The Financial Industry Regulatory Authority (FINRA) is an independent, non-governmental organization responsible for protecting investors by ensuring that the U.S. securities markets operate in a fair and honest manner. FINRA oversees 12 markets and exchanges, 3700 firms and more than 600,000 brokers. FINRA deters misconduct by enforcing rules, detecting and preventing wrongdoing in the U.S. markets, and disciplining members who break the rules.
To protect investors, FINRA is involved in identifying fraud schemes in the market. It does so by surveilling 99 percent of the equity markets and approximately 70 percent of the options markets. To do this, FINRA captures all transaction data—more than 100 billion trading events per day—from the various securities markets. FINRA then uses machine-learning algorithms to identify fraudulent patterns of behavior for investigation. Unfortunately, their legacy architect created a number of challenges that prevented them from effectively and efficiently monitoring the security markets. Challenges included:
Databricks provides FINRA with a Unified Data 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. With Databricks, teams can quickly iterate on ML models and scale detection efforts to 100’s of billions of market events per day. As a result, FINRA has significantly improved fraud prevention leading to a more secure financial future for investors in the US.
With Databricks, we have one cohesive end-to-end process with one single unified team working on protecting the securities markets.