Best execution compliance automation: towards an equities compliance workstation

Purpose - Forthcoming requirements in MiFID and RegNMS mean that buy‐side and sell‐side firms need to find ways of showing regulators that they are sifting through their trading volumes in a justifiable, methodical manner looking for anomalous trades and investigating them, in order to prove “best execution”. The objective was to see if a SVM/DAPR approach could help identify equity trade anomalies for compliance investigation. Design/methodology/approach - A major stock exchange, a computer systems supplier, four brokers and a statistical firm undertook a cooperative research project to determine whether automated statistical processing of trade and order information could provide a tighter focus on the most likely trades for best execution compliance investigation. Findings - The support vector machine approach worked on UK equities and has significant potential for other markets such as foreign exchange, fixed income and commodities. Research limitations/implications - The research has implications for risk professionals as a generic approach to trading anomaly detection. The prototype compliance workstation can be trialed. Originality/value - Automated anomaly detection could transform the role of compliance and risk in financial institutions.