Intelligent and Other Computational Techniques in Insurance:Theory and Applications

Edited by A F Shapiro and L C Jain

in World Scientific Books from World Scientific Publishing Co. Pte. Ltd.

Abstract: This book presents recent advances in the theory and implementation of intelligent and other computational techniques in the insurance industry. The paradigms covered encompass artificial neural networks and fuzzy systems, including clustering versions, optimization and resampling methods, algebraic and Bayesian models, decision trees and regression splines. Thus, the focus is not just on intelligent techniques, although these constitute a major component; the book also deals with other current computational paradigms that are likely to impact on the industry. The application areas include asset allocation, asset and liability management, cash-flow analysis, claim costs, classification, fraud detection, insolvency, investments, loss distributions, marketing, pricing and premiums, rate-making, retention, survival analysis, and underwriting.

Keywords: Insurance; Actuarial Science; Neural Networks; Fuzzy Systems; Computational Intelligence; Computational Techniques; Life and Health Insurance; Property and Casualty Insurance (search for similar items in EconPapers)
Date: 2003
ISBN: 9789812387189
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Chapters in this book:

Ch 1 Insurance Applications of Neural Networks, Fuzzy Logic, and Genetic Algorithms , pp 3-47

Arnold F. Shapiro

Ch 2 An Introduction to Neural Networks in Insurance , pp 51-102

Louise A. Francis

Ch 3 Practical Applications of Neural Networks in Property and Casualty Insurance , pp 103-136

Louise A. Francis

Ch 4 Statistical Learning Algorithms Applied to Automobile Insurance Ratemaking , pp 137-197

C. Dugas, Y. Bengio, N. Chapados, P. Vincent, G. Denoncourt and C. Fournier

Ch 5 An Integrated Data Mining Approach to Premium Pricing for the Automobile Insurance Industry , pp 199-227

A. C. Yeo and K. A. Smith

Ch 6 Fuzzy Logic Techniques in the Non-Life Insurance Industry , pp 229-257

Raquel Caro Carretero

Ch 7 Population Risk Management: Reducing Costs and Managing Risk in Health Insurance , pp 261-298

Ian Duncan and Arthur Robb

Ch 8 A Fuzzy Set Theoretical Approach to Asset and Liability Management and Decision Making , pp 301-333

Chiu-Cheng Chang

Ch 9 Using Neural Networks to Predict Failure in the Marketplace , pp 337-364

Patrick L. Brockett, Linda L. Golden, Jaeho Jang and Chuanhou Yang

Ch 10 Illustrating the Explicative Capabilities of Bayesian Learning Neural Networks for Auto Claim Fraud Detection , pp 365-399

Stijn Viaene, R. A. Derrig and G. Dedene

Ch 11 Merging Soft Computing Technologies in Insurance-Related Applications , pp 401-430

Arnold F. Shapiro

Ch 12 Robustness in Bayesian Models for Bonus–Malus Systems , pp 435-463

E. Gómez-Déniz and F. J. Vázquez-Polo

Ch 13 Using Logistic Regression Models to Predict and Understand Why Customers Leave an Insurance Company , pp 465-490

Montserrat Guillen, Jan Parner, Chresten Densgsoe and Ana M. Perez-Marin

Ch 14 Using Data Mining for Modeling Insurance Risk and Comparison of Data Mining and Linear Modeling Approaches , pp 493-522

Inna Kolyshkina, Dan Steinberg and N. Scott Cardell

Ch 15 Emerging Applications of the Resampling Methods in Actuarial Models , pp 523-560

Krzysztof M. Ostaszewski and Grzegorz A. Rempala

Ch 16 System Intelligence and Active Stock Trading , pp 563-585

Steve Craighead and Bruce Klemesrud

Ch 17 Asset Allocation: Investment Strategies for Financial and Insurance Portfolio , pp 587-623

K. C. Cheung and H. Yang

Ch 18 The Algebra of Cash Flows: Theory and Application , pp 625-652

W. Hürlimann

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