Experian Assistant Leading the Way in Financial Services: Wins Big Innovation Award

Lending is becoming more automated, more connected and increasingly powered by artificial intelligence. But across many lending processes, a significant gap remains between that vision and today’s reality. New research from Celent, a global research and advisory firm for the financial services industry, highlights that gap and how quickly financial institutions are moving to close it. According to the Celent 2026 Enterprise Decision Intelligence Survey, 82% of lenders plan to increase their spending on decision intelligence technology over the next two years. By 2028, Celent projects decision intelligence adoption will increase 32 percentage points in mortgage lending and 28 points in consumer lending, with more than half of lenders expected to use it across key lending processes. The automation gap creates an opportunity Automation is already well established in some areas of lending. Celent found that 68% of credit card decisioning is fully or mostly automated today, compared with 31% of small business term loan decisioning and just 19% for mortgages. Manual processes and fragmented technology can increase costs, slow decisions and make credit risk and fraud management more complex. For borrowers, they can mean additional friction and longer waits. Closing that gap requires more than automating individual steps. Financial institutions increasingly need to connect data, analytics, models, decisioning and workflows across the credit lifecycle. Decision intelligence moves into the mainstream Celent defines decision intelligence as an integrated approach that combines data, software, rules management systems and artificial intelligence to optimize decision making. The research finds that decision intelligence platforms have entered the mainstream as lenders look to connect capabilities that have traditionally operated separately. More than eight in 10 lenders plan to increase their investment in decision intelligence technology over the next two years. Data management is also among their leading investment priorities, reflecting the importance of a strong foundation for automation and AI. The result is a shift from automating individual lending decisions toward creating a connected decisioning environment across the credit lifecycle. AI makes trust even more important AI can accelerate this transformation by helping financial institutions extract more value from data, improve models and analytics, and make decisions faster. As AI evolves toward agentic systems capable of acting across complex workflows, the opportunity to automate more of the lending lifecycle grows. But so does the importance of trust. Celent finds financial institutions are prioritizing data integrity, lineage, privacy and control, along with secure deployment, explainability and auditability. As AI moves deeper into lending, institutions need to understand the data being used and how decisions are reached and governed. They also need ways to connect AI agents with trusted data, analytics and decisioning while maintaining governance, controls, auditability and human oversight. From decision intelligence to agentic AI Experian is helping financial institutions address these needs through the Experian Ascend Platform™, which brings together trusted data, advanced analytics, model development and deployment, decisioning, and fraud and identity capabilities in an integrated environment. Decisioning on the Experian Ascend Platform™ provides a flexible, component based automated decision engine designed to help lenders operationalize data, models and strategies across the credit lifecycle and turn intelligence into faster, more informed decisions at scale. Experian’s Agent Operating System™ builds on that foundation with a trusted agentic AI layer within the Experian Ascend Platform. It is designed to enable AI agents from Experian, financial institutions and partners to work together through a common trust, semantic and orchestration layer, with governance, auditability and human oversight built in. This creates a path from using AI for individual tasks toward orchestrating more complex workflows. The Agent Operating System is designed to connect agents and capabilities across data, models and workflows, allowing organizations to begin with targeted use cases and expand over time. By connecting data, analytics, decisioning, workflow and AI, financial institutions can create a common foundation for continuously improving decisions while laying the groundwork for trusted agentic automation. As Craig Focardi, Principal Analyst, Banking from Celent explains: “Decision intelligence is evolving from a point solution into enterprise infrastructure. As lenders extend these capabilities across products and the credit lifecycle, the opportunity is to create a common foundation that connects data, decisioning, workflow and AI, enabling institutions to make better decisions faster and continuously improve how those decisions are made.” The next phase of lending automation will be about more than applying AI to existing processes. It will be about creating a trusted, connected environment where data, analytics, decision intelligence and AI agents can work together across the credit lifecycle. For financial institutions, that offers a path toward more intelligent, orchestrated workflows while maintaining the governance, transparency and human oversight needed to operationalize AI confidently at scale. Source: Celent 2026 Enterprise Decision Intelligence Survey, May 2026.

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.

This week marks the start of International Fraud Awareness Week, a global initiative dedicated to raising awareness about fraud prevention and empowering businesses and individuals to take proactive steps against financial crime. At Experian, we’re dedicated to helping organizations and consumers stay ahead of fraudsters and anticipate future threats. That’s why I’m excited to announce the launch of a new Experian DataTalk podcast series: Fraud Frontlines. This series will feature conversations between myself and industry experts and innovators on the latest fraud trends and strategies to mitigate risk. Introducing DataTalk’s Fraud Frontlines Series: Insights from Episode One In our inaugural Fraud Frontlines episode, I sat down with Nash Ali, Experian’s VP of Fraud Strategy, to discuss how fintech innovation has reshaped the fraud landscape and what that means for the future. As financial technology continues to revolutionize how people transact online, it’s also changing how fraudsters operate. The rise of GenAI and automated scams has introduced a new level of sophistication that demands equally advanced defenses. Key Themes & Insights: AI vs. AI: The New Battleground: Fraudsters are weaponizing GenAI to create sophisticated scams. What’s the way forward? Deploying AI-powered defenses that detect anomalies, identify malicious bots, and uncover coordinated fraud rings in real time. Smart Friction, Not Roadblocks: Consumers demand security without sacrificing convenience. Leading fintechs are embracing risk-based orchestration, applying adaptive controls tailored to user behavior instead of rigid authentication. Behavioral Biometrics to Combat Bots: Experian’s behavioral analytics powered by NeuroID enable the detection of bots and are evolving to recognize and distinguish between good agents and fraudulent agents. This capability analyzes multiple new digital and behavioral signals without adding friction to the user experience. The Rise of Agentic AI: Transactions are beginning to involve autonomous agents acting on behalf of humans. Businesses must prepare to authenticate these agents, validate the human and the intent behind them and distinguish automation from bad actors. Fintechs have enabled great new digital experiences, rapid response rates and a focus on user convenience. This digital transformation has also led to new attack surfaces for fraudsters. Traditional industry players and fintechs alike are joining forces to fight these new types of fraud. The challenges are complex, but the opportunities to innovate have never been greater. These are exciting times for those shaping a safer digital economy. I invite you to listen or watch the episode and stay tuned for new episodes and ongoing insights into fraud trends and prevention strategies. Listen to the episode Watch on YouTube Learn more about Experian’s fraud prevention solutions