Transaction / Finance based AML
Transaction-based AML focuses on detecting money laundering through trade finance and commercial transactions by analyzing both financial flows and physical goods delivery. This use case addresses the complexity of understanding multi-disciplinary logistics, linking financial transactions with shipping and customs data, detecting sophisticated trade finance laundering schemes, reducing false positives from legitimate trade, and providing an agile platform to develop new detection methods as criminals adapt their techniques.
The Challenge¶
Financial institutions face significant challenges in transaction-based AML:
- Complexity — Transaction-based laundering, specifically trade finance based laundering, is a difficult problem that enterprises have struggled to tackle not least due to its complexity
- Multi-disciplinary understanding — Understanding the logistics of transactions brings multi-disciplinary challenges in understanding let alone delivering the holistic data tools required to identify the issues
- Dual analysis requirement — Financial flows and the physical delivery of the goods must both be analyzed and monitored
- Regulatory scrutiny — Whilst only about a fifth of global trade is financed, it is an area under great regulatory scrutiny that is very difficult to tackle with the existing technical landscape
- Data fragmentation — Trade finance data is scattered across multiple systems (banking, shipping, customs, etc.)
- Cross-border complexity — International trade involves multiple jurisdictions with varying regulations
- Pattern detection — Criminals adapt their methods, requiring systems that can detect new suspicious patterns
- False positive management — Distinguishing legitimate trade finance from money laundering schemes
However, it is essential to tackle the problem of the illicit exploitation of the system.
Why EKG is Required¶
Enterprise Knowledge Graphs provide powerful capabilities for transaction-based AML:
- Relationship identification — The EKG assists this by identifying relationships between importers, exporters and other related parties
- Cross-system linking — Link across to the financial systems to link to financed and non-financed trade
- Holistic views — These holistic views enable cross silo analytics to identify risks
- Agile platform — Provide an agile platform to develop new tools to identify new potentially illicit behaviours
- Multi-dimensional analysis — Connect financial transactions, shipping data, customs records, and trade documents
- Pattern discovery — Use graph algorithms to identify suspicious patterns across trade finance networks
- Temporal analysis — Track trade finance transactions over time to detect anomalies
Business Value¶
- Enhanced detection — Identify sophisticated trade finance money laundering schemes
- Regulatory compliance — Meet enhanced due diligence requirements for trade finance
- Risk mitigation — Prevent money laundering through trade finance channels
- Operational efficiency — Automate detection of suspicious trade finance patterns
- Cross-silo insights — Gain insights by connecting data across banking, shipping, and customs systems
- Agile response — Quickly develop new detection methods as criminals adapt their techniques