How To Spot Credit Card Fraud Using Data Science and ML techniques
Credit card fraud detection has become increasingly sophisticated — leveