Insurers face growing demands to improve and demonstrate their understanding and management of risk in order to comply with intensifying regulations and emerging solvency requirements — while also increasing profitability. Meanwhile, market fluctuations, changes in consumer expectations and product designs, and new risk modeling techniques all are increasing the pressure on carriers to modernize their approach to the actuarial sciences. The new risk management and reporting requirements demand an ever-increasing volume of assumptions, and the growth of data to be analyzed calls for new technology architecture. What are the requirements of a modern actuarial environment, and what technologies can help insurers meet current and future modeling needs?
Modernizing Actuarial Capabilities: An Ongoing Battle
By Brian Cartwright, Assistant VP, MetLife (New York)
New regulatory requirements, fast-changing global markets and the need to do more complex tasks have made it essential for insurers to make better determinations and decisions, putting pressure on actuarial capabilities. At MetLife, we look to have a strong foundation for our systems so that parts of the process can change as needed without having to build a whole new environment, and we try to have repeatable processes. Right now, we're building processes that go all the way from policy administration through areas such as valuation, asset liability management (ALM), enterprise risk management (ERM) and more.
Attention to time reduction is another characteristic of a modern actuarial system. In addition, you need reliable systems that give you more confidence in the results, as well as a common technology stack and methodologies for approaching different processing problems to help accelerate development and ensure that your development environment is stable.
It's also essential to maintain data quality. Bad data can lead to costly mistakes and can cause reruns that may take even more time and cause more pressure on reporting. No matter how much we compute in our environment, there's always a demand to do more and to perform additional analyses. Development teams need to control costs by not overreacting and also by being creative. If there's a new processing demand, don't go out and buy hardware and other things until you can actually assess it and come up with the best approach. Find alternative solutions that will enable you to do things faster and better.
Always look to improve and reduce bottlenecks in areas such as networking and storage. It's not just a hardware or computer issue; it's sometimes optimizing the models we process and the way they manage memory, and we can save time just by changing a model to operate somewhat differently.
Staying up to date on technology and implementing new capabilities is a key to success. But modernizing these environments is like a battlefront: You need to constantly push forward in different areas in order to move the progress line forward.
[For more on how the insurance industry is enhancing its modeling to better understand risk, check out Disaster Response: Changing the Face of CAT Risk.]
Peggy Bresnick Kendler has been a writer for 30 years. She has worked as an editor, publicist and school district technology coordinator. During the past decade, Bresnick Kendler has worked for UBM TechWeb on special financialservices technology-centered ... View Full Bio