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Manual processes are quietly expensive. Every handoff between teams, every file transfer waiting in a queue and every decision that sits on someone's desk adds cost, introduces risk and slows the customer experience. For financial institutions, those delays translate directly into lost revenue and eroded margins. That’s why workflow automation is becoming critical for financial institutions looking to stay competitive. Done well, it doesn't just make existing tasks faster. It reshapes how decisions get made across the entire customer lifecycle, from the first marketing touch to account servicing and beyond. What is workflow automation? Workflow automation is the use of technology to run a sequence of tasks, decisions and handoffs with minimal manual intervention. Instead of a person moving work from one step to the next — pulling data, applying a rule, routing an account and sending a communication — software executes those steps automatically based on defined logic and real-time data. For financial institutions, workflow automation usually combines four ingredients: Data Connecting to the internal and external data sources that inform a decision. Analytics Scores, models and attributes that turn raw data into insights. Decisioning A rules engine that determines the right action for each customer or account. Execution The operational layer that carries out the action, whether that's an offer, a credit line change or outreach. The benefits of workflow automation The value of automation goes well beyond "doing the same thing faster." The benefits financial institutions consistently see include:Greater efficiency and lower operating costsAutomation frees underwriters, analysts and agents to focus on exceptions and high-value work rather than repetitive processing. Faster, more consistent decisionsA credit application that once waited in a queue can be assessed in real time against consistent, auditable policies, improving both the applicant's experience and portfolio quality. Better customer experiencesAutomation enables financial institutions to personalize communications at the point of interaction and offer the self-service options that many people now prefer. Improved compliance and governanceReduce the risk of costly compliance failures with built-in controls, audit trails and guided workflows. ScalabilityRespond to changing volumes without sacrificing speed, consistency or the customer experience. Where workflow automation makes the biggest difference Workflow automation tends to deliver the most value where decisions are frequent, repeatable and informed by data. In financial services, those opportunities exist across the customer lifecycle. Onboarding Onboarding is a customer's first experience of your organization, and it's also where friction can cause customers to abandon the process and turn to another provider. Forty percent of U.S. consumers have considered walking away from opening a new account when the process felt burdensome.1 An automated onboarding workflow can bring together document verification, device intelligence, behavioral analytics, credit attributes and more, then orchestrate them into a single decision. The result is a lower-friction experience for the customer and a consistent, auditable process. Once customers are on the books, serving them well means making continuous, high-volume decisions: credit line changes, cross-sell and up-sell opportunities, risk monitoring and retention actions. Automation makes it practical to run these recurring decisions consistently across an entire portfolio, using a holistic view of each customer that draws on multiple scores and attributes. Lending The underwriting process is a great example of how workflow automation can help prevent applicants from waiting days for an answer. Loan origination and credit decisioning capabilities are designed to create a seamless review process across consumer and commercial lending. After automating originations with our solutions, Michigan State University Federal Credit Union cut application processing time to under 24 hours. Fraud Financial institutions are checking fraud at every touchpoint, and the standard for AI fraud detection continues to rise as fraudsters use AI to slip under the thresholds of any single detection tool. Rather than running fraud checks in isolation, an automated workflow can run multiple fraud and identity verification services in parallel and weigh signals together. A fraud decisioning platform connects signals across internal systems, Experian data and third-party services, allowing teams to stay on top of evolving threats. Build a strong foundation for workflow automation Workflow automation can connect these stages, creating a consistent decisioning framework. What ultimately separates good automation from great automation is the quality of the data and decisioning software underneath it. An automated workflow is only as good as the information feeding it. That's where our comprehensive credit, alternative and identity data with the tools financial institutions need to act on it. Learn more here FAQs How does automated decisioning improve credit decisions? Automated decisioning applies consistent logic to every account in real time or in bulk, enabling faster and more informed decisions, quicker responses to market and