Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/265047 
Year of Publication: 
2022
Citation: 
[Journal:] Journal of Risk and Insurance [ISSN:] 1539-6975 [Volume:] 89 [Issue:] 3 [Publisher:] Wiley [Place:] Hoboken, NJ [Year:] 2022 [Pages:] 725-763
Publisher: 
Wiley, Hoboken, NJ
Abstract: 
In this paper, we first construct a cyber risk consciousness score using a text mining algorithm, applied to annual reports of large‐ and mid‐cap US banks and insurers from 2011 to 2018. We next categorize the firms' cyber risk management based on keywords to study determinants and value‐relevance. Our results show an increasing cyber risk consciousness, regardless of the industry. In addition, for the entire sample we find that firms belonging to the banking industry, with a higher cyber risk consciousness score and a higher general risk awareness are more likely to implement cyber risk management, which also holds for both industries separately. We find the opposite in the case of profitable firms for the entire sample and the insurer subsample. Finally, we observe a significant positive relationship between cyber risk management and firm value measured by Tobin's Q for the entire sample and the subsamples of banks and insurers.
Subjects: 
cyber (security) risk management
cyber risk
cybersecurity
text mining
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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