Pricing Cyber Insurance: A Geospatial Statistical Approach

IF 1.3 4区 数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Applied Stochastic Models in Business and Industry Pub Date : 2024-09-22 DOI:10.1002/asmb.2891
L. V. Ballestra, V. D'Amato, P. Fersini, S. Forte, F. Greco
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Abstract

Cyberspace is a dynamic ecosystem consisting of interconnected data, devices, and individuals, with multiple network layers comprising identifiable nodes. Location-based information can significantly improve cyber resilience decision-making and facilitate the development of innovative cyber risk pricing tools. This article is based on a methodology that uses company geospatial data to accurately estimate the number of expected losses arising from cyberattacks. Our approach aims to build and compare statistical spatial models that allow pricing cyber policies more effectively than traditional non-spatial methods by incorporating all available data. By accounting for spatial dependence, we can assess the risk of data breaches and contribute to the design of more efficient cyber risk policies for the insurance market.

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网络保险定价:地理空间统计方法
网络空间是一个动态的生态系统,由相互连接的数据、设备和个人组成,多个网络层包含可识别的节点。基于位置的信息可以大大改善网络复原力决策,促进创新网络风险定价工具的开发。本文基于一种方法,利用公司地理空间数据准确估算网络攻击造成的预期损失数量。我们的方法旨在建立和比较统计空间模型,通过纳入所有可用数据,比传统的非空间方法更有效地为网络政策定价。通过考虑空间依赖性,我们可以评估数据泄露的风险,为保险市场设计更有效的网络风险保单做出贡献。
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来源期刊
CiteScore
2.70
自引率
0.00%
发文量
67
审稿时长
>12 weeks
期刊介绍: ASMBI - Applied Stochastic Models in Business and Industry (formerly Applied Stochastic Models and Data Analysis) was first published in 1985, publishing contributions in the interface between stochastic modelling, data analysis and their applications in business, finance, insurance, management and production. In 2007 ASMBI became the official journal of the International Society for Business and Industrial Statistics (www.isbis.org). The main objective is to publish papers, both technical and practical, presenting new results which solve real-life problems or have great potential in doing so. Mathematical rigour, innovative stochastic modelling and sound applications are the key ingredients of papers to be published, after a very selective review process. The journal is very open to new ideas, like Data Science and Big Data stemming from problems in business and industry or uncertainty quantification in engineering, as well as more traditional ones, like reliability, quality control, design of experiments, managerial processes, supply chains and inventories, insurance, econometrics, financial modelling (provided the papers are related to real problems). The journal is interested also in papers addressing the effects of business and industrial decisions on the environment, healthcare, social life. State-of-the art computational methods are very welcome as well, when combined with sound applications and innovative models.
期刊最新文献
Issue Information Foreword to the Special Issue on Mathematical Methods in Reliability (MMR23) Limiting Behavior of Mixed Coherent Systems With Lévy-Frailty Marshall–Olkin Failure Times Pricing Cyber Insurance: A Geospatial Statistical Approach Regional Shopping Objectives in British Grocery Retail Transactions Using Segmented Topic Models
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