regulatory changes at the point of interaction. What is workflow automation in financial services? It's the use of software to execute sequences of data gathering, analysis, decisioning and action. Does workflow automation replace human judgment? No. The goal is to automate routine, high-volume decisions so skilled staff can focus on the exceptions and complex cases that genuinely require human judgment. For example, a sensitive collections conversation or a nuanced underwriting call. Are we still compliant with regulations if we use an automated workflow process? Well-designed platforms include built-in governance, audit trails and compliance controls that help institutions align with requirements like the Fair Credit Reporting Act (FCRA) and other regulatory guidelines improving compliance compared with manual processes. How long does it take to implement? It varies by solution and scope, but modern cloud-based platforms are designed for fast onboarding and limited IT involvement. 1Global Fraud Snapshot 2025: Opportunities and challenge in identity, fraud and financial crime

Start with a simple question Credit prescreen is an important tool in many lenders’ growth strategies. But the precision of any prescreen strategy depends on the data behind it. What financial behavior might traditional credit data alone not reveal? With Clarity data now available for Instant Prescreen decisioning, lenders can bring alternative credit insights into their targeting strategy, helping them identify prospects who may align with their established criteria, refine targeting strategies and explore additional acquisition opportunities while maintaining control over their risk thresholds. Additional insights alongside traditional credit data For many consumers, a traditional credit file tells a rich and reliable story. But it doesn't always tell the whole story. Consumers may also be using alternative financial products, such as small-dollar installment loans, single-payment loans, auto title loans or rent-to-own agreements and building payment histories that provide additional signals about their financial behavior. For lenders, those unseen signals can represent untapped opportunities. With more than 60 million unique subprime identities, Clarity's database helps lenders gain a more complete view of their applicant pool. Clarity data adds another dimension to that view, providing alternative credit insights that can help lenders better understand consumers whose financial behavior may not be fully represented by traditional credit data alone. How Clarity data sharpens instant prescreen decisioning Clarity provides specialty alternative credit data, with insights into subprime and near-prime consumer activity that may not appear in traditional credit files. And because Clarity is part of Experian, those insights can now be brought directly into Instant Prescreen decisioning. That means lenders can incorporate additional attributes and scores into their credit decisioning strategies without managing a separate data feed or stitching together disconnected sources. It has quickly become a visibility gap lenders can't ignore. Additional data may help support more granular segmentation and targeting strategies. Lenders remain in control of their criteria and risk thresholds while gaining additional information to inform their prescreen strategies. When considered alongside traditional credit data, alternative credit insights can support several aspects of prescreen decisioning: Identify more opportunities: Surface qualified prospects who may be harder to identify using traditional credit data alone. Refine targeting: Add alternative credit insights to help differentiate consumers with greater precision. Inform offer strategies: Use a broader view of financial behavior to help align consumers with appropriate offers. Expand intelligently: Explore incremental audience opportunities while maintaining control over your established risk criteria. Simplify execution: Access Experian and Clarity insights within a connected Instant Prescreen decisioning environment. See more opportunity in your prescreen strategy Growth doesn’t always require looking for an entirely new audience. Sometimes, it starts with seeing more in the audience already in front of you. By bringing Clarity data into Instant Prescreen, lenders can add another layer of insight to their decisioning, helping identify incremental opportunities, refine targeting and support acquisition decision processes across a broader range of consumers. Explore prescreen solutions

Fraudsters are getting surprisingly good at onboarding. Sometimes, better than your customers. Legitimate customers treat onboarding like an errand. They start an application between other tasks, get distracted, forget a password, switch devices, upload a document or come back later to finish. Their digital lives aren’t always linear, because real life isn’t either. Fraudsters approach onboarding differently. For them, opening an account is the objective. Every interaction is designed to increase the odds of success. The difference raises an uncomfortable question hanging over onboarding: What exactly are we rewarding? When smooth becomes suspicious Digital onboarding has traditionally rewarded experiences that feel smooth, consistent and complete. The challenge is that legitimate customers rarely behave