A German bank wants to prevent fraud at an early stage in the course of introducing a new credit product. Until now, there has been no possibility to examine the relationships between customers, products and transactions carried out for suspicious networks and patterns (fraud detection).
Various data sources and systems are used to generate a "Big Data"Data basis integrated. The data is logically linked and then processed for network analysis. Pattern recognition algorithms are then implemented using R. This enables the detection of conspicuous and unusual relationships, processes and transactions.
A new approach is being developed with Fraud Detection for the Prevention and Fraud detection integrated. Customer relationships are visualised in an interactive and freely navigable app.
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