Charchit Bahl

In the evolving landscape of financial crime and regulatory compliance, the financial institutions face increasing pressure to detect and report suspicious activities effectively. The Suspicious Activity Reporting (SAR) Assistant solution leverages advanced Generative AI capabilities to enhance and expedite the investigation of suspicious activities in financial systems. This solution integrates natural language processing (NLP) and machine learning (ML) techniques to automate and streamline the SAR process, ensuring timely and accurate reporting. The Generative AI-driven SAR Assistant utilizes extensive training on diverse datasets, enabling it to recognize complex patterns and anomalies indicative of fraudulent activities. By stitching together domain expertise and Generative AI techniques, the solution can generate detailed, contextually relevant narratives and summaries for SARs. This automation streamlines the SAR process, allowing compliance officers to focus on higher-level investigations and decision-making. This paper aims at a) unveiling the transformative role of Generative AI in the investigation of financial crimes, and b) detailing out the key components of the case investigation system including automated data processing, conversion into data embeddings, vector database set up, information retrieval, case summarization and the eventual AI-based recommendation.