that way. Most people approach onboarding somewhere between mildly distracted and mildly annoyed. They pause halfway through because dinner is burning. They reopen an old account only to realize everything is attached to an email they made in college and, somehow, still use for airline receipts. Digital life accumulates history unevenly, because ordinary life does too. Fraudsters have every reason to eliminate those inconsistencies. Applications may be rehearsed. Identity attributes are assembled deliberately. Contact points are prepared in advance. Every interaction is optimized to make the application appear credible. Ironically, the qualities organizations often associate with confidence — clean submissions, steady progression and few corrections — can also describe applications that have been carefully engineered to pass inspection. The challenge isn't that smooth onboarding is meaningless. It's that smooth onboarding, by itself, doesn't tell the whole story. Context changes interpretation A smooth onboarding experience should be the beginning of the evaluation, not the end. Behavior provides important context. How someone moves through an application can reveal whether the experience feels naturally human or unusually orchestrated. Do they interact naturally? Do they hesitate, correct mistakes or navigate in ways that resemble ordinary human behavior? Or does the session appear unusually scripted, automated or repetitive? Identity verification adds another layer. Matching information across trusted sources, validating identity details and strengthening confidence in account creation remain important, particularly when onboarding decisions carry financial, fraud or customer experience consequences. But verification largely answers a point-in-time question: Does this information match right now? A third layer comes from digital history. An inbox attached to years of airline receipts, loyalty accounts, subscription renewals, account recovery, financial notifications and familiar digital routines introduces a different kind of confidence. Legitimate digital identities leave behind patterns of persistence and engagement that develop gradually over time. Fraudsters can assemble convincing identity attributes, but creating years of ordinary digital life is much harder. Building confidence in an identity requires more than verifying information submitted during a single onboarding session. It requires understanding whether the identity reflects a broader history that supports what the application suggests. A multilayered approach builds stronger identity confidence No single signal can provide a complete view of identity risk. Organizations need multiple sources of confidence that reinforce one another. That's the thinking behind our approach: combining behavioral intelligence, identity verification and digital identity continuity into a more complete view of risk. We bring these complementary layers together through: • NeuroID adds behavioral context during onboarding and account creation, helping identify interaction patterns that may indicate automation, manipulation or coordinated fraud. • Precise ID® strengthens identity verification and resolution by comparing applicant information with trusted identity data. • AtData, recently added to our portfolio, contributes email-centered intelligence based on persistence, engagement and long-term digital history. Together, these capabilities help organizations move beyond evaluating a single moment in time to understanding whether an identity is supported by consistent behavior, trusted identity data and an established digital history. The future of fraud prevention isn't about rewarding the smoothest application. It's about recognizing the most trustworthy identity. Fraudsters can rehearse an application. They can optimize an onboarding journey. They can even assemble convincing identity attributes. What they can't easily manufacture is years of ordinary digital life. That's why digital identity continuity has become an important layer of modern fraud prevention. Combined with identity verification and behavioral intelligence, it helps organizations distinguish between identities that simply look convincing and those supported by a history that is much harder to fake. Learn more Contact us

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What if some of your best potential borrowers are the ones your traditional credit strategy can't fully see? A credit score can tell lenders a lot about a consumer, but it doesn't always capture the full picture of how someone is managing their financial life. For consumers with nontraditional income patterns or limited credit histories, that incomplete view can mean missed opportunities. In this Ask the Expert session, David Elmore of Experian talks with Michelle Goeppner, Chief Lending Officer at Vantage West Credit Union, about how alternative data can provide additional context around consumer risk, uncover opportunities traditional data alone might miss and help lenders expand their reach without disrupting strategies that already work. Who could lenders be missing? That question is especially important when a consumer’s financial life doesn’t fit neatly into a traditional credit profile. Take gig workers. Someone driving for Uber or delivering for DoorDash likely has a different income pattern than a salaried