Could machine learning help to combat expenses fraud?


Consider the following expenses claims: registration fees for a cancelled seminar, two separate claims for mileage when the employees travelled together, and a sandwich-and-coffee dinner claimed as the full per diem.

While it’s easy to believe that a few dishonest claims won’t hurt, for individual victims, expenses fraud can be costly. Research conducted by the National Fraud Authority suggests that exaggerated expenses claims cost the British economy around £100 million annually; the private sector alone lost £80 million in 2013. Imagine if 20 per cent of your staff added 10 per cent to each mileage claim; the cumulative loss for the company would quickly become significant.

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Author: cvjepsen

Claus Jepsen is a technology expert who has been fascinated by the micro-computer revolution ever since he received a Tandy TRS model 1 at the age of 14. Since then, Claus has spent the last few decades developing and architecting software solutions, most recently at Unit4, where he is the CTO leading the ERP vendor’s focus on enabling the post-modern enterprise. At Unit4, Claus is building cloud-based, super-scalable solutions and bringing innovative technologies such as AI, chatbots, and predictive analytics to ERP. Claus is a strong believer that having access to vast amounts of data allows us to construct better, non-invasive and pervasive solutions to improve our experiences, relieve us from tedious chores, and allow us to focus on what we as individuals really love doing.

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