Hiring more staff to conduct these manual audits is an expensive and inefficient option. Instead,
the key is optimizing that team’s work by using
big data to detect fraudulent activity with a higher degree of accuracy. This means using data from multiple sources (from patients and providers) and analyzing them together so that audit teams look only at the highest-risk cases to detect more fraud.
Santéclair is a subsidiary of several supplementary health insurance companies (Allianz, Maaf-MMA, Ipeca Prévoyance, and Mutuelle Générale de la Police). They support the health care of more than 10 million beneficiaries, helping to cover optical, dental, and aural expenses as well as dietetic and orthopedic services. For more than 13 years, Santéclair has proven their expertise in risk management, benefiting more than 50 health insurance companies.
Santéclair found fraudulent reimbursements stemmed both from opticians as well as patients, however it didn’t have a system that would analyze the right data and adapt with increasingly sophisticated fraudsters. Instead, it relied on “if-then-else” business rules to identify likely fraud cases, which resulted in the manual audit team spending their time on too many low-risk cases. With the increase of reimbursement volume (more than 1.5M a year), Santéclair needed to improve efficiency and productivity.
In less than a year, Santéclair has developed
an unprecedented fraud detection system using Dataiku that allows our company to handle a growing volume of invoices and to control costs. By choosing Dataiku, Santéclair was
able to internalize its data skills and pursue additional analytics projects.
Head of Partnerships and Development| Santéclair