employee — irregular, seasonal, spread across platforms. That doesn't mean they aren't reliably managing bills, rent and other obligations. It just means a traditional file may not show it. Goeppner has a name for the risk of overlooking that context: FOMM — Fear of Missing Members. You've heard of FOMO — Fear of Missing Out. I think about it as FOMM — Fear of Missing Members. Who are we leaving behind if we're not using it?Michelle Goeppner, Chief Lending Officer For credit unions especially, that's not just a data question — it's a mission question. A partial view of a member's finances can mean missing a member the institution exists to serve. The credit score alone doesn't tell you where someone's headed Traditional credit data is still  foundational to lending decisions. But alternative data — income, cash flow, payment behavior — adds a layer that a credit score alone can't provide. Goeppner illustrates the distinction with two consumers who have exactly the same credit score: I don't know if you're a 640 score on your way to 720 — or are you a 640 headed southwards to 580? It doesn't show me how you're managing your day-to-day financial lifeMichelle Goeppner, Chief Lending Officer Two borrowers can share the same score and be moving in opposite directions. Alternative data helps lenders tell the difference — and put that score in context rather than treating it as the whole story. Start small and layer it in Adopting alternative data doesn't mean overhauling an existing strategy. As Goeppner puts it, it's additive, not a replacement: It's not a rip and replace. You don't have to let go of your existing playbook. It's additive — you layer it in.Michelle Goeppner, Chief Lending Officer Her advice for getting started: Define the problem first. Are you trying to increase approvals, reach more underserved borrowers, or improve decisioning for a specific product? Test before you scale. Revisit loans you've already booked and ask whether alternative data would have changed the outcome — or pilot it on a single product before rolling it out further. Build in governance from day one. Document what changed, where the new data was used, and what results followed. As Goeppner puts it: “Crawl, walk, run. Slow and grow.” More loans without changing the risk profile For Vantage West, the value of that approach has shown up in its lending results. It has been an absolute game changer for us at Vantage West. We have been able to make more loans to our target members, our target segments, without changes to our risk profile.Michelle Goeppner, Chief Lending Officer That distinction matters. The goal isn't approving more loans for its own sake — it's having enough information to recognize good borrowers that traditional data alone would have missed. The result is a fuller picture of the people behind the credit file, and more confidence in deciding who a lender can serve. Explore alternative data with us Alternative data can help lenders add context to traditional credit information for a more complete view of consumers. Experian works with institutions of all sizes to incorporate additional consumer signals into existing lending strategies — strengthening decisioning, managing risk and identifying new opportunities for growth. Learn more Contact us About our experts Michelle Goeppner Chief Lending Officer, Vantage West Credit Union Michelle Goeppner is a dynamic financial services executive with over two decades of experience driving strategic growth, product innovation, and operational excellence across leading credit unions and financial institutions. Currently serving as the Chief Lending Officer at Vantage West Credit Union, Michelle leads the strategic vision for multi-billion-dollar consumer loan and deposit portfolios, as a member of the Executive Coalition. Her expertise spans consumer lending, product management, integrated marketing, and talent development, with a proven track record of leveraging fintech partnerships, automation, and data-driven strategies to optimize portfolio performance and member engagement. Throughout her career, Michelle has held pivotal leadership roles in organizations such as Alliant Credit Union and Discover Financial Services. She is recognized for her collaborative approach, detail-oriented execution, and commitment to developing future female leaders. Michelle’s contributions include founding Alliant’s Women’s Resource Group, serving on advisory councils and boards, and earning multiple industry awards for excellence and innovation. She holds an Executive Certification in Product Management from UC Berkeley, a Master of Science in Integrated Marketing Communications from Roosevelt University, and a Bachelor of Science in Marketing from Northern Illinois University. David Elmore Vice President of Fintech Sales, Experian David Elmore leads a team of fintech sales professionals at Experian focused on helping fintech organizations drive responsible, scalable growth through data-driven analytics and decisioning. With more than 20 years in financial services — a decade of it focused on fintech — he brings deep expertise in applying traditional and alternative data across the customer lifecycle. David and his team partner with fintech leaders to navigate opportunities across acquisition, underwriting, portfolio management, and collections, balancing innovation, risk, and trust.

