Data Science and Machine Learning's Potential for Fraud Detection

The consumer marketplace has been a hot spot for fraud lately. This is due in part to the rise in more digitally focused transactions amid the pandemic and the evolving way we communicate with our banks. We're seeing a rise in fraud risk surrounding applications that are newer to the market, like digital wallets, buy now pay later (BNPL), peer-to-peer (P2P) payments as well as those that have been in the market for a while such as bank transfers and card not present (CNP) payment methods. Consumers are attracted to these methods because they're convenient, meaning it's pivotal to control the rise in fraud risk to reduce customer inconvenience and friction so these more innovative payment methods can keep entering the market. We're seeing these obstacles primarily in industries like retail because the e-commerce space has been a big proponent of CNP payment methods.