FCAS, MAAA, CSPA
Senior Consulting Actuary

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Gary C. Wang

Gary Wang is a Senior Consulting Actuary with Pinnacle Actuarial Resources, Inc. in the Bloomington, Illinois office. He holds a Bachelor of Science degree in mathematics from the University of Illinois and a Master of Science degree in mathematics education from Northern Illinois University. He also has extensive graduate level coursework in Theoretical and Applied Mathematics from Northern Illinois University. He has over seventeen years of actuarial experience in the property/casualty insurance industry.

Mr. Wang currently serves the CAS as a member of the Ratemaking and Product Management Planning Committee.

Before joining Pinnacle, Mr. Wang was employed as a pricing actuary for three of the top ten insurance companies. His pricing experience includes standard homeowners rate indications, commercial auto rate indications, and reinsurance treaty pricing for both personal and commercial lines. In addition, he has experience in reserving analyses for commercial auto and market trend analyses for commercial auto and workers compensation.

At Pinnacle, Mr. Wang has worked extensively on the application of advanced statistical modeling techniques to the insurance process. His experience in predictive analytics applications include rating and underwriting plan design, homeowners by-peril analysis, auto vehicle characteristics analysis and scorecard development, and territory boundary development. Mr. Wang has made numerous presentations on topics relating to predictive modeling, ratemaking, and insurance credit‐based scoring.

Publications and Media

February 2020 APEX
How to Incorporate Simulated Data into Actuarial Research
Authored by Gary C. Wang and Michael K. Chen.

February 2019 APEX Webinar
The Actuary’s Evolving Role in Today’s Dynamic Industry Landscape
Authored by Gary C. Wang and Michael K. Chen.

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Case Studies

Colorado Automobile No-Fault Impact Analyses

Colorado Automobile No-Fault Impact Analyses

Pinnacle Actuarial Resources prepared an independent actuarial analysis on behalf of the Colorado Auto Insurance Working Group to determine the cost implications of changes to the Colorado no-fault law. One of the scenarios analyzed was the complete repeal of the no-fault law, replacing it with medical payments coverage.

The analysis employed data from a recent study by the Insurance Research Council (IRC) to assess the impact of a $2,500 economic loss threshold relative to BI losses. Loss and trend information from the Fast-Track monitoring system was reviewed to estimate the impact of implementing no-fault systems from other jurisdictions. Moreover, the Fast Track data was evaluated to assess the impact on costs of other jurisdictions that had previously repealed their no-fault systems.

Lastly, the indicated cost estimates for the state of Colorado were compared to those of tort states in order to assess the reasonableness of the study’s outcomes. The results from this study were used to support rate filings of several of our clients in support of the reforms.

Retention Analysis

Retention Analysis

Pinnacle was asked by a large self-insured regional transportation authority to assess the impact of increasing their self-insured retentions for both workers compensation and automobile liability. We developed a stochastic simulation analysis, based on the program’s historical claims experience and industry benchmarks, that examined not only the increase in expected losses but the program’s additional potential loss variability. Finally, we discussed with the customer the relationship between their current capital position, as well as the current reinsurance market, to ensure the retention they selected for their program was appropriate for them. The authority ultimately increased their retentions, put some of their excess capital to work, and realized substantial savings in their reinsurance costs.

Territory / Summit Analysis

Territory / Summit Analysis

The insurer had not reviewed or adjusted their territorial boundaries in several years; and their current territories were not based upon an analysis of their underlying loss experience.

Pinnacle began with an evaluation of available insurer and external industry data at the ZIP code level as well as their current and future policy processing capabilities. After all of the experience data was adjusted to a common base level, we used our Summit® software product to smooth the data to develop an initial adjusted pure premium by ZIP code to reflect both experience in a ZIP code and in neighboring ZIP codes. The number of additional neighboring ZIP codes used was dependent upon attaining a sufficient exposure level.

The smoothed data was then clustered using Summit® on both a contiguous and non-contiguous basis. The insurer needed to decide whether to maintain relatively contiguous definitions or use more granular and theoretically accurate non-contiguous definitions. Using statistical measures, we identified and graphed optimal definition sets. Non-contiguous definitions were selected by the client. To minimize the number of territories with a limited geographic area or only a few ZIP codes, some manual combination of “outlying” ZIP codes with territories (clusters) with similar adjusted pure premiums was performed.

Finally, we assisted the insurer in developing the necessary filing support material to gain approval. The new program is generating new business in areas of historical profitability but previously less than average competiveness. 

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