Early Detection of Insurer Insolvency

Authors:

Tianyang Wang, Ph.D., ASA, CFA, FRM, Department of Finance and Real Estate, College of Business, Colorado State University

Xiaowen Hu, Ph.D., Department of Finance, Leeds School of Business, The University of Colorado at Boulder

Description:

Early detection and assessment of insurer’s insolvency risk are critically important to regulators, insurers, policyholders, and investors for fiduciary assessment of insurer’s financial stability and for protection of potential financial loss associated with insurer’s insolvency. This study aims to develop a market-based insolvency prediction model to detect financially distressed insurers at an early stage with the information content of higher moments from the market.

Report:

Early Detection of Insurer Insolvency

Acknowledgments:

The researchers’ deepest gratitude goes to those without whose efforts this project could not have come to fruition: the Project Oversight Group and others for their diligent work overseeing questionnaire development, analyzing and discussing respondent answers, and reviewing and editing this report for accuracy and relevance. We also greatly appreciate the invitation, comments and feedback at the 2020 Predictive Analytics Virtual Seminar (Hong Kong).

Project Oversight Group Members

Rachit Agarwal, FSA, CERA, FCIA

Victor Chen, FSA, FCIA, CERA

Louise Francis, MAAA, FCAS

Xiaojie Gong, FSA, CERA

Jiani (Maggie) Ma, FSA, FCIA

Justin Tanjuakio, FSA, CERA

Yu (Kaitlynn) Weng, FSA, FCIA

Ai Yan (Shirley) Wu, FSA, MAAA, ACIA

At the Society of Actuaries

Jan Schuh, SOA Senior Research Administrator

David Schraub, FSA, MAAA, CERA, AQ Senior Practice Research Actuary

Ronora Stryker, ASA, MAAA, SOA Senior Practice Research Actuary

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