Fraud is the highest-volume financial services workload on the Databricks Platform, and it is the one that punishes a split architecture hardest: real-time scoring sits in one system, ninety days of history in another, and the investigator who has to connect them gets neither governance nor speed. Put an AI agent into that picture and you inherit a second problem, which is proving the model only ever saw what the analyst was allowed to see.

Data and analytics leaders, platform and data engineering teams, and architects responsible for fraud, risk, or governed AI. The session is technical, level 200 to 300. Familiarity with SQL and Python helps, but no lab requires writing code from scratch.