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Credit scoring, response modelling a...

Finlay, Steven, (1969-)

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Credit scoring, response modelling and insurance rating = a practical guide to forecasting consumer behaviour /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Credit scoring, response modelling and insurance rating/ Steven Finlay.
Reminder of title:	a practical guide to forecasting consumer behaviour /
Author:	Finlay, Steven,
Published:	Houndmills, Basingstoke ;Palgrave Macmillan, : 2010.,
Description:	1 online resource (xiv, 280 p.) :ill.
[NT 15003449]:	Project Planning -- Sample Selection -- Gathering and Preparing Data -- Understanding Relationships In Data -- Data Pre-Processing -- Model Construction (Parameter Estimation) -- Validation, Model Performance and Cut-off Strategy -- Sample Bias and Reject Inference -- Implementation and Monitoring.
Subject:	Credit analysis. -
Online resource:	http://www.palgraveconnect.com/doifinder/10.1057/9780230298989An electronic book accessible through the World Wide Web; click for information
ISBN:	9780230298989 (electronic bk.)

Credit scoring, response modelling and insurance rating = a practical guide to forecasting consumer behaviour /
Finlay, Steven,1969-

Credit scoring, response modelling and insurance ratinga practical guide to forecasting consumer behaviour /[electronic resource] :Steven Finlay. - Houndmills, Basingstoke ;Palgrave Macmillan,2010. - 1 online resource (xiv, 280 p.) :ill.

Includes bibliographical references and index.

Project Planning -- Sample Selection -- Gathering and Preparing Data -- Understanding Relationships In Data -- Data Pre-Processing -- Model Construction (Parameter Estimation) -- Validation, Model Performance and Cut-off Strategy -- Sample Bias and Reject Inference -- Implementation and Monitoring.

Within the financial services industry today, most decisions on how to deal with consumers are made automatically by computerized decision making systems. At the heart of these systems lie mathematically derived forecasting models. These use information about people and their past behaviour, to predict how people are likely to behave in the future. For example, who is likely to repay a loan, who will respond to a mail shot and the likelihood that someone will claim on their household insurance policy. Decisions about how to treat people are then made on the basis of the predictions calculated by the system. This book provides a step-by-step guide to how the forecasting models used by the worlds leading financial institutions are developed and deployed. It covers all stages involved in the construction of such a model, including project management, data collection, sampling, data pre-processing, model construction, validation, implementation and post-implementation monitoring of the model's performance.

ISBN: 9780230298989 (electronic bk.)

Standard No.: 9786612999215

Source: 335984Palgrave Macmillanhttp://www.palgraveconnect.comSubjects--Topical Terms:

749169
Credit analysis.
Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: HG3701 / .F55 2010

Dewey Class. No.: 658.8/342

Credit scoring, response modelling and insurance rating = a practical guide to forecasting consumer behaviour /
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504 $a Includes bibliographical references and index.
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520 $a Within the financial services industry today, most decisions on how to deal with consumers are made automatically by computerized decision making systems. At the heart of these systems lie mathematically derived forecasting models. These use information about people and their past behaviour, to predict how people are likely to behave in the future. For example, who is likely to repay a loan, who will respond to a mail shot and the likelihood that someone will claim on their household insurance policy. Decisions about how to treat people are then made on the basis of the predictions calculated by the system. This book provides a step-by-step guide to how the forecasting models used by the worlds leading financial institutions are developed and deployed. It covers all stages involved in the construction of such a model, including project management, data collection, sampling, data pre-processing, model construction, validation, implementation and post-implementation monitoring of the model's performance.
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