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Explainable AI and Interpretable Model for insurance premium Prediction

Journal on Artificial Intelligence 2023年第1期5卷 31-42页

作者： Umar Abdulkadir Isa Anil Fernando Department of Computer and Information Science University of StrathclydeGlasgowUK

Traditional machine learning metrics(TMLMs)are quite useful for the current research work precision,recall,accuracy,MSE and *** enough for a practitioner to be confident about the performance and dependability of innovative interpretable model 85%–92%.We included in the prediction process,machine learning models(MLMs)with greater than 99%accuracy with a sensitivity of 95%–98%and specifically in the *** need to explain the model to domain specialists through the ***-understandable explanations in addition to ML professionals must establish trust in the prediction of our *** is achieved by creating a model-independent,locally accurate explanation set that makes it better than the primary *** we know that human interaction with machine learning systems on this model’s interpretability is more *** supporting set validations in model selection insurance premium *** this study,we proposed the use of the(LIME and SHAP)approach to understand research properly and explain a model developed using random forest regression to predict insurance *** SHAP algorithm’s drawback,as seen in our experiments,is its lengthy computing time—to produce the findings,it must compute every possible *** addition,the experiments conducted were intended to focus on the model’s interpretability and explain its ability using LIME and SHAP,not the insurance premium charge *** experiments were conducted through experiment,one was to interpret the random forest regression model using LIME *** experiment 2,we used the SHAP technique to interpret the model insurance premium prediction(IPP).

关键词： LIME SHAP innovative explainable AI random forest machine learning insurance premium

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Cyberattack Ramifications, The Hidden Cost of a Security Breach

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Journal of Information Security 2024年第2期15卷 87-105页

作者： Meysam Tahmasebi Department of Cybersecurity EC-Council University Albuquerque USA

In this in-depth exploration, I delve into the complex implications and costs of cybersecurity breaches. Venturing beyond just the immediate repercussions, the research unearths both the overt and concealed long-term consequences that businesses encounter. This study integrates findings from various research, including quantitative reports, drawing upon real-world incidents faced by both small and large enterprises. This investigation emphasizes the profound intangible costs, such as trade name devaluation and potential damage to brand reputation, which can persist long after the breach. By collating insights from industry experts and a myriad of research, the study provides a comprehensive perspective on the profound, multi-dimensional impacts of cybersecurity incidents. The overarching aim is to underscore the often-underestimated scope and depth of these breaches, emphasizing the entire timeline post-incident and the urgent need for fortified preventative and reactive measures in the digital domain.

关键词： Artificial Intelligence (AI) Business Continuity Case Studies Copyright Cost-Benefit Analysis Credit Rating Cyberwarfare Cybersecurity Breaches Data Breaches Denial Of Service (DOS) Devaluation Of Trade Name Disaster Recovery Distributed Denial of Service (DDOS) Identity Theft Increased Cost to Raise Debt insurance premium Intellectual Property Operational Disruption Patent Post-Breach Customer Protection Recovery Point Objective (RPO) Recovery Time Objective (RTO) Regulatory Compliance Risk Assessment Service Level Agreement Stuxnet Trade Secret

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insurance ratemaking method for risk of construction diversion project

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Engineering Sciences 2012年第2期10卷 90-96页

作者： Chen Zhiding Hu Zhigen College of Hydraulic ＆ Environmental Engineering China Three Gorges University YichangHubei 443002 China State Key Laboratory of Water Resources and Hydropower Engineering Science Wuhan University Wuhan 430072 China

Based on analyzing risk factors of diversion project,synthetic risk rate and engineering insurance period,the frequency and distribution law of loss are researched on the grounds that foundation pit is submerged after diversion project ceases to be *** then,the standpoint that these total loss is subject to non-homogeneous compound Poisson processes is put ***,the collective risk model of the total loss about engineering insurance is established on the basis of construction diversion project ***,insurance ratemaking method for construction engineering risk and its mathematical expression are presented,which provides theoretical method for the insurance ratemaking of hydropower engineering to some extent.

关键词： diversion risk engineering insurance insurance premium non-homogeneous compound Poisson processes

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