A comprehensive model for cyber risk based on marked point processes and its application to insurance
After scrutinizing technical, legal, financial, and actuarial aspects of cyber risk, a new approach for modelling cyber risk using marked point processes is proposed. Key covariates, required to model frequency and severity of cyber claims, are identified. The presented framework explicitly takes in...
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| Published in | European actuarial journal Vol. 12; no. 1; pp. 33 - 85 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Berlin, Heidelberg
Springer
01.06.2022
Springer Berlin Heidelberg Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
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| Abstract | After scrutinizing technical, legal, financial, and actuarial aspects of cyber risk, a new approach for modelling cyber risk using marked point processes is proposed. Key covariates, required to model frequency and severity of cyber claims, are identified. The presented framework explicitly takes into account incidents from malicious untargeted and targeted attacks as well as accidents and failures. The resulting model is able to include the dynamic nature of cyber risk, while capturing accumulation risk in a realistic way. The model is studied with respect to its statistical properties and applied to the pricing of cyber insurance and risk measurement. The results are illustrated in a simulation study. |
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| AbstractList | Abstract After scrutinizing technical, legal, financial, and actuarial aspects of cyber risk, a new approach for modelling cyber risk using marked point processes is proposed. Key covariates, required to model frequency and severity of cyber claims, are identified. The presented framework explicitly takes into account incidents from malicious untargeted and targeted attacks as well as accidents and failures. The resulting model is able to include the dynamic nature of cyber risk, while capturing accumulation risk in a realistic way. The model is studied with respect to its statistical properties and applied to the pricing of cyber insurance and risk measurement. The results are illustrated in a simulation study. After scrutinizing technical, legal, financial, and actuarial aspects of cyber risk, a new approach for modelling cyber risk using marked point processes is proposed. Key covariates, required to model frequency and severity of cyber claims, are identified. The presented framework explicitly takes into account incidents from malicious untargeted and targeted attacks as well as accidents and failures. The resulting model is able to include the dynamic nature of cyber risk, while capturing accumulation risk in a realistic way. The model is studied with respect to its statistical properties and applied to the pricing of cyber insurance and risk measurement. The results are illustrated in a simulation study. |
| Author | Zeller, Gabriela Scherer, Matthias |
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| CitedBy_id | crossref_primary_10_1007_s13385_023_00341_9 crossref_primary_10_1080_03461238_2023_2191869 crossref_primary_10_1016_j_procs_2023_01_320 crossref_primary_10_1051_mmnp_2022041 crossref_primary_10_1007_s13385_024_00381_9 crossref_primary_10_1111_jori_12450 crossref_primary_10_1007_s13385_023_00366_0 crossref_primary_10_1017_S1748499523000258 crossref_primary_10_2139_ssrn_4353098 crossref_primary_10_1057_s41288_022_00282_6 crossref_primary_10_1214_23_EJP979 crossref_primary_10_1057_s41288_023_00289_7 crossref_primary_10_1016_j_ejor_2023_05_003 crossref_primary_10_3233_JIFS_222308 |
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| Keywords | Cyber insurance Accumulation risk Cyber risk Marked point processes Emerging risks |
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| SubjectTerms | Accumulation risk Actuarial science Applications of Mathematics Binomial distribution Cyber insurance Cyber risk Data integrity Economics Emerging risks Financial Services Game Theory Liability insurance Literature reviews Losses Marked point processes Mathematics Mathematics and Statistics Network security Original Research Paper Quantitative Finance Risk management Social and Behav. Sciences Stochastic models |
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| Title | A comprehensive model for cyber risk based on marked point processes and its application to insurance |
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