Capital Markets Example: Near Real-Time Fraud Pattern Matching for Trader Surveillance Identify suspicious trading activity • Use time-series based pattern matching to identify unusual patterns of trade activity intra-day
Trader Surveillance
• Potential patterns include front-running, market manipulation, non-compliant positions that expose the firm to undue risk
Combine trading patterns with diverse data • Introspect communications over e-mail and chat channels for corroborating evidence of trade misbehavior
Streamline investigations with iterative, hypothesis-driven query interface • Save valuable time by conducting ad-hoc analysis of trades, cases, alerts, account data
40
Confidential and proprietary. Copyright © 2011 Teradata Corporation.
Characteristics • High rate of new data generation • Granular data • Simultaneous load & query