Combat financial fraud with GraphRAG on Amazon Bedrock Knowledge Bases

Financial fraud detection isn’t just important to banks—it’s essential. With global fraud losses surpassing $40 billion annually and sophisticated criminal networks constantly evolving their tactics, financial institutions face an increasingly complex threat landscape. Today’s fraud schemes operate across multiple accounts, institutions, and channels, creating intricate webs designed specifically to evade detection systems.

Financial institutions have invested heavily in detection capabilities, but the core challenge remains: how to connect the dots across fragmented information landscapes where the evidence of fraud exists not within individual documents or transactions, but in the relationships between them.

In this post, we show how to use Amazon Bedrock Knowledge Bases GraphRAG with Amazon Neptune Analytics to build a financial fraud detection solution.

The limitations of traditional RAG systems

In recent years, Retrieval Augmented Generation (RAG) has emerged as a promising approach for building AI systems grounded in organizational knowledge. However, traditional RAG-based ...