Combatting Financial Crimes with Graph Databases and Analytics

Presented by

Martin Darling, VP EMEA, TigerGraph

About this talk

Fighting Money Laundering with Machine Learning, Graph Database and Analytics. This session covers how graph analytics creates new business value for banks, credit institutes, insurance providers and other financial institutions. Financial crime is a graph-based opportunity, so this is where graph analytics can help with your endeavours to detect fraudulent activity. Graph analytics will also help with other programmes around customer journey, customer 360, customer segmentation and product recommendation. Learn why 7 out of the top 10 global banks already depend on TigerGraph and graph analytics to detect fraud and to deliver outstanding customer experiences.
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TigerGraph is a platform for advanced analytics and machine learning on connected data. Based on the industry’s first and only distributed native graph database, TigerGraph’s proven technology supports advanced analytics and machine learning applications such as fraud detection, anti-money laundering (AML), entity resolution, customer 360, data operations, digital twin, recommendations, knowledge graph, cybersecurity, supply chain, IoT, and network analysis. This channel showcases TigerGraph's technology and how it helps organisations tap into their data to gain key insights into the business decisions and processes driving innovation, growth and cost optimisation. For more information visit