• FINRA Addressing Market Risks: HFT, Algo’s, CARDS, CAT & Dark Pools
  • January 10, 2015 | Author: Thomas K. Potter
  • Law Firm: Burr & Forman LLP - Nashville Office
  • Carlo DiFlorio, FINRA’s Chief Risk Officer and Head of Strategy, told the annual meeting of the National Society of Compliance Professionals Monday that FINRA is emphasizing efforts to mitigate market risks, even as it regards US capital-market integrity as at its strongest historically.

    HFT & Algorithmic Trading

    DiFlorio addressed thee initiatives. First, FINRA examiners are focusing on firms’ supervision of HFT and algorithmic trading, including pre-implementation testing and firm-wide “kill switch” procedures when something goes awry.

    Second, FINRA’s Board decided at its September meeting to propose a rule requiring FINRA registration by those who develop, design or significantly modify trading algorithms. The Staff is drafting a proposed rule for comment.

    Third, FINRA is working on additional guidance on existing supervisory obligations for algorithmic trading.

    Market Surveillance & Big Data

    FINRA also is working to boost its market-surveillance capabilities. FINRA’s surveillance systems monitor for 29 cross-market patterns attuned to 55 threat scenarios. When current initiatives are complete, FINRA surveillance will cover 90% of markets.

    Second, FINRA is one of final bidders under consideration by the SEC for a new Consolidated Audit Trail (“CAT”) processor to improve “data mining” of information across markets.

    Third, FINRA is working to increase transparency of dark-pool and other alternative markets, including expanding FINRA’s disclosure of Alternative Trading System (“ATS”) volume data.

    Fourth, FINRA’s second CARDS (comprehensive automated risk data system) proposal is out for comment until December 1. The proposed Rule would standardize and automate a broad range of securities account and transaction data from clearing (and later fully disclosed introducing) firms. It is another effort to assemble more easily mined “big data” for industry-wide surveillance and compliance.