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To hire or not to hire? Underwriter staffing analysis for AMERICAN Insurance Company

Kevin Pan et al.

Risk Management and Insurance Review2025https://doi.org/10.1111/rmir.70015article
ABDC C
Weight
0.37

What the paper says

Abstract This teaching case examines a critical staffing decision faced by the underwriting division of AMERICAN Insurance Company (“AMERICAN”), a multi‐line, multi‐state property and casualty (“P&C”) carrier. Following significant policy growth and recent implementation of a new core technology platform designed to enhance underwriting efficiency, Mr. Edward Lloyd, head of underwriting, must determine whether to hire additional underwriting staff. Students need to make a data‐driven recommendation to help Mr. Lloyd make a decision. The case requires students to integrate foundational knowledge of P&C insurance carrier operations with practical considerations such as training lags and productivity gains from automation. Students will perform time‐series analyses of realistic staffing and policy data using Excel to evaluate trends in policy growth and underwriting productivity. Designed for use in risk management, insurance, and business analytics courses, this case gives students hands‐on experience with data visualization, regression analysis, and strategic decision‐making integrated with insurance carrier functions.

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https://doi.org/https://doi.org/10.1111/rmir.70015

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@article{kevin2025,
  title        = {{To hire or not to hire? Underwriter staffing analysis for AMERICAN Insurance Company}},
  author       = {Kevin Pan et al.},
  journal      = {Risk Management and Insurance Review},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1111/rmir.70015},
}

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To hire or not to hire? Underwriter staffing analysis for AMERICAN Insurance Company

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.