Titlebook: Credit Scoring, Response Modelling and Insurance Rating; A Practical Guide to Steven Finlay Book 2010 Palgrave Macmillan, a division of Mac

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Book 2010Every year, financial services organizations make billions of dollars worth of decisions using automated?systems. For example, who to give a credit card to and the premium someone should pay for their home insurance. This book?explains how the forecasting models, that lie at the heart of these systems, are developed and deployed.

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978-1-349-36689-7Palgrave Macmillan, a division of Macmillan Publishers Limited 2010

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credit card to and the premium someone should pay for their home insurance. This book?explains how the forecasting models, that lie at the heart of these systems, are developed and deployed.978-1-349-36689-7978-0-230-29898-9

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Peter Hartz,Hilarion G. PetzoldCredit scoring models that predict the likelihood of someone repaying the credit they have applied for suffer from a problem known as sample bias.. Consider the flow through a typical credit application process, as shown in Figure 9.1.

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Validation, Model Performance and Cut-off Strategy,Once a model has been constructed, the only way it can be assessed accurately is by using an independent holdout sample. Where a model is going to be applied some time after the development and holdout samples were taken, then it is good practice to also assess the model using an out-of-time sample.