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Procurement Fraud Discovery using Similarity Measure Learning (2008)
| Content Provider | CiteSeerX |
|---|---|
| Author | Günter, Björn Grosskreutz, Henrik Punko, Natalja Rüping, Stefan |
| Abstract | Abstract. This paper describes an approach to detect risks of 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 on 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 spatial 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. This leads to an adaptive, easily transferable approach for a generic class of fraud opportunities. |
| File Format | |
| Publisher Date | 2008-01-01 |
| Publisher Institution | In: Transactions on Casebased Reasoning |
| Access Restriction | Open |
| Subject Keyword | Overall Similarity Function European Union Project Spatial Similarity Bogus Payment User Input Several Simple Similarity Measure Transferable Approach Generic Class Fraud Prevention Similarity Measure Learning Address Similarity Creditor Record Creditor Data Record Procurement Fraud Discovery Weighting Scheme Fraud Opportunity Procurement Fraud Special Kind Particular Pair Similarity Measure Standing-data Record |
| Content Type | Text |
| Resource Type | Article |
