Case Study: FINRA achieves faster ML-driven fraud detection and streamlined development with Databricks

FINRA - Customer Case Study

FINRA, the Financial Industry Regulatory Authority, works to protect investors by ensuring fair and honest operation of the U.S. securities industry and uses machine learning to detect fraudulent securities trading. Their data science and engineering efforts were hampered by difficult development and debugging, low code modularity and reuse, and long development cycles caused by segmented teams.

Databricks provided a unified, fully managed analytics platform — including infrastructure, Databricks Runtime, and an interactive workspace — that broke down silos, streamlined development, and let teams focus on modeling instead of DevOps. The result was faster iteration, greater reuse of feature libraries, improved collaboration across a single unified team, shortened time to market, and higher operational efficiency.

FINRA

Saman Michael Far

SVP, Technology