Identify anomalies to detect potential fraud
Refine your detection methods and improve your fraud detection capabilities
Configure standard consumption patterns
Refine your forecasts with multiple iterations defining an anticipated pattern
Detect abnormal behavior
With which tools?
With consumption and risk modeling
With graphs showing actual consumption and the risk of fraud for a defined period. Visualize the evolution of the estimated consumption according to your initially defined parameters.
With a refined results
Thanks to the numerous iterations carried out by our machine learning solution, we refine the understanding of the results and remove atypical values. Thus defining a level of consumption corresponding to a common behavior.
With the definition of confidence indexes
Thanks to this scoring system, you can quantify and highlight sequences likely to contain fraud, whether for excessive or moderate consumption.
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