% with VA showing the strongest growth from 2023 to 2025. But origination mix only tells part of the story. Beneath it lies an arguably more consequential shift: borrower expectations, affordability pressures and regulatory changes are converging. On the regulatory front, the Homebuyers Privacy Protection Act (HPPA) may reduce mortgage trigger leads and limit broad competitive outreach. As competitive visibility narrows, the lender relationship becomes more central and important beyond the closing transaction. In this environment, lenders must provide value to win, and that increasingly means financial wellness. A growing trust gap Only 34% of first mortgage hard inquiries of first mortgage hard inquiries convert into funded originations, according to Experian. That means two-thirds of borrowers who initiate the process never close. External data confirms the trend as Mortgage Bankers Association reported retail mortgage pull-through rates declined to roughly 69% in early 2025 – the lowest in over a decade – and as low as 55% among depository lenders. While pull-through can be impacted by a number of factors not influenced by the lender, when borrowers abandon applications, it can be a biproduct of uncertainty – something that the lender can influence. This is where financial wellness becomes strategic and lenders can close the trust gap by providing proactive credit visibility and guidance before underwriting friction occurs. Read more in our white paper, “The New Unlock for Mortgage.” Affordability stress While rates have eased from their 2023 highs, they remain above 6%, sustaining the lock-in effect and limiting housing supply, according to Experian’s 2026 State of the U.S. Housing Market Report. Approximately 70% of homeowners are locked into sub-6% mortgages, according to Freddie Mac. Beyond mortgage rates, increases in property taxes and non-tax escrow amounts (i.e. insurance) increase affordability pressures for consumers. Financial wellness solutions that incorporate credit monitoring, budgeting insights and cashflow visibility help borrowers understand whether they are prepared. Opportunity among millennials and Gen Z Nearly 47% of U.S. renters expect to purchase a home within four years, rising to 67% within eight years, according to Experian. This signals the time to invest in financial wellness as a differentiator, and both a growth and retention driver, is now. Financial wellness as the new unlock for mortgage Financial wellness is not an ancillary service but the foundation upon which borrower confidence, long-term engagement, conversion and risk management connect. Lenders who embed solutions like credit education, score visibility, alerts, and identity protection directly into the consumer experience can differentiate themselves from the competition above and beyond rates alone. Read more in our white paper, “The New Unlock for Mortgage.” Learn more about Experian Mortgage

What do BNPL rules mean for mortgage credit scoring? As regulators push for greater transparency and alternative data reporting, lenders must adopt modern credit models that include rent, cash flow, and trended data. Learn how evolving BNPL guidance signals the future of mortgage underwriting and why forward-thinking lenders are modernizing scoring strategies now.

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

Explore energy and utilities industry trends 2026, focusing on digital services and evolving customer demands in the sector.

Explore the public sector trends for 2026 shaping digital services, workforce resilience, and citizen trust for better governance.

  Experian Verify is redefining how lenders streamline income and employment verification; a value clearly reflected in Marcus Bontrager’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

Lenders who want to outperform peers in today’s housing market should embrace a data-driven playbook. These four strategic pillars—borrower insights, efficiency, geography, and refinance readiness—define the path forward. 

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.

Explore the importance of employee benefits in promoting financial security and supporting employee well-being in today’s workforce.

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