Fraud Detection and Prevention by using Big Data Analytics

Abstract

A retail sector is a group of organization or people who sell goods or services for gaining income. Fraud is wrongful or criminal activities for the economic and personal benefits. Fraud detection is finding actual or expected fraud which takes place in an organization and in the retail market is one of the challenging aspects. Fraud is mischievous activities occur in retail sector includes shoplifting, skimming, replicating cards from skimmed data, counterfeiting, bar code or POS(Point-of-Sale) manipulation, contamination, mislabeling, substitute cheaper ingredients instead of high-quality ingredients. Fraudulent activities occur in the retail sector by both consumer and supplier. Analyzing financial crimes related to fraudulent activities is difficult where traditional data mining techniques fail to address all of them. Big data analytics is used to identify an unusual pattern to detect and prevent fraud in the retail sector. Various predictive analytics tools are used to handle massive data and their pattern.