Segmentation in Markov chain consumer behaviour models

Contents * A: Historical development of credit and behavioural scoring * R W Johnson: Legal, social and economic issues in implementing scoring in the US * R Eisenbeis: Problems in applying discriminant analysis in credit scoring models * M A Hopper and E M Lewis: Behaviour scoring and adaptive control systems * B: Objectives and measures in credit scoring * A D Wilkie: Measures for comparing scoring systems * G Wilkinson and J Tingay: The use of affordability data - does it add real value? * R L Keeney and R M Oliver: Improving lender offers using consumer preferences * C: Practical implementation of scoring systems * A Lucas: Updating scorecards: Removing the mystique * R M Oliver and E Wells: Efficient frontier cut-off policies in credit portfolios * D: Features of scoring * D J Hand and W E Henley: Can reject inference ever work? * G A Overstreet Jr, E L Bradley, and R S Kemp Jr: The flat-maximum effect and generic linear scoring models: a test * J N Crook, L C Thomas, and R Hamilton: The degradation of the scorecard over the business cycle * G Bennett, G Platts, and J Crossley: Inferring the inferred * E: Other applications of scoring in credit risk * K J Leonard: Detecting credit card fraud using expert systems * G Platts and I Howe: A single European scorecard * A Lucas and J Powell: Small sample scoring * F: Alternative approaches to scoring systems * B Narain: Survival analysis and the credit granting decision * P Sewart and J Whittaker: Graphical models in credit scoring * M B Yobas, J N Crook, and P Ross: Credit scoring using neural and evolutionary techniques * J Ho, L C Thomas, T A Pomrey, and W T Scherer: Segmenting in Markov chain consumer credit behaviour models