risk intelligence

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.

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Copy the following link for free access to the first chapter of this title: http://www.springerlink.com/content/j23468h304310755/fulltext.pdf This book is a warning. It aims to warn policy-makers, industry, academia, civil society organisations, the media and the public about the threats and vulnerabilities facing our privacy, identity, trust, security and inclusion in the rapidly approaching world of ambient intelligence (AmI). In the near future, every manufactured product – our clothes, money, appliances, the paint on our walls, the carpets on our floors, our cars, everything – will be embedded with intelligence, networks of tiny sensors and actuators, which some have termed “smart dust”. The AmI world is not far off. We already have surveillance systems, biometrics, personal communicators, machine learning and more. AmI will provide personalised services – and know more about us – on a scale dwarfing anything hitherto available. In the AmI vision, ubiquitous computing, communications and interfaces converge and adapt to the user. AmI promises greater user-friendliness in an environment capable of recognising and responding to the presence of different individuals in a seamless, unobtrusive and often invisible way. While most stakeholders paint the promise of AmI in sunny colours, there is a dark side to AmI. This book aims to illustrate the threats and vulnerabilities by means of four “dark scenarios”. The authors set out a structured methodology for analysing the four scenarios, and then identify safeguards to counter the foreseen threats and vulnerabilities. They make recommendations to policy-makers and other stakeholders about what they can do to maximise the benefits from ambient intelligence and minimise the negative consequences.

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This book constitutes the thoroughly refereed joint post-workshop proceedings of four international workshops organized by the Japanese Society for Artificial Intelligence, held in Miyazaki, Japan, in June 2007 during the 21st Annual Conference JSAI 2007.

The volume starts with 7 award winning papers of the JSAI 2007 main conference that are accompanied by 24 revised full workshop papers, carefully reviewed and selected from the following four co-located international workshops: Logic and Engineering of Natural Language Semantics (LENLS 2007), International Workshop on Risk Informatics (RI2007), Fifth Workshop on Learning with Logics and Logics for Learning (LLLL 2007), and First International Workshop on Juris-informatics (JURISIN 2007).

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