Find new ways to improve fraud detection accuracy and detection time across multiple transaction fraud types (CP, CNP, Debit, Wire, etc)
Use AI to generate new fraud rules
Detect anomalous patterns for individuals, accounts and networks within large data sets
Target different groups and subsets in a tailored approach, comparing different inferences from these subsets with the same inferences from the entire population
Flag specific repetitive fraud groups and deploy counter measures
Build AI models and use custom recipes specifically built for generating features/variables that provide associated information about fraudulent behavior. This data is then available to the fraud investigator who can further slice and dice the data and consume the information intuitively.
Behavior profiling for data networks - IP addresses, buying patterns
Terabytes of data leveraged to deliver high scalability and performance, flexible deployment and integration with other big data frameworks