Slideshow 10 Tips for Effective Governance of Actuarial Models

  • March 25 2013, 12:51pm EDT

A recent report from Deloitte asserts the importance of actuarial modeling to insurers' ability to effectively underwrite, as well as the importance of an overarching governance policy to maintain continuity. The research indicated that U.S. insurers lag their international counterparts when it comes to formal governance by 25 percent—half of U.S. insurers use formal governance to drive actuarial controls, compared to 75 percent of non-U.S.-owned insurers. The following 10 leading practices were culled from survey results and follow-up discussion.

1. Develop a single set of standards regarding model building and documentation

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2. Create a corporate culture in which employees understand the value of and seek to improve governance and controls across all functions

3. Establish a dedicated structure related to the modeling organization, with clear and delineated responsibilities for development, maintenance and change management, including the coordination of user-acceptance testing and the establishment of an inventory of models

4. Define change request procedures for revisions to production models and clearly communicate request prioritizations across user groups

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5. Establish protocols for updates/upgrades to the actuarial modeling platforms, operating systems and other systems that support the modeling process, such as spreadsheet programs, including regression testing

6. Controlled and automated attribution testing processes to identify and quantify differences due to system, logic or data updates, which is an even more critical component of model integrity in cases where multiple areas use a common model

7. Establish a prioritization scheme to rank models, or specific components of models, and use prioritization to establish frequency and intensity of reviews

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8. Develop a production model

9. Monitor the model users' skills, including training and development/software accreditation

10. Conduct ongoing reviews of models' functionality against new developments