Experian Innovation Lab Celebrates 15 Years of Transforming Industries

I recently had the opportunity to attend Money20/20 in Las Vegas, where one theme dominated nearly every conversation: artificial intelligence is reshaping financial services. But amid all the excitement around algorithms and technology, the data that powers it all often gets overlooked. AI is only as effective and trustworthy as the data behind it. For financial institutions, high-quality, differentiated data determines how confidently they can assess creditworthiness, detect anomalies, and manage risk. Ultimately, it’s data that allows lenders to innovate responsibly, personalize experiences, and deliver better outcomes for consumers. At Experian, we see measurable impact when institutions strengthen their data foundations. Our clients are making faster lending decisions, reducing default rates, and expanding access to credit through responsible, data-driven innovation. Turning Better Data Into Better Decisions Experian’s industry-leading core credit data, alternative credit data, cash flow insights, and more gives lenders a more holistic view of financial health. These differentiated data assets, combined with our history or continuous innovation, enable AI systems that are more transparent, explainable, and fair. On example of this is our Experian Assistant for Model Risk Management, a new AI-powered capability that automates the most complex and time-intensive areas of compliance. This solution continuously analyzes model documentation, detects model drift, and recommends corrective actions in real time. Ultimately, this is transforming compliance from a barrier to a driver of ROI and innovation that benefits consumers and businesses. Bridging the Gap Between Innovation and Compliance While at Money20/20, I had the opportunity to share more about how we are leveraging differentiated data and technology to help make room for innovation during an interview with Fintech Futures. Reporter Tyler Pathe and I discussed the fact that many institutions still rely on manual processes for compliance — with some involving up to 50 people just to document and validate models. That level of inefficiency slows progress and increases operational risk. Through automation and AI, and differentiated data at our foundation, we are changing this narrative and helping our clients move faster and innovate with confidence. You can tune into my full interview with Fintech Futures below.

As we approach 2026, artificial intelligence is no longer just a tool for innovation—it’s a weapon in the hands of cybercriminals. Our 13th Annual Data Breach Industry Forecast, released today, highlights how AI is poised to redefine the cybersecurity landscape, introducing a new era of highly personalized, persistent, and technologically advanced attacks. We outline six key predictions, with AI emerging as the central theme. From synthetic identities and autonomous AI agents to shape-shifting malware and even vulnerabilities in brain-computer interfaces, the forecast paints a picture of a threat environment that’s evolving faster than many organizations can keep up with. The stakes are high. In the first half of 2025 alone, more than 8,000 global data breaches exposed approximately 345 million records [1]. Experian’s clients in the United States, United Kingdom, and Canada were among the hardest hit. Consumers Are Feeling the Impact To check the pulse of how consumers are feeling about the impact of AI on security, we recently conducted a national survey in the U.S. and UK. The findings reveal growing anxiety around AI-driven threats. In both the U.S. and U.K., more than 80% of respondents expressed concern about AI being used to create fake identities indistinguishable from real people. Millennials appear especially vulnerable, with 1 in 4 reporting identity theft in the past year and nearly a quarter falling victim to phishing attacks. The findings also show a lack of confidence in corporate defenses: 69% of U.S. adults don’t believe their bank or retailer is prepared for AI-driven attacks. 76% believe cybercrime will continue to escalate and become impossible to slow down due to AI. 35% worry about being held personally liable for cybersecurity mistakes at work. Preparing for the AI-Driven Future While the threats are daunting, organizations can turn the tide by adopting AI defensively. Proactive investments in AI-powered threat detection, employee training, and incident response planning will be critical in 2026 and beyond. Experian Data Breach Resolution has more than 20 years of experience helping companies manage a security incident and it’s no different today than it was two decades ago – the same technologies that are being used against us can also be used to protect us. AI can help detect anomalies faster, automate responses, and reduce human error. But it requires investment, training, and preparation. To review all six predictions, download the paper here. Understanding what’s coming is the first step toward building a stronger, more resilient cybersecurity strategy. [1] Data Breach Statistics 2025: Key Trends, Costs & Risks Revealed, SQ Magazine, October 6, 2025

Fraud impacts more than just the bottom line. It affects confidence, relationships, and the sense of security that every business and customer depends on. At Experian, helping to rebuild that trust through data and technology has become part of who we are. That commitment was recently recognized when our Commercial First Party Fraud Score received the Gold Award for Banking Fraud Prevention in Juniper Research’s 2025 Fintech & Payments Awards. First party fraud is one of the most difficult types of financial crime to uncover. It often begins with what looks like a legitimate credit application, only to turn into a default or a “bust out” once credit has been extended. The losses can be significant, but what makes this type of fraud so challenging is how well it hides in plain sight. Our teams developed a new model that uses advanced machine learning and blends consumer and business insights. The Commercial First Party Fraud Score analyzes credit patterns and behavioral data from more than 250 million consumer records. It spots early warning signs that traditional credit models often miss, giving lenders a clearer picture of who they are working with from the start. In testing, the model identified 22 percent more fraudulent applications and 33 percent more high-risk applicants compared with older systems. This improvement helps organizations reduce costs, speed up onboarding, and better serve genuine customers. The recognition from Juniper Research is more than an award. It represents progress toward a safer and more transparent financial system. By combining innovation, data, and purpose, we continue to help businesses make smarter choices and protect the trust that keeps the economy moving. Learn more about the Juniper Research Fintech & Payments Awards here.