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Every retailer invests heavily to drive shoppers to its website during the holidays. But after months of planning and thousands to millions of dollars spent on marketing, every customer journey comes down to one critical moment: Checkout.  Today, fraud prevention means protecting revenue by ensuring legitimate customers complete their purchase, not just stopping bad actors.  That's becoming increasingly important as holiday shopping evolves. In 2025, U.S. online holiday spending reached a record $257.8 billion,1 with shoppers spreading their purchases across months rather than just Black Friday and Cyber Monday. Every approval and every false decline has a bigger business impact than ever.  Trust is becoming a conversion strategy  Consumers expect retailers to protect them from fraud, but they don't want that protection to slow them down. That's where a significant opportunity exists.  Experian research found that 52% of consumers expect retailers to protect them online, yet only 19% trust them to do so.2 Meanwhile, payment providers enjoy a positive trust gap because security happens quietly in the background with minimal friction.   The takeaway? Customers don't equate more authentication with more trust. Instead, they equate less friction with better experiences.  Learn how retailers can improve approvals, reduce false declines and build customer trust through layered identity intelligence.  Download the white paper Invisible security is the future of checkout  Modern identity verification, behavioral analytics and account intelligence allow retailers to recognize trusted customers behind the scenes – reserving step-up authentication only for higher-risk transactions. Why does that matter? Because friction is measurable.  Research from Experian and cited in our white paper, shows that 16% of online transactions encounter suspected fraud friction, and 70% of that friction is unnecessary.3 Meanwhile, 25% of consumers abandon the purchase after experiencing onboarding friction, choosing a competitor instead.   Reducing unnecessary friction isn't just good customer experience; it's good business.  One retailer that used Experian's account ownership verification and identity intelligence captured more than $8 million in additional monthly revenue by improving auto-approval strategies and reducing customer friction.   Learn how to protect revenue, not just prevent fraud As holiday traffic ramps up, retailers have an opportunity to rethink checkout as more than a fraud control. It's a revenue engine. Our latest white paper explores how layered identity strategies can help retailers improve approvals, reduce false declines and deliver the frictionless experiences customers increasingly expect.  Download the full white paper to learn how invisible security can help strengthen customer trust while maximizing holiday conversion.  Download now

Every year, consumers say they'll spend less during the holidays. Every year, many do the opposite. Ahead of the 2025 holiday shopping season, 57% of consumers told Deloitte they expected the economy to weaken, the most pessimistic outlook recorded in the survey's history. Planned holiday spending was down 10%. Yet by the end of the season, online holiday sales reached a record $257.8 billion, up 6.8% year over year. Credit card balances climbed to $1.28 trillion, and Buy Now, Pay Later (BNPL) financing surpassed $20 billion during the holiday period. For lenders, the takeaway is to identify and engage the right consumers before the holidays were best equipped to capture that spending while effectively managing risk. As the 2026 holiday season approaches, Experian's latest market insights suggest that while credit performance appears relatively stable at the portfolio level, important shifts beneath the surface are changing how lenders should evaluate both opportunity and risk. Holiday shopping season 2026 Winning top of wallet before the holiday swipe Download the white paper now Holiday lending decisions happen long before the holidays It’s been observed that the holiday shopping season has expanded – beginning before Black Friday – over recent years. While Cyber Week continues to generate headlines, holiday spending is becoming more distributed throughout the quarter. For lenders, that means strategies must be in place before peak shopping begins. Credit line increases, portfolio reviews, acquisition strategies and risk segmentation completed in late summer often determine how much holiday spending an institution can safely capture. At the same time, early signs of credit deterioration are emerging faster than traditional portfolio metrics suggest reinforcing the importance of identifying emerging portfolio risk early rather than relying solely on broad portfolio performance indicators. Income is becoming a stronger predictor of credit performance One of the most notable shifts in today's lending environment is the growing relationship between income and future credit performance. Experian's data suggests the market is becoming increasingly polarized. The population earning more than $250,000 annually has more than doubled since 2023, but more than one-quarter of those consumers have since moved into lower income brackets, often following retirement or job loss. Meanwhile, consumers earning less than $50,000 annually show relatively little income mobility, with approximately 85% remaining in the same income band year-over-year. These trends highlight an important reality: a credit score alone may no longer provide a complete picture of borrower risk. Four priorities before peak holiday spending With only a short window before holiday borrowing accelerates, lenders have an opportunity to strengthen both growth and risk strategies. Key areas of focus include: Refine acquisition strategies Move beyond score-only targeting by incorporating verified income, cash flow and existing credit relationships to identify qualified borrowers. Optimize existing portfolios Identify customers demonstrating positive credit migration and proactively evaluate opportunities to increase credit lines before peak spending