Major Swiss Bank

Developing an ML model to identify potential rogue traders and flag them to minimise risk of financial losses and lower need for regulatory cash reserves

Challenge

• Inability to monitor and identify traders whose behaviour differs from what is expected, resulting in potential monetary and reputational risks for the client

Solution

• Integrated trading data from several sources into a single platform
  Deployed ML techniques to identify potential rogue traders based on their trading behaviour
• Configured an alerting system to flag traders with an elevated risk of rogue trading

Impact

• Able to quickly identify risky traders based on their trading activities, which would have been impossible to do manually
• Minimised rogue trading risk and potential financial losses, lowering the need for regulatory cash reserves