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In this session, we look specifically at graphs within the financial services industry. We review the types of data typically available within a bank, illustrate the graphs formed from that data, and discuss the use cases those graphs enable and support.
Use cases presented include anti-money laundering as well as fraud detection and prevention, including its integration with artificial intelligence (AI) and machine learning technologies. We also explore use cases on regulatory compliance, customer 360 views, master data management (MDM), and identity and access management (IAM).
A variety of companies in the industry already utilize Neo4j’s database, such as Lending Club for network and information technology (IT), German insurance company Die Bayerische for graph-based search, Cerved for MDM, Wobi for price comparison and real-time recommendation, and UBS for identity and access management.
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