begins. Monitor emerging credit risks Use early-stage delinquency indicators and behavioral signals to identify potential performance issues before losses accelerate. Strengthen fraud management and prevention Seasonal account openings and increased transaction volumes create greater fraud exposure. Identity verification, synthetic identity detection and dormant account monitoring remain critical during high-volume acquisition periods. Preparing for the holiday shopping season ahead The 2025 holiday season demonstrated that consumer spending decisions don't always align with consumer sentiment. How does that translate for the 2026 shopping season? For lenders, success will depend less on reacting to spending trends in November and more on making informed credit decisions months earlier. As consumer financial behavior continues to evolve, combining traditional credit data with income, cash flow and alternative data can provide a more complete understanding of both opportunity and risk. Institutions that incorporate these broader insights into acquisition, portfolio management and fraud strategies will be better positioned to grow responsibly during one of the year's most active lending periods. Ready to learn more? Access the full white paper

The why behind Experian's acquisition of AtData What happens when a comprehensive email intelligence database joins a global leader in data, analytics and fraud prevention? The acquisition of AtData adds 25+ years of building a complete view of email as an identity signal. Financial institutions can recognize, engage and protect customers unlocking a new standard for the way their teams work and the customer experience. That's what Experian's acquisition of AtData delivers. How we got here Not all email addresses tell the same story. Some are newly created. Some exhibit bot-like patterns. Some are inconsistent with every other signal you have about that person. Imagine a real customer. You have a job. You shop online. You have a primary email from your employer, a personal Gmail you've used for 15 years, and an old Yahoo address you still use for shopping because you've been using it since college. You're an engaged customer who interacts with brands, makes purchases and pays bills on time. But each system sees a different version of you. When you apply for credit, the lender sees one email. When you shop, the retailer sees another. When you sign up for a service, you might use the third. For financial institutions: You slow down the approval process to manually verify identity or approve applicants without the full picture. For retailers: You can't tell which version of "customer" is the most engaged, so you either over-mail or under-serve. For fraud systems: Sees a new account created under one email and flags it as suspicious because it doesn't have the history. This was the original problem AtData was built to solve in 1999. Twenty-five years later, that problem didn’t go away, it became more complex. Email fragmentation and device sharing are more common, and identity theft is more sophisticated. Capabilities that now work together Experian has built sophisticated identity and fraud solutions backed by consumer data resources and decades of expertise in credit and risk. AtData brought the ability to assess whether an email address is trustworthy, reachable and consistent—at scale, in real time. Experian is now making email intelligence foundational, not optional. This matters for: Fraud prevention and risk management: Distinguishing a returning customer from a new threat. Knowing whether an email is newly created, exhibiting bot-like patterns or inconsistent with other identities is crucial. Compliance: Building audit trails that can explain identity decisions. Email data history and behavioral signals create the documentation needed to defend your decisions. Credit: Verifying identity in a world where traditional signals are shifting. Email signals provide a persistent, durable identifier that confirms who someone actually is. Marketing: Reaching the right person across email, mail and digital channels. Email intelligence reveals which addresses are actively engaged and reachable. Research shows email remains one of the highest-ROI marketing channels outperforming paid search and social advertising1. The problem every marketer faces: You end up burning budget on addresses that bounce, are unmonitored or are associated with users who never open mail. For credit marketing specifically, email enables faster, more targeted delivery of firm offers across channels, something that's increasingly important in a post-cookie world. "Email is a persistent identifier in a fragmented world. It's what connects a person's postal address, phones, devices, behaviors—the full picture of who they are. By embedding that into our infrastructure, we're not just adding another data point. We're fundamentally improving how businesses understand who their customers are."- Ashley Knight, Senior Vice President, Financial Services and Data Why now? AI is reshaping how decisions are made in every industry. Models are getting faster, more automated and more embedded in core workflows. But AI is only as effective as the data behind it. Fragmented data + fast models = faster, larger-scale misclassifications. In an era of synthetic identities, AI agents, deepfakes and AI-generated activity, the value of durable, persistent, real-world data signals has increased dramatically. Deloitte’s Center for Financial Services projects that generative AI could drive fraud losses in the U.S. up to $40 billion by 2027, a 32% growth rate since 2023. And email sits at the center of it with business email compromise already being one of the most common and costly fraud types. People change phones, move homes and swap devices, but they often hold onto their email for years. That's the signal that protects your business, and the one we've built into the core of how we help you make decisions with confidence. View the press release here

