AI in Credit Card Fraud Detection: Innovations and Future Directions

Abstract

In 2019, a significant financial institution named JP Morgan Chase & Co. adopted an AI-driven fraud detection system that saved $120 million by identifying and preventing fraudulent transactions with an accuracy of 96%; this shows the quantitative impact of artificial intelligence credit fraud detection [4].Historically, AI has evolved from the usage of complex machine learning models and increasing their accuracy in the field of fraud detection. Machine learning uses large amounts of data, leverages its advanced models, and identifies patterns and anomalies that indicate fraudulent activities surpassing traditional methods.In this paper, we will talk about the latest advancements in AI for fraud detection, including the use of neural networks, deep learning, and deep learning analytics. We will also see how these technologies have changed the detection process, making it faster and more reliable. Moreover, we will discuss future directions, such as the adoption of blockchain technology and advanced customer authentication methods.