Zorg en Zekerheid is a medium-sized and independent regional health insurer in the Netherlands, with more than 460 employees and more than 380,000 policyholders. The company is committed to providing accessible and affordable healthcare.
“Zorg en Zekerheid is a medium-sized and independent regional health insurer in the
Netherlands, with more than 460 employees and more than 380,000 policyholders. The
company is committed to providing accessible and affordable healthcare. The majority of
policyholders and healthcare providers submit claims for treatments that have actually
taken place. However, a small number commit fraud — for example by adapting invoices.
There are instances of policyholders who, after returning from vacation, submit invoices
for medical costs made abroad. Further examination shows that the invoiced amount has
been altered and is many times higher than the original amount. There are also instances
of “up-coding” — a form of fraud committed by healthcare providers performing simple
services but claiming for more complex alternatives, which results in higher costs.”
Zorg en Zekerheid needed a more accurate and efficient solution to detect claims fraud.
Assume you have been hired by Zorg en Zekerheid to work on this project — to build a
predictive modelling solution that translates many data elements from a diverse range of
sources into quantitative risk ratings for fraudulent claims.
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