The seminar will describe experience with a large-scale database of debit card transactions, with patterns of fraudulent usage. Data cleaning was performed on this material, followed by data visualisation and statistical analysis to determine the most useful features, and experiments with the results of the analysis. Several decision trees with different features were constructed during this activity. The experiments show that "hand crafted" business rules are more effective discriminators than those generated by decision trees.