Case study

New Risk Detection – Retail Banking

By SymphonyAI team
 

SensaAML™ uses state-of-the-art AI and intuitive UI to organize large amounts of data based on similarity to reveal hidden relationships and groups of customers with deep meaning. These shapes help non-data science users easily interact with large data sets to identify patterns, anomalies, and hotspots like in our case study below using retail banking data.

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