How Experian’s AI Agents Are Transforming Financial Services and Fighting Fraud

As artificial intelligence reshapes how businesses and consumers interact with data, global data and technology company Experian is focusing on how to scale innovation without undermining trust. 

From automation and personalization to fraud prevention, AI systems are becoming increasingly embedded across financial services and the broader industry landscape. But as adoption accelerates, Experian says responsible design and governance will be critical to ensuring the technology delivers long-term value. 

“At Experian, our goal is to harness the most advanced AI capabilities in a way that is responsible, secure and transparent,” said Jack Yu, Director at Experian North America Data Labs. “That’s how clients, consumers and regulators gain confidence in the outcomes.” 

Companies across industries are now grappling with how to deploy AI agents: software systems capable of autonomously performing tasks and interacting with other systems. Yu described adoption as both an exploratory and strategic process, requiring careful choices between building proprietary tools and integrating third-party technologies.

“This is uncharted territory for many organizations,” Yu said. “You have to be clear about where you can build differentiated capabilities yourself and where it makes sense to integrate solutions, while still maintaining control and accountability.”

Experian has developed its own AI agent capabilities through Experian Assistant, a real-time conversational tool integrated into its Ascend platform. The assistant enables users to query data, test assumptions and validate models using natural language, significantly reducing the time required to generate insights.

“The technology helps shorten the distance between data and decision-making,” Yu said. “You don’t need to be a data scientist. Product, risk and business teams can interact directly with advanced analytics in a controlled way.”

Behind the interface, Experian structures its AI systems around a multi-layered architecture. Task-focused “worker agents” execute specific actions, while orchestration agents manage interactions across systems and workflows. Oversight is provided by governance agents, which Yu refers to as “sentinels,” designed to monitor behavior, detect anomalies and intervene when systems operate outside defined boundaries.

According to Yu, safeguards around security, compliance and ethical use must be embedded from the outset rather than added later. “You can’t bolt trust on at the end,” he said. “These controls have to be part of the system’s foundation.”

Alongside governance, Experian is using agentic AI to accelerate innovation across its data and technology platforms. Yu said development cycles that previously took weeks or months can now be compressed dramatically to just days or even hours, enabling faster experimentation and deployment. The company is also applying AI to enhance decisioning models and broaden access to financial services in a more inclusive way.

At the same time, AI is playing a defensive role as fraud becomes more sophisticated. Criminal networks are increasingly using generative AI to create synthetic identities and automate attacks at scale. 

“Fraud isn’t a single problem with a single solution,” Yu said. “It requires layered defenses that bring together signals from identity, behavior and context in real time.”

Experian has also invested heavily in workforce readiness, training much of its global employee base in AI and data literacy, including guidance on designing fair, explainable and inclusive systems. 

For Experian, the future of AI adoption will depend as much on trust as on technical capability. 

“Trust is a prerequisite,” he said. “Without it, innovation won’t scale.”

Check out the Experian Exchange series to learn more insights on financial innovation and AI.