When sales networks do not function, organizations experience losses and accounting troubles. Detecting fraud and reducing losses is a key goal for audit managers of retail companies. Detailed analysis of available information is difficult and expensive. The number of transactions is huge, and the size of the network and the volume of detail that can be recorded (including movement of the drawers of the boxes in the stores) make the job more difficult.
It’s important to quickly identify and stop improper behavior, but it’s also necessary to identify new behavior and risks that were not previously associated with losses.
Fraud Detection identifies risks of fraud or improper behavior resulting in losses. Through a mix of business rules, anomaly detection and predictive analytics that identify risky behavior, the application can assign a fraud risk score to any event.