Examination of Credit Card Transactions Driven by Machine Learning and Their Potential Uses

Abstract

According to this article, the biggest problem that customers face in the banking industry is the false crediting of monies. Conversely, credit card fraud has been there since the beginning of the industry. When faced with such a complex set of factors, many rule-based approaches to fraud detection were inadequate. But detecting fraud is critical to save consumers from paying for more credit. The government is now promoting digital money and is using machine learning methods to fight corruption. Despite the prevalence of credit and ATM cards, many consumers still may not realize how vulnerable they are to fraud. Every year, criminals steal personal data and use it to conduct fraudulent financial transactions, costing businesses and consumers billions of dollars. Implementing efficient algorithms for detecting fraud may help reduce losses. Those looking into fraud may find these algorithms' usage of complex machine learning techniques beneficial.