AI News, Combatting retail fraud using a simulator

Combatting retail fraud using a simulator

Retail fraud is common and it is the amount of scams rather than the size of the transactions that create the costly losses.

A woman working at a petrol station was recently sentenced for repeatedly stealing money from the cash register and trying to cover up her crimes by registering false returns.

Creating a simulator Researchers Edgar Alonso Lopez-Rojas, Dan Gorton and Stefan Axelsson at Blekinge Institute of Technology set out to create realistic fraud research data by developing a simulator, primed by real data which would enable sharing data with the research community, without exposing potentially sensitive information.

The simulator is called RetSim (short for Retail Simulator) and allows us to generate synthetic transactional data that can be publicly shared and studied without leaking business sensitive information, and still preserve the important characteristics of the data.

general model can be applicable in other domains RetSim is intended to be used for developing and testing fraud scenarios in a shoe retail store, while keeping business sensitive and private personal information about customers secret from competitors and others.

Synthetic data facilitates further research in retail fraud The purpose of the simulator is to generate transaction data sets that can be used for research into fraud detection.

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