Coursera Spring Sale
40% Off Coursera Plus Annual!
Grab it
Explore how artificial intelligence and graph analytics are revolutionizing the detection of financial crime networks in this 47-minute podcast episode. Discover the intersection of AI, entity resolution, and forensic accounting as veteran practitioner Paco Nathan from Senzing reveals how cutting-edge techniques are uncovering massive money laundering operations, shell company networks, and cybercrime schemes. Learn about real-world cases including the Azerbaijani Laundromat and Danske Bank scandal, where AI helped expose financial flows exceeding entire countries' GDP. Understand how entity resolution serves as the backbone of fraud detection, why accuracy is critical in high-stakes financial crime investigations, and how graph analytics reveal hidden structures in criminal networks. Examine advanced AI tooling including DSPy, BAML, and MLflow for programmatic prompt engineering, plus the emerging field of Graph-RAG that combines retrieval-augmented generation with knowledge graphs. Gain insights into forensic accounting methodologies, fraud tradecraft patterns, synthetic data simulators, and open-source initiatives like OpenSanctions, OpenOwnership, and GLEIF that support transparency efforts. Discover career opportunities for data professionals in combating financial crime while exploring how these same technologies power legitimate business intelligence applications.
