Experian announced the launch of the Agent Operating System, a trusted agentic AI layer within the Experian Ascend Platform, unveiled at Money20/20 Europe. The Experian Agent Operating System is designed to help financial services organizations move successfully beyond AI experimentation and safely scale agentic AI to transform decision-making, customer experiences, and day-to-day operations. It enables AI agents from Experian, clients and partners to work together through a common trust, semantic and orchestration layer, supported by clear controls, auditability and human oversight.

The launch comes as financial services firms accelerate investment in AI but continue to face major barriers to scaling adoption. ServiceNow will be the first partner to integrate with Experian?s Agent Operating System. Through the multi-year partnership, ServiceNow AI agents will connect with Experian?s Ascend Platform, allowing customers to access trusted data, decisioning and governance capabilities within existing enterprise workflows.

Supporting the full lending lifecycle from customer acquisition and fraud detection to credit decisioning, portfolio monitoring, and reporting, Agent Operating System bridges the gap between AI ambition and operational reality. It combines data, analytics, decisioning, and identity with built-in governance, risk management, explainability, and controls to enable trusted complex workflow automation. The Agent Operating System will be available to early adopters later this year, before rolling out to more than 2,300 client solutions globally.

Key capabilities include: A trusted agentic operating layer: Identity, access control, data security, compliance guardrails, monitoring and governance controls that enable AI agents to operate safely across data, models and workflows. Composability: Experian, client-built, and partner agents work together without having to replace existing technology, allowing organizations to start with targeted use cases and progressively evolve toward fully connected, agent-driven workflows. Agent-native decisioning: Purpose-built agents across fraud, identity, credit risk, marketing, analytics, operations and governance that can investigate, orchestrate and optimise workflows, rather than simply respond to prompts.

Embedded governance by design: Model risk management, explainability, audit trails, monitoring and policy enforcement built into agentic workflows to support compliant AI at enterprise scale. Productivity at scale, with human oversight: Automation of investigation, strategy execution, insight generation, documentation and monitoring, with human-in-the-loop validation for complex decisions and high-impact outcomes.