Data Analytics Driven
Second Line of Defence
Delivering Best Practices for achieving market integrity, transparency, and fairness.
A European Investment Bank was looking to develop a comprehensive monitoring solution to assess traders’ use of Cancel, Correct and Amend (CCA).
Unlocking Insights: Trader Behaviour Analytics in Financial Services
Trader Behaviour Analytics is a specialised field within the financial industry that focuses on analysing and understanding the actions and decisions made by traders in the context of their trading activities. It involves the use of data analytics and advanced technology to assess and monitor trader behaviour to ensure compliance with regulatory requirements, ethical standards, and internal trading policies.
Industry: Financial Services, Investment Banking
Designing the Key Risk Indicator (KRI) tests
We developed a series of complex analytics algorithms in order to identify potential suspicious behaviour by individual / groups of traders and to present findings to the Anti-Financial Crime (“AFC”) unit.
These algorithms used the following statistical methods to assess the complete client trade population:
- peer group clustering calculation and identification of 95 and 99 percentiles
- random forest/decision tree analysis
- k-means clustering
The algorithms generated went through a rigorous back-testing regime which applied the each statistical method to a set of real transaction flow data and a set of control data to test the efficacy of the models developed.