Fraud Detection Model
Identifying, preventing and reducing the phenomenon of fraud is assuming an ever-increasing primary role in the business world. By exploiting the practically total computerisation of transactions, which is a feature of business in general, fraud has become more and more frequent, sophisticated and difficult to detect, rendering the problem of intercepting it and consequently reducing it, a daunting one. For example, for the banking system to sustain payment by credit card, fraud associated with this tool must necessarily become an extremely limited phenomenon. A similar argument can be made for electronic trade, accidents in the insurance field, etc..
From the analytical perspective, the activity of identifying potentially fraudulent phenomena turns out to be like a particular interpretation of a Segmentation Model, in which we pursue the aim of characterising a group of potential fraud committers in relation to the rest of the population which has a “normal” behaviour. Even in this case, the analysis is based on information, which the company can avail itself of, on client or employee behaviours, depending if the investigation is carried out on external or internal fraud respectively.
Identifying the client or employee subset with anomalous behaviours allows us to accurately employ auditing for the exact fraud check, thereby producing the reduction of the phenomenon as the final result. And, in summary, this translates into an important competitive advantage for cost reduction.