Santéclair: Detecting Fraudulent Claims More Effectively

Santéclair uses Dataiku to enable fraud detection teams to target actual fraud cases 3x more effectively, saving money for both the company and its customers.


more effective in targeting actual fraud cases

weeks vs. months

to operationalize similar fraud models in production


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 in reimbursement volume (more than 1.5M a year), Santéclair needed to improve efficiency and productivity.

Santéclair found Dataiku via a POC led by the IMT TeraLab platform. Eulidia produced an algorithm using Dataiku to help the manual audit team identify more fraud by feeding them cases with a high likelihood of actually being fraudulent.

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. Jocelyn Philippe Head of Partnerships and Development @ Santéclair

Santéclair identified high-risk cases using Dataiku by:

  • Outsmarting fraudsters with advanced machine learning algorithms that continually update and automatically learn or retrain using the latest data so that any new fraud patterns are immediately identified and audited. Dataiku handles the entire workflow, from raw data to exposing the predictive model to the operational applications.
  • Automatically combining hundreds of variables from different datasets, including patient/prescriber history, interaction graphs, prescription characteristics, and other contextual data.
  • Allowing teams to develop their data science skills through Dataiku’s collaborative, easy-to-use interface.

Without Dataiku, the marketing team would have to rely on the technical team to continually provide or update data, which would be inefficient and ineffective for both teams.

In addition, due to the comprehensive solution developed with Dataiku, Santéclair and Eulidia have enabled fraud detection teams to target actual fraud cases three times more effectively. They have also reduced time-to-market for similar projects by making a POC in a few weeks and then industrializing the project within a few months with a low impact on the IT team.

All of this, of course, saves their customers a lot of money by decreasing fraudulent behaviors in the health network and excluding the fraudsters from the network.

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