One of the most highly regulated industries all over the world is Financial Industry. No matter what the size of a firm is, there are numerous regulations to comply with to do any business in this vertical. From the annual reports from regulatory enforcement bodies like FINRA in the US and information about the fines levied on firms for non-compliance, we know that non-compliance is a very costly affair which could not only lead to financial loss but also cancellation of license to operate. EagleAi can be used to monitor the patterns around compliance rules to detect any deviations that would warrant further inspection.
In this use case scenario, let us consider a hypothetical but a very plausible scenario where something can go very wrong with compliance of a firm due to innocuous changes in a very complex trading environment. If the firm finds about non-compliance, it has to self report to the regulators and hope for lesser fines. If the regulators find about it, it could have a more severe consequence such as the firm being suspended to trade. A junior developer of a trading firm accidentally removes a critical compliance rule that nets the long and short trading positions of each symbol across all trading accounts and sets whether a sell order for that symbol should go out as ‘Long’ or ‘Short’. Short-Sell orders requires that there is enough borrow-able shares before it can be traded. This went into production with the result that all sell orders went only as Sell Long and none as Sell Short. Further, no one noticed the fact that there were no short sell orders from firm’s trading accounts for over six months until the regulators notices this in their audit. Further investigation revealed that firm was benefiting from these trades with no constraints faced on borrowability of the stock. Regulators fine the firm over $500,000 and bars them from trading on that asset class for over 2 weeks which is estimated to be more than $500,000 thus resulting in more than $1M loss. Further there are news items in famous news papers like Wall Street Journal putting the firm in bad light that causes reputational damages along with financial loss.
This scenario even though is imaginary, could have been real incident that transpired in many of the regulatory findings. There are ways firm can protect themselves from such violations and manage compliance risks better. EagleAi’s TradeWatch Compliance Risk module is one such innovative tool that can be employed to raise alerts when something goes amiss.
EagleAi Compliance Risk module is designed to watch the critical compliance related characteristics of every order and observe the patterns of behavior of each trading entity such as client or trader. For example, for each client it observes the fraction of order flows that a client places as buy vs sell, sell long vs sell short, the type of symbols it places as sell short, gross vs net notional value, notional value on various asset classes etc. All of these traits at both an individual order level and aggregate level forms the knowledge base of EagleAi from which it applies its multiple anomaly detection algorithms. If EagleAi Compliance Risk module was at work in a similar scenario, it would have raised alerts that pinpoints the fact the number of Short Sell orders from the trading account is anomalously low. It further gives more context such as which particular system this problem was detected giving clear information that reduces the time to investigate and fix.
- Introduction to EagleAi TradeWatch
- EagleAi Use Case Series: Fraud Risk – Undetected spoofing practice at a trading firm brings disrepute to the firm along with hefty fines
- EagleAi Use Case Series: Market Data Risk – Bad market data causes a broker to reject orders from a client incorrectly which leads to a financial loss
- EagleAi Use Case Series: Trading Risk – A single order with incompatible instructions from a client caused $100k+ loss in revenues for a major broker