Data & Analytics
Every business makes decisions about people and transactions all day long. Should we approve this loan? Is this purchase fraud? Which customer should get this offer, and what should it be? For a long time, those decisions were made in one of two ways: a person reviewed each case by hand, or the company wrote fixed rules, like "approve anyone with a credit score above 700." Both work. Both also leave value on the table. The manual review is slow and hard to scale. The fixed rule can turn away good applicants and is slow to adapt when the market shifts. AI decisioning is a third way. What makes AI decisioning work Instead of relying on a single reviewer or a rigid rule, automated decisioning uses models that learn from data — studying how thousands of past cases turned out, finding the patterns that predict an outcome, and applying them to each new decision, often in real time. The result is faster, more consistent decisions. But a model on its own isn't the whole story. Getting real value from AI decisioning takes good data to learn from, AI analytics to generate insights, the tools to act on it and the governance to keep it compliant. What we've found is that the pieces only pay off when they work together, and that is where we're built differently. A model is only as good as what it learns from, and we pair your data with one of the deepest views of consumer and commercial credit: decades of full-file history and vetted attributes. Then we give you the tools to act on it. Use cases across your business Whether you're trying to grow your customer base, reduce fraud, manage lending risk, or improve collections, automated decisioning brings all the pieces together to make more accurate, consistent and explainable decisions at scale. Fraud and Identity A fraudulent transaction that slips through costs money and erodes trust. Rules are static, and fraudsters move fast. They'll probe boundaries, find the blind spots and move to the next scheme. By the time the rules are updated, they're already three steps ahead. How AI decisioning changes this: AI fraud detection with real-time risk scoring and decisioning across transactions and customer interactions Intelligence that continuously learns from results to help adapt fraud strategies as threats evolve Reduced false positives and less friction for customers at account opening and checkout Identity verification tools that confirm someone is who they say they are without slowing down the experience Credit and Lending Loan approval is where the relationship begins. Credit risk decisioning helps lenders find that delicate balance between approving enough people to grow, but carefully enough to manage risk. Missing that balance means turning away good customers or taking on losses that are difficult to absorb. How AI decisioning changes this: Increased approval opportunities for creditworthy applicants without increasing overall risk Models you can update and deploy quickly as market conditions change, rather than waiting months Ability to run "what-if" scenarios to test how a new strategy would have performed on your historical data before putting it live Collections Which customer should your team reach out to today? Through which channel? What kind of message? If you reach out too aggressively, you push someone who might have recovered into default. If you wait too long, you lose them. If you call someone at work, they resent you; if you text, they might ignore it. If you offer a payment plan, they might accept it, but only if the terms make sense to their financial situation. How AI decisioning changes this: Optimized next-best-action and contact-channel strategies for each individual customer Improved recovery potential through better targeting Less time spent on accounts with a lower propensity to pay, freeing your team for higher-impact cases Ability to segment and test new strategies before rollout Customer Acqusition Finding the right customers is about reaching the right people with the right offer at the right time. To stay competitive, it’s now a requirement to balance growth with risk while creating a seamless experience converting prospects into customers. How AI decisioning changes this: More precise prospect targeting using credit, behavioral, and alternative data, where permitted, to identify consumers most likely to respond Personalized offers delivered in real time Dynamic decision strategies that can be updated quickly as market conditions and customer behavior change Ongoing testing and optimization of acquisition strategies to improve campaign performance and support customer lifetime value Driving results with AI decisioning Every customer interaction is a decision. Businesses that can adapt quickly will be better positioned to grow, manage risk, and deliver the experiences customers expect. The technology will continue to evolve, but the goal remains the same: making informed decisions that balance business objectives, risk, and customer experience. Learn more about our decisioning software
Learn how Caliber Financial uses Experian data to improve lead targeting, underwriting and AI-driven decisioning for better outcomes.
Credit modernization, VantageScore 4.0, and smarter data are reshaping mortgage lending. Learn how lenders can reduce risk, optimize workflows, and expand access.
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.
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.
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.
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.
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
Rising late-stage mortgage delinquencies signal hidden risk in 2025. Learn how lenders can identify early warning signs and manage mortgage and HELOC risk proactively.
Learn how alternative data enhances credit decisioning by giving lenders deeper visibility into consumer financial behavior and improving access to credit for more consumers.
Fintech analytics transforms fragmented data into real-time decisioning power, helping lenders manage risk and earn consumer trust.
Discover how data-driven risk management strategies are transforming credit risk management in the fintech industry.
As financial behavior becomes more dynamic, real-time data is emerging as a powerful tool in reshaping how lenders assess risk.