Oracle Financial Services is supercharging its Investigation Hub Cloud Service with the addition of a broad class of AI agents and agentic workflows that enable financial firms to automate investigative processes needed to uncover complex patterns and fight financial crime.

The agents help improve the overall quality and speed of reviewing suspicious activity by using generative AI-driven narratives to supplement investigators' own analysis. This can save valuable time and resources by offloading many traditionally manual tasks and enabling investigators to focus their time on the most pressing leads. These new capabilities are available globally for financial institutions of all sizes using the Investigation Hub crime and case management solution.

"The addition of agentic AI capabilities to our Investigation Hub Cloud Service represents a paradigm shift in financial crime investigations," said Jason Somrak, head of financial crime product strategy, Oracle Financial Services. "Our unique generative AI approach follows investigative plans, collects evidence, and recommends actions while providing investigators with robust narratives documenting the findings. This enables firms to drive consistency in decision making and thoroughly investigate all risks automatically while realizing massive operational efficiencies."

Combatting crime with agentic AI
Financial institutions face mounting pressure to identify and combat increasingly sophisticated financial crime schemes while managing regulatory scrutiny. Traditional investigative processes often rely on tedious manual data collection and analysis that can be slow, resource-intensive, and prone to human error.

While some solutions employ AI chatbots that require investigators to ask the right questions in the right way, Oracle Financial Services delivers multiple AI agents that are designed to surface key insights, collect evidence, recommend decisions, and generate comprehensive alert narratives. This automated approach helps eliminate inconsistencies caused by variations in user queries and helps deliver more consistent and reliable information for investigative analysts.

These agents, driven by generative AI, can be leveraged to analyze alert information, including matches between customer data and sanction lists. From there, they can be used to automatically create compelling narratives that summarize the key details of each alert, providing financial crime and compliance investigators with relevant information to better conduct a thorough analysis and make data-informed decisions.