IT-Driven Approaches to Fraud Detection and Control in Financial Institutions

Abstract

Financial Institution of this 21st Century has witnessed an increase in the incidence and sophistication of fraud, waste and abuse in organisational processes. To ensure sustainability, there is need to fight fraud effectively and continually, dynamically and intelligently monitoring organisational processes. This paper, IT-driven approach to fraud detection and control in financial institutions x-rays the fundamentals of fraud detection and monitoring dwelling on IT-driven approaches to fraud detection and  control. The paper further gave typically applications examples using unsupervised learning in Neural Networks, case-based Reasoning, genetic algorithm and fuzzy logic. Its derivable benefits were x-rayed. It has been concluded that there is need for an IT-driven approach to fraud detection and control as a workable alternative to curb the increase and  sophistication of fraudsters.

KEYWORD: Data Mining, Artificial Neural Network, Fuzzy Logic, Case Based reasoning