Credit Card Transaction Analysis Using Machine Learning and Its Practical Uses

Abstract

According to this article, the biggest problem that customers face in the banking industry is the fraudulent crediting of amounts. However, scams have been around with credit card innovation from the start. Due to the overwhelming amount of variables, many rule-based approaches used for fraud detection in the past failed. But detecting fraud is critical to stop consumers from paying for extra credit. In addition to promoting digital currency in the modern era, the government is using machine learning techniques to fight corruption. Despite the prevalence of credit and ATM cards, many consumers still do 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. It is possible to reduce losses by using efficient algorithms that detect fraud. Investigators looking into fraud may benefit from the complex machine learning techniques used by these algorithms.