Covering the underwriting risk

Underwriting risk exists when an insurer’s obligations are incorrectly priced. So it’s imperative that you correctly calculate the cost of the risk in the contracts you offer and accurately match it with the appropriate premiums. Maïssetou Coulibaly says that analytics helped her and her team manage underwriting risks across the company.

"We needed to be able to define the level of risk in an activity, sector and geographical location beyond the basic variables of age, sex or family composition," explains Coulibaly, Actuarial Services Supervisor in the Underwriting, Pricing and Medical Monitoring division of Klesia.

"We’re now able to keep track of our decisions and justify them immediately if we are asked. We’re improving our response time in decision making, which represents a significant gain in performance.

Maïssetou Coulibaly
Supervisor, Underwriting, Pricing and Medical Monitoring

Risk analysis, reporting and data consolidation

Analytics was the answer. We can see the risk in each case in relation to the amortization and the overall impact on the solvency margin. Coulibaly says there were three major areas where they saw improvements in reporting and distribution:

  1. Support for the technical management of actuarial planning decisions – regarding products and premiums.
  2. Better access to relevant information by the sales team and brokers.
  3. Targeted and relevant distribution of information to customers.

Turning a regulatory constraint into a competitive advantage

Klesia is a new social protection group formed from the merger of the Mornay and D&O groups. So in terms of the implementation of an analytics solution, the biggest challenge is consolidating data coming from multiple operational systems – which are linked to different legal structures within the new organization.

"The initial work performed on the quality and traceability of data is a prerequisite in the context of Solvency II, but also, quite simply, is necessary for the viability of our own activities," says Coulibaly.

To date, the progress of this project has shown more than convincing results. "We’re improving our response time in decision making, which represents a significant gain in performance,” says Coulibaly.

And the data quality work has borne fruit in underwriting risk control and Solvency II compliance. She says, "We’re now able to keep track of our decisions and justify them immediately if we are asked."



  • Optimize the underwriting risk process.
  • Analyze the impact of credit risk pricing.
  • Produce strategic and operational reports to control the credit risk. 
  • Meet the regulatory requirements for Solvency II.



  • Improved response times in decision making, resulting in significant gain in performance.
  • Enhanced underwriting risk assessment.
  • Compliance with Solvency II.
The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.

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