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Fintech growth is returning, but growth alone is no longer enough to separate market leaders from the rest. The next stage of fintech will be shaped by how well organizations understand the consumers they serve, how accurately they assess risk and how consistently they make decisions across the customer lifecycle. That requires more than speed, more data or a single new model. It requires a unified view of the consumer that brings together identity, credit and behavioral signals into one decisioning strategy. Experian’s 2026 State of Fintech Report identifies partnerships, data and fraud as three forces shaping the next phase of fintech growth. The report also makes a clear point: institutions that integrate these forces into cohesive strategies will be better positioned to grow with confidence. For many fintechs, the challenge is not a lack of innovation. It is the increasing complexity of turning innovation into scalable, explainable and profitable growth. Fintech organizations span a wide range of maturity, from early-stage startups to scaled lenders, and many are experimenting with new products, technologies and customer engagement models at the same time. That creates opportunity, but it also creates pressure to make more disciplined decisions. The market is rewarding institutions that connect product strategy, risk management and customer experience in a more coordinated way. This is why the unified consumer view is becoming so important. It helps fintechs turn fragmented signals into consistent decisions that support both growth and resilience. Why a unified consumer view matters now A unified consumer view means bringing together the signals that define a customer’s identity, credit behavior, financial capacity and risk profile. It moves fintechs away from isolated decision points and toward a more connected picture of the customer across origination, account management and servicing. This matters because consumer behavior is becoming more fluid, fraud is becoming more sophisticated and product strategies are becoming more specialized. A customer may appear strong through one lens and risky through another. An application may pass an onboarding check, but later show behavior that suggests emerging fraud or repayment stress. Without a connected view, those signals may stay trapped in different systems or teams. The 2026 State of Fintech Report highlights this shift across several areas. Fintechs are managing credit cards and unsecured personal loans with greater precision, recognizing that each product requires different strategies and risk controls. Credit cards require ongoing account management because exposure continues after origination. Unsecured personal loans follow a fixed repayment structure, which makes underwriting precision especially important at the point of origination. These differences show why a one-size-fits-all strategy cannot support modern fintech growth. A unified consumer view helps lenders apply the right data, risk framework and customer strategy to the right product at the right time. Siloed decisions create blind spots Many fintechs already use multiple sources of data. They may rely on traditional credit data, alternative data, fraud tools, cash flow information, identity verification and internal account performance data. If those signals are managed separately, the organization may still lack a clear view of the customer. Data can become fragmented. Risk teams can reach different conclusions than fraud teams. Product teams can pursue growth without a full understanding of emerging portfolio pressure. The State of Fintech Report points out that fintech competition is increasingly defined by the ability to align data strategies with decision frameworks. That means data is not just a support function. It is becoming central to growth, risk management and customer experience. Organizations are investing in richer datasets and more advanced analytics, but the differentiator is how effectively those inputs are operationalized. This is where many fintechs still have work to do. The value comes not from any single dataset, but from how signals are layered, interpreted and applied together. For example, a lender may understand a consumer’s credit score, but that does not always reveal broader financial behavior. Cash flow data may add insight into income and expenses, but it needs to be categorized and normalized to support reliable decisions. Identity signals may help detect fraud, but they become more powerful when combined with credit and behavioral data. A unified view brings these inputs together so fintechs can better determine whether a customer represents a growth opportunity, a fraud risk, an emerging credit risk or a borrower who needs a different product experience. Product complexity requires better decisioning The need for a unified consumer view becomes even clearer when looking at how fintechs manage different credit products. Fintech lenders continue to originate approximately 1.5 unsecured personal loans for every one credit card, which reinforces the importance of both products within portfolio strategy. Credit card originations continue to grow moderately while unsecured personal loan originations have slowed after tighter lending standards. These patterns suggest that fintechs are not simply shifting from one product to another. They are becoming more mature in how they manage each product based on its structure, risk profile and consumer use case. Credit cards and installment loans behave differently. Credit cards introduce ongoing exposure and require active account management, line management and monitoring of utilization behavior. Unsecured personal loans carry fixed terms and structured repayment schedules, which makes origination quality especially important. For fintechs, this means product strategy and risk strategy must be tightly connected. The same consumer may need to be evaluated differently depending on the product, loan amount, repayment expectations and observed behavior. A unified consumer view gives lenders the context needed to make those differences actionable. This is also where segmentation becomes more sophisticated. The State of Fintech Report’s loan segmentation framework connects strategy, risk and data advantage