New Study Findings from Kennesaw State University Illuminate Research in Risk Management (Modeling Under-Reporting in Cyber Incidents): Insurance – Risk Management

2022 NOV 25 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Data detailed on risk management have been presented. According to news reporting originating from Kennesaw, Georgia, by NewsRx correspondents, research stated, “Under-reporting in cyber incidents is a well-established problem.”

Our news editors obtained a quote from the research from Kennesaw State University: “Due to reputational risk and the consequent financial impact, a large proportion of incidents are never disclosed to the public, especially if they do not involve a breach of protected data. Generally, the problem of under-reporting is solved through a proportion-based approach, where the level of under-reporting in a data set is determined by comparison to data that is fully reported. In this work, cyber insurance claims data is used as the complete data set. Unlike most other work, however, our goal is to quantify under-reporting with respect to multiple dimensions: company revenue, industry, and incident categorization. The research shows that there is a dramatic difference in under-reporting-a factor of 100-as a function of these variables. Overall, it is estimated that only approximately 3% of all cyber incidents are accounted for in databases of publicly reported events.”

According to the news editors, the research concluded: “The output of this work is an under-reporting model that can be used to correct incident frequencies derived from data sets of publicly reported incidents. This diminishes the ‘barrier to entry’ in the development of cyber risk models, making it accessible to researchers who may not have the resources to acquire closely guarded cyber insurance claims data.”

For more information on this research see: Modeling Under-Reporting in Cyber Incidents. Risks, 2022,10(200):200. (Risks - http://www.mdpi.com/journal/risks). The publisher for Risks is MDPI AG.

A free version of this journal article is available at https://doi.org/10.3390/risks10110200.

Our news journalists report that additional information may be obtained by contacting Seema Sangari, School of Data Science and Analytics, Kennesaw State University, 3391 Town Point Dr. NW, Kennesaw, GA 30144, United States. Additional authors for this research include Eric Dallal, Michael Whitman.

(Our reports deliver fact-based news of research and discoveries from around the world.)