The Casualty Actuarial Society (CAS) launched course offerings at the end of 2016 to grant credentials in Predictive Analytics. Kudos to the CAS in creating this accreditation, but it is really a “better late than never” step versus a cutting edge change for actuaries. Reader’s Digest, a powerhouse magazine at the time, was doing the first business oriented predictive analytics in 1968!
The new credential is called the Certified Specialist in Predictive Analytics (CSPA) and requires the completion of two online courses, passing three exams and completing a case study project. These requirements are administered by the newly established CAS Institute (iCAS). The CAS hopes this Institute, while beginning with a credential in predictive analytics, will go on to develop credentials for catastrophe model analytics, capital modeling and quantitative reinsurance analysis. The CAS leadership recognized the opportunity to serve quantitative professionals in these complementary fields of advanced analytics and data science while maintaining its focus on credentialing property and casualty actuaries with the ACAS, FCAS and CERA professional accreditations.
Data Science Demand
Interestingly this “complementary” expertise is experiencing dramatic growth outside of the insurance industry. Popularly known as data science, the advent of accessible computing power to handle the “lakes” of internet data, even small firms are doing innovative and cutting edge analytics. Demand for this skill set within the insurance and risk industry is not “complementary” but becoming a requirement. Actuaries at almost every level will see broadened career opportunities through utilizing this broadened skill set . Many insurers report improved profitability after implementing predictive modeling into their process. This designation will help employers easily identify those that have the skills to assist in achieving that improved profitability.
For current associates or fellows in the CAS Society a waiver for some of the requirements can be obtained by examination. A partial waiver is possible for those holding a CPCU designation. But learning the foundational concepts for preparing and managing data and datasets that are to be use d in quantitative analyses and predictive modeling as well as the concepts, methods and tools used for statistical analyses and predictive modeling is almost as critical as proving to potential employers that you have actually applied these skills. The case study required for this credential is one step towards proving your real-world experience, but any projects or consulting assignments you can get with your current company, academia or other companies is critical to proving your value to a potential external employer.