Customer Case Study: FINRA - Databricks


Customer Case Study


FINRA (Financial industry Regulatory Authority) is a regulatory body charged with protecting investors by ensuring that the U.S. securities industry operates in an honest and fair manner.

Vertical Use Case

  • Leveraging machine learning to detect fraudulent securities trading

Technical Use Case

  • Data Ingest and ETL
  • Machine Learning

The Challenges

  • Difficult development and debugging processes
  • Little modularity and reuse of code caused inefficiencies
  • Long development cycles due to segmented data scientist and engineering teams

The Solution

Databricks provides FINRA with a unified analytics platform that democratizes data and brings previously siloed teams together, cutting down overall time to market, increasing reusability of feature libraries, and improving operational efficiency.

  • Unified analytics platform that includes Infrastructure management, Databricks Runtime, and interactive workspace streamlines the development process for their machine learning models
  • Interactive workspace enables their data science to overcome siloes to iterate faster and collaborate better
  • Fully managed cloud service allows their team to focus on higher-level issues related to the domain of machine learning rather than DevOps work

With the Databricks environment and the notebooks and the richness of the languages and the possibilities of that, we have one cohesive end-to-end process with one single unified team working on these various aspects together.

Saman Michael Far, Senior Vice President of Technology at FINRA