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Optimization of admission fraud detection at the financial entity Cetelem

The increase of the arrearage rate is one of the main concerns of the financial sector. Entities make efforts to combat non-payments with different strategies. Among them, Cetelem counts on the Apara’s technology for the detection of admission fraud.  It is estimated that 10% to 30% of the arrearage come from this kind of fraud.

Since the implementation of the Apara’s predictive analytic platform (dVelox) at Cetelem, the percentage of avoided fraud increased obtaining an average of 2.4%, which results in a 20% increase of fraud detection.

Thanks to the creation of a predictive model that allows its automatic update in a simple and accurate way, dVelox has provide Cetelem the capacity of identifying common patterns and characteristics of the requestors with higher probability to defraud, explaining its causes ,detecting fraud that was not identified to date and reducing economic losses.

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