Profit optimisation of insurance companies by decreasing fraud-caused loss

by | Nov 15, 2020 | 0 comments

Application Track:

Theme Driven

Code:

REACH-2020-THEMEDRIVEN_1.2

Proposed by:

CEA DIGIHALL

Entity Logo:

Summary of the entity:

List institute, a digital systems’ expert. Based in Saclay (Paris region, France), List Institute is one of CEA Tech three technological research institutes constituting CEA technological Division. Dedicated to smart digital systems, our mission is to achieve technological development of excellence for our industrial partners and create value, with more than 200 industrial collaborations per year. List institute counts more than 750 partners and every year more than a 200 partnership activities are being conducted with French and foreign industrial companies on applied research projects in four main topics: Advanced Manufacturing, Embedded systems, Data intelligence and Health ionizing radiations

Summary of the challenge:

The goal is to provide insurance companies of solutions that allow reducing financial losses by fraud. This is, to have the ability to control their operational risks in fraud and be able to comply with the associated regulatory directives regarding financial solvency.

The goal is to get innovative solutions for detecting different types of cases of health insurance fraud.

Description:

Stakeholder: Healthcare Insurance companies

Description:

As most of the health insurance, frauds are small frauds initiated or with the complicity of health professionals, traditional detection is tedious and inefficient (less than 1%). The very large number of acts and health services partly explains the low rate of detection and recovery.

Insurance companies are continuously interested in improving their revenue margins, preserving their image with their policyholders: If the detection strategy is too “permissive”, loss of money with all the undetected fraud. Conversely, if the detection strategy is too “restrictive”, loss of image with the risk of having many “false positives” which will see their reimbursement request refused due to fraud while the act (care) was completely normal. These companies need to have the ability to control their operational risks in fraud and be able to comply with the associated regulatory directives regarding financial solvency.

The challenge for these companies is therefore to reduce financial losses by fraud through effective detection of health insurance errors and fraudulent actions. They need, however an efficient and highly secure environment for fraud detection, in accordance with the requirements and normative standards of healthcare. They must therefore establish trusted and secure collaborations with antifraud agencies and healthcare professionals to scale up their capacities.

Data:

Expected outcomes:

  • To help insurance companies to increase significantly (over +30%) the number of detected fraud cases.
  • To reduce the revenue losses of healthcare insurance companies caused by fraud and allow them to keep their solvency as required by law.

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