Xie, S.; Li, Y. Analyzing Size of Loss Frequency Distribution Patterns: Uncovering the Impact of the COVID-19 Pandemic. Risks2024, 12, 40.
Xie, S.; Li, Y. Analyzing Size of Loss Frequency Distribution Patterns: Uncovering the Impact of the COVID-19 Pandemic. Risks 2024, 12, 40.
Xie, S.; Li, Y. Analyzing Size of Loss Frequency Distribution Patterns: Uncovering the Impact of the COVID-19 Pandemic. Risks2024, 12, 40.
Xie, S.; Li, Y. Analyzing Size of Loss Frequency Distribution Patterns: Uncovering the Impact of the COVID-19 Pandemic. Risks 2024, 12, 40.
Abstract
The study delves into the critical examination of the Size of Loss distribution patterns in the context of auto insurance during pre- and post-pandemics, emphasizing their profound influence on insurance pricing and regulatory frameworks. Through a comprehensive analysis of the historical Size of Loss data, insurers and regulators gain essential insights into the probabilities and magnitudes of insurance claims, informing the determination of precise insurance premiums and the management of case reserving. This approach aids in fostering fair competition, ensuring equitable premium rates, and preventing discriminatory pricing practices, thereby promoting a balanced insurance landscape. The research further investigates the transformative impact of the COVID-19 pandemic on these Size of Loss patterns, given the substantial shifts in driving behaviors and risk landscapes. Also, the research contributes to the literature by addressing the need for more studies focusing on the implications of the COVID-19 pandemic on pre- and post-pandemic auto insurance loss patterns, thus offering a holistic perspective encompassing both insurance pricing and regulatory dimensions.
Keywords
Rate-making; Predictive Analytics; Insurance Rate Regulation; COVID-19 Pandemic; Size of Loss Distribution
Subject
Business, Economics and Management, Econometrics and Statistics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
