We were very pleased to be chosen to participate in the Pinnacle U program for 2020. We decided to investigate the ever-evolving role of simulation in insurance, with a focus on the practicality and implementation of the Monte Carlo Simulation (MCS). Our presentation followed a funnel approach starting with the general procedure for any type of simulation. We then narrowed in on theoretical and practical methods and uses of simulations for the insurance industry. Finally, we focused specifically on MCS and a few applications of that particular simulation technique.

One of the interesting trends during the COVID-19 quarantine was the dramatic increase in pet adoptions. Furry, four-legged family members require financial investment in their daily care. Typically, the costs of food, toys and grooming are well understood by first-time pet owners. Owners may be less aware, however, of veterinary expenses and liability claims that can costs thousands of dollars. They should understand these often unforeseen and potentially costly pet expenses to understand how risk can be mitigated through pet insurance. 

Pinnacle University (Pinnacle U) is a complex program to pull off. Designing, planning and executing an event like Pinnacle U, usually requires a lot of flexibility in the process. This year, however, required a higher level of flexibility than we might have ever expected. Pinnacle U is an immersive, in-person symposium at which students, professionals, panelists and participants meet and spend the day discovering and debating important actuarial issues of the day. 

On the May 2020 Pinnacle APEX Webinar, “The Importance of Data Management and Data Quality,” we addressed a critical business issue:  the costs of poor data, reasons for data management, and ways to improve how data is managed in an organization. The webinar also took a deep dive into methods to address the major challenge of missing data.

On Pinnacle’s September 2019 APEX webinar, “Digging Into the Modeling Lifecycle,” we discussed the importance of understanding all of the steps involved in the modeling lifecycle—far beyond simple model construction. That includes understanding the business question, anticipating the potential constraints of implementation, and staying ahead of model usage from a change management perspective. Management of those issues are among the most critical contributors to the model’s best chance for success.