across small-dollar, mid-tier and large-ticket loans. Small-dollar lending can support thin-file acquisition, but may require alternative data and stronger identity visibility. Mid-tier lending may involve debt consolidation and cash flow pressure, where transaction insights and trended data can be particularly useful. Large-ticket lending can support higher-value growth, but it also creates greater exposure and may require a fuller combination of credit, fraud and identity signals. This kind of framework helps fintechs align product strategy with risk and data strategy in a more deliberate way. Fraud is making the unified view even more urgent Fraud is another reason fintechs need to move beyond siloed decisioning. Fraud is becoming more complex across the customer lifecycle. Synthetic identities, first-party misuse and AI-driven threats are reshaping the risk landscape. Traditional controls that focus primarily on onboarding are no longer enough. Effective strategies now require continuous monitoring across account access, transactions and servicing. That shift changes how fintechs should think about customer intelligence. Fraud is no longer something that only happens at the point of application. It can emerge later through account behavior, suspicious activity or patterns that look normal when viewed in isolation. Advanced identity signals, including email intelligence, are becoming more central to fraud prevention because they add context that traditional data may not capture. The report also highlights Experian’s acquisition of AtData as part of a broader recognition that email-based identity signals represent a critical layer in digital identity and fraud detection.   The takeaway for fintech leaders is clear. Identity, fraud and credit risk cannot be treated as separate problems. A customer who appears creditworthy may still present identity risk. A fraud signal may also influence credit exposure. A repayment pattern may reflect financial stress, misuse or both. A unified view helps lenders evaluate these signals together so they can make decisions with more confidence and less friction for legitimate customers. Trust is becoming a growth strategy Trust has always mattered in financial services, but fintechs now need to think about trust as a measurable part of decisioning. Customers expect fast applications, seamless experiences and fair outcomes. Regulators and internal governance teams expect transparency, explainability and consistency. Business leaders expect growth without unnecessary exposure. These expectations are difficult to meet when data and decisions are fragmented. The State of Fintech Report’s 2026 action playbook identifies trust as a function of decision accuracy, identity confidence and customer transparency. That framing is important because it moves the conversation beyond speed alone. A fast decision is not valuable if it approves the wrong customer, declines a good customer or creates unnecessary friction in the wrong place. Fintechs should evaluate where friction improves outcomes, such as preventing fraud or identifying risk, and where it creates unnecessary loss of good customers. For many lenders, the path forward is not removing friction everywhere. It is applying the right level of friction at the right moment based on a clearer view of the consumer. This is where unified decisioning becomes a competitive advantage. It allows fintechs to create experiences that feel faster and more relevant while still protecting the portfolio. It supports better segmentation, more informed offers and more consistent risk treatment. It also gives teams a shared understanding of why decisions are made, which is essential as AI and automation become more embedded in lending workflows. What should fintech leaders do next? A unified view of the consumer is not built by adding one more tool or one more dataset. It requires a decisioning strategy that connects data, analytics, fraud, identity and product objectives. Fintech leaders should start by evaluating where their current decisioning frameworks fall short. Are credit and fraud signals looked at together? Are cash flow insights being used consistently? Are identity signals monitored after account opening? Are decisions explainable across teams and channels? The 2026 State of Fintech Report recommends prioritizing experimentation tied to measurable decision lift and model performance. This means testing combinations of credit, alternative, cash flow and identity signals to determine where incremental data improves response rates, approval rates, early-loss reduction and fraud mitigation. It also means treating data and decisioning as connected priorities, with a focus on signal quality, integration and measurable impact. The goal is not to collect more inputs for the sake of volume. The goal is to understand which signals improve outcomes and how those signals should be applied at scale. For fintechs, this is the next competitive frontier. Growth will continue to depend on product innovation, customer acquisition and speed to market. But the lenders that separate themselves will be the ones that can connect those growth priorities to a stronger decisioning foundation. That requires a consumer view that is broader than a credit profile, deeper than a fraud check and more actionable than a data warehouse. It requires a unified framework that helps lenders understand who the customer is, how the customer behaves and how risk may change over time. Download the 2026 State of Fintech Report The next phase of fintech will not be defined by a single innovation. It will be defined by the ability to connect identity, credit and behavioral data into more confident decisions across the full customer lifecycle. Fintechs that build this unified view will be better positioned to grow, manage risk and strengthen customer trust in a more complex market. To explore the trends shaping fintech growth and decisioning in 2026, download Experian’s 2026 State of Fintech Report. Read now To learn more about how Experian partners with fintechs, visit www.experian.com/fintech. Learn more

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