Regulating risk culture in the insurance industry using machine learning
Aparna Gupta
Lally School of Management, Rensselaer Polytechnic Institute, Troy, New York, USA
Search for more papers by this authorCorresponding Author
Abena Owusu
Feliciano School of Business, Montclair State University, Montclair, New Jersey, USA
Correspondence Abena Owusu, Feliciano School of Business, Montclair State University, Montclair, NJ, USA.
Email: [email protected]
Search for more papers by this authorAparna Gupta
Lally School of Management, Rensselaer Polytechnic Institute, Troy, New York, USA
Search for more papers by this authorCorresponding Author
Abena Owusu
Feliciano School of Business, Montclair State University, Montclair, New Jersey, USA
Correspondence Abena Owusu, Feliciano School of Business, Montclair State University, Montclair, NJ, USA.
Email: [email protected]
Search for more papers by this authorAbstract
This study examines the relationship between risk culture and regulation in the insurance industry using textual analysis and machine learning. By analyzing 10-K disclosures, we classify firms into distinct risk culture clusters and find that the risk culture of insurance firms is significantly shaped by their uncertain risk strategies, constraints in defining, implementing, and reporting risks, as well as litigious decisions and risk management practices. A temporal prediction analysis indicates that large insurers maintaining a poor risk culture trend are less likely to reverse it compared to those improving. Moreover, insurance firms show enhanced risk culture post-Dodd–Frank Act. Our findings underscore the potential benefits of regulations aimed at monitoring and overseeing insurers' risk practices.
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