A bubble matrix helps surveillance analysts detect patterns of manipulation across different teams and through different points in the order chain of command.
Danielle Jett
Product Design
Anomaly Detection
Data visualization to monitor trades and detect bad actors in financial markets
The Problem
Buy-side firms have a legal and ethical obligation to monitor the activities of their traders and portfolio managers for market manipulation. Nasdaq's trade surveillance software uses AI to detect bad actors and keep companies ahead of sophisticated market manipulation techniques. But high alert volume can make it difficult to know where to focus, and without a holistic view of the trading day, surveillance teams can miss manipulation spread across multiple trades and actors.
I used data visualization techniques to help analysts quickly identify where to focus.
With a simple scatter plot visualization, analysts can quickly identify and get a detail view of participants outside a range of normal trading activity.
Some trade anomalies can only be detected on the security level within the context of all trades. This scatter chart allows the analyst to view all trades and uses shading and size as well as extremes along performance metrics to hone in on suspicious activity.