Improving Trade Surveillance and Market Manipulation Detection 

The Challenge

The bank’s existing alert review process could not efficiently manage the high volume of daily alerts requiring manual review. The complexity grew exponentially due to operations across multiple asset classes including equities, currencies, debt, futures, options, commodities, precious metals, dark pools energy contracts, and cryptocurrencies traded under different regulators and jurisdictions.

Key challenges included: 

• Poor data quality with missing or inconsistent identifiers
• Missing contextual information due to lack of organizational business structure 
• Ambiguous meaning from unaligned terms across diverse sources
• Limited analytical capabilities for detecting complex manipulation practices 

With regulatory obligations steadily growing, the bank needed a smarter approach to suspicious pattern detection.

The Solution

The bank chose GraphDB to power their Trade Surveillance system. The knowledge graph-based solution provided unique global identifiers, interoperable definitions, domain-specific knowledge expression, and data quality constraints.

The solution used the Financial Industry Business Ontology (FIBO) as foundation for developing suitable hierarchies, enabling interoperability of traded instruments despite multiple identifiers. Interlinked descriptions created necessary context for the Compliance team, allowing interpretation of alerts against organizational structure at the time activities occurred.

The knowledge graph enabled domain-centric compliance views and pattern searches based on GraphDB graph similarity for sophisticated manipulation detection.

The Impact

The Smart Trade Surveillance solution delivered enhanced monitoring capabilities allowing integration of aggregated data to monitor high-volume traders and alert generation. The business unit hierarchies provided improved contextual analysis for better pattern identification. As a result of the solution, data scientists gained an advanced analytical foundation to develop statistical models for suspicious information patterns.

Other key outcomes were the increased operational efficiency in alert reviews and the minimized market manipulation risks through better detection. Across multiple jurisdictions, the solution enhanced regulatory compliance while enabling Compliance teams to monitor and analyze greater numbers of suspected activities.