Fraud Measurement using Ordered Weighted Aggregation

The expansion of modern technologies and global communication is giving rise to a dramatic increase of frauds, resulting in the loss of billions of dollars world-wide each year. Fraud is an ‘unpleasant and expensive reality that all banks, retailers and credit granting companies face. It is important to provide expertise to help financial institutions to resolve and recover assets and develop a solid business experience and base its policy on successful fraud prevention and recovery. The aim of the present paper is to investigate the use of ordered weighted averaging (OWA) operators and their extensions fur fraud measurement in financial transactions.We consider the fraudulent behaviour in some components (criteria) and argue that the aggregation of the corresponding information can be effectively carried on introducing a parameterized family of aggregation operators (OWA,GOWA) that provide a fusion of pieces of information when the selection of the weights supports the modelling of some aggregation imperative depending on the rationality of the experts.