Procurement Fraud Discovery using Similarity Measure Learning

An approach to detect risks of procurement fraud is described, based on the idea to learn a similarity measure that compares an employee (or payroll) standing-data record to a creditor record, in order to detect creditors that are suspiciously similar to employees.

Abstract

Abstract. This paper describes an approach to detect hints on procurement fraud. It was developed within the context of a European Union project on fraud prevention. Procurement fraud is a special kind of fraud that occurs when employees cheat their own employers by executing or triggering bogus payments. The approach presented here is based on the idea to learn a similarity measure that compares an employee (or payroll) standing-data record to a creditor record, in order to detect creditors that are suspiciously similar to employees. To this ends, it combines several simple similarity measures like address similarity or spacial similarity using a weighting scheme. The weights, that is the overall similarity function, are learned from user input specifying whether a particular pair of payroll and creditor data records are similar. Key words: similarity measure learning, fraud detection, health care 1