In this paper, we try to validate existing theory on and develop additional insight into repeat-purchase behavior in a direct marketing setting by means of an illuminating case study. The case involves the detection and qualification of the most relevant RFM (Recency, Frequency and Monetary)...

Traditionally, customer credit scoring aimed at distinguishing good payers from bad payers at the time of the loan application. However, the timing when customers become bad is also very interesting to investigate since it can provide the bank with the ability to compute the profitability over a...

Traditionally, credit scoring aimed at distinguishing good payers from bad payers at the time of the application. The timing when customers default is also interesting to investigate since it can provide the bank with the ability to do profit scoring. Analysing when customers default is...

he Basel II capital accord encourages financial institutions to develop rating systems for assessing the risk of default of their credit portfolios in order to better calculate the minimum regulatory capital needed to cover unexpected losses. In the internal ratings based approach, financial...

One of the key decisions financial institutions have to make as part of their daily operations is to decide whether or not to grant a loan to an applicant. With the emergence of large-scale data-storing facilities, huge amounts of data have been stored regarding the repayment behavior of past...

An important objective of data mining is the development of predictive models. Based on a number of observations, a model is constructed that allows the analysts to provide classifications or predictions for new observations. Currently, most research focuses on improving the accuracy or...

Decision trees are a widely used knowledge representation in machine learning. However, one of their main drawbacks is the inherent replication of isomorphic subtrees, as a result of which the produced classifiers might become too large to be comprehensible by the human experts that have to...