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By A. F. Shapiro, L. C. Jain

This publication provides fresh advances within the idea and implementation of clever and different computational recommendations within the assurance undefined. The paradigms coated surround man made neural networks and fuzzy platforms, together with clustering types, optimization and resampling tools, algebraic and Bayesian versions, selection timber and regression splines. therefore, the focal point is not only on clever ideas, even though those represent a big part; the publication additionally bargains with different present computational paradigms which are more likely to effect at the undefined. the appliance components comprise asset allocation, asset and legal responsibility administration, cash-flow research, declare expenditures, category, fraud detection, insolvency, investments, loss distributions, advertising and marketing, pricing and charges, rate-making, retention, survival research, and underwriting.

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Extra resources for Intelligent and Other Computational Techniques in Insurance: Theory and Applications (Series on Innovative Intelligence, 6)

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To this end, they compared the performance of NN with four linear models, a random walk process and three different specifications based on the purchasing power parity theory. They found mixed results. In experiments with quarterly data, they found no advantage in the use of NNs for forecasting the exchange rate, while the performance of the NNs clearly improves when they were trained on monthly data. Lokmic and Smith (2000) investigated the problem of forecasting when checks issued to retirees and beneficiaries will be presented for payment, in order to forecast daily cash flow requirements.

1996), which focuses on the categories of derivatives and termstructure models, foreign exchange, equities and commodities, and corporate distress and risk models. Two examples involving cash flow issues follow. Boero and Cavalli (1996) investigated a NN model for forecasting the exchange rate between the Spanish peseta and the US dollar. Their goal was to examine whether potentially highly nonlinear NN models outperform traditional methods or give at least competitive results. To this end, they compared the performance of NN with four linear models, a random walk process and three different specifications based on the purchasing power parity theory.

They began by calculating several possible trends using ac- 34 A. F. Shapiro cepted statistical procedures and for each trend they determined the degree to which the estimate was good by intersecting several fuzzy goals. They suggested that one may choose the trend that has the highest degree of goodness and proposed that a trend that accounts for all the trends can be calculated by forming a weighted average using the membership degrees as weights. They concluded that FL provides an effective method for combining statistical and judgmental criteria in insurance decision-making.

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