MAT012 - Credit Risk Scoring

Catalogue Entry

The course aim is to present a comprehensive review of the objectives, methods and practical implementations of credit and behavioural scoring in particular and data mining in general. It involves understanding how large data sets can be used to model customer behaviour and how such data is gathered, stored and interrogated and it use to cluster, segment and score individuals. The aim is to look at the largest application in more detail. Credit scoring is the process of deciding, whether or not to grant or extend a loan. Sophisticated mathematical and statistical models have been developed to assist in such decision problems.

Semester

Spring

Lecturer

Dr Meko So

Recommended Books

The following books are recommended texts for this module:-

L.C.Thomas, J.N.Crook, D.B.Edelman, Credit Scoring and its Applications, SIAM Press, Philadelphia, (2002).

H.McNab, A Wynn, Principles and Practice of Consumer Credit Risk Management, CIB Publishing, Canterbury (2000).

S.Jacka, D.J.Hand, Statistics in Finance, Edward Arnold, (1997).

L.C.Thomas, J.N.Crook, D.B.Edelman, Readings in Credit Scoring, OUP, (2004).

E.M.Lewis An Introduction to Credit Scoring, Athena Press, San Rafael, (1992).

E. Mays. Credit Scoring for Risk managers, South Western, Mason, (2004).

D.M.Hand, H.Mannila, P.Smyth, Principles of Data mining, MIT Press (2001).

N. Siddiqi Credit Risk Scorecards, Wiley/SAS (2006).