Credit Intelligence and Modelling provides an indispensable explanation of the statistical models and methods used when assessing credit risk and automating decisions.
Over eight modules, the book covers consumer and business lending in both the developed and developing worlds, providing the frameworks for both theory and practice. It first explores an introduction to credit risk assessment and predictive modelling, micro-histories of credit and credit scoring, as well as the processes used throughout the credit risk management cycle. Mathematical and statistical tools used to develop and assess predictive models are then considered, in addition to project management and data assembly, data preparation from sampling to reject inference, and finally model training through to implementation.
Although the focus is credit risk, especially in the retail consumer and small-business segments, many concepts are common across disciplines, whether for academic research or practical use. The book assumes little prior knowledge, thus making it an indispensable desktop reference for students and practitioners alike.
Credit Intelligence and Modelling expands on the success of The Credit Scoring Toolkit to cover credit rating and intelligence agencies, and the data and tools used as part of the process.