Credit scoring is the term used to describe formal statistical methods used for classifying
applicants for credit into 'good'and 'bad'risk classes. Such methods have become …

Credit scoring and behavioural scoring are the techniques that help organisations decide
whether or not to grant credit to consumers who apply to them. This article surveys the …

Data mining is the discovery of interesting, unexpected or valuable structures in large
datasets. As such, it has two rather different aspects. One of these concerns large …

Consequential decision-making incentivizes individuals to strategically adapt their behavior
to the specifics of the decision rule. While a long line of work has viewed strategic adaptation …

Credit Risk Management: Basic Concepts is the first book of a series of three with the
objective of providing an overview of all aspects, steps, and issues that should be …

An introduction to statistical data mining, Data Analysis and Data Mining is both textbook
and professional resource. Assuming only a basic knowledge of statistical reasoning, it …

Methods for assessing the credit risk when lending to consumers has been in operation for
50 years. Yet, there are probably now more opportunities and challenges for research into …

This paper proposes a Bayesian network model to address censoring, class imbalance and
real-time implementation issues in credit risk scoring. It shows that the Bayesian network …

The consumer credit market is experiencing unprecedented change, increased competition,
and new challenges. To cope with these developments, increasingly sophisticated …

The purpose of this article is to show that Bayesian methods, coupled with Markov chain
Monte Carlo computational techniques, can be successfully employed in the analysis of …