How big data is being used to improve fraud detection

Depending on its type and reach, fraud could result in exceptionally costly problems for businesses and even individuals. However, companies depend on big data to make fraud less likely to happen. Here are some of the ways technological advancements are gaining ground in the effort to stop fraud in various industries. Stopping so-called "serial returners" in retail. Most established companies have return policies that help create trust between the retailer and purchaser. For example, if a person has a proof-of-purchase and offers an explanation for why they want to send something back, those pieces of information may be sufficient for processing a return. Retailers, however, are learning to detect the instances when people might be returning items to participate in return fraud, and they often do that with big data. For example, a store might have compiled information about what constitutes "normal" behavior for customers who buy a certain number of items per year. Perhaps the majority of people who buy at least 40 products from a merchant per year return no more than three of them.