By Nicholas Yeo
The combination of artificial intelligence (AI) and process automation is revolutionizing actuarial work. AI will be the brains underlying the new age actuarial work whilst process automation will be the brawn. Actuarial work will be completed quickly, efficiently and accurately. Actuaries will be freed up from crunching numbers and producing reports, thus freeing up time to focus on high value activities such as insightful recommendations, business development and risk management.
It was not too long ago when I was a fresh graduate crunching the numbers required for actuarial reporting on MS-DOS programs, receiving data from, and saving results into, CD-ROMs. I spent nights, early mornings and weekends running and rerunning data validation checks and valuation models, at times manning multiple CPUs and often only barely making the deadlines.
Risk-Based Capital, Solvency II and various other reporting requirements left insurance companies with no choice but to invest in technology that churns out results efficiently. Enhancements such as cloud computing, data warehousing as well as streamlined actuarial software, have led to significant improvements. Run times of complex models are now measured in hours if not minutes while the quality of the work has improved significantly.
Nonetheless, actuarial work has remained manual. This is because despite automation, actuarial judgment is still applied at every step of the process, be it data manipulation, assumption setting or methodology selection (mainly for non-life insurance reserving). Without AI, i.e., without the brains, the upside of process automation is limited.
AI is altering the actuarial landscape. AI brings to the actuarial profession a structured, consistent and unbiased way to perform actuarial work that minimizes the need for human intervention. AI, coupled with process automation and technology, will make the actuary much more productive.
This is not science fiction. IBNR Robot, developed by Nicholas Actuarial Solutions, has been implemented in actual pricing and reserving work. Based on statistical techniques including jack-knifing, runs test, hypothesis testing, Lagrange multipliers, and the method of moments, loss reserves are calculated in seconds without the need for human intervention. With the IBNR Robot, data reliability is ensured, actuarial assumptions such as development factors, tail factors and seed loss ratios are automatically selected, actuarial methodologies (paid vs. incurred data, link ratio vs. Bornhuetter-Ferguson methods) are optimally chosen, and the reserve range is automatically calibrated.
This is not to say that actuarial judgement is redundant. Actuarial judgement remains valuable. However, instead of making decisions at every step of the process, actuaries only need to make decisions at the end to overwrite the model output when required. For example, there could be qualitative information not captured in the data or subsequent events could trigger adjustments.
With process automation and AI, the actuaries’ time would no longer be unnecessarily spent in processing data and crunching numbers. Instead, actuaries could spend more time performing analysis and making recommendations in areas they understand well such as marketing financial products and managing enterprise risk.
Nicholas Yeo, FSA, FIA, is the founder of Nicholas Actuarial Solutions. He can be contacted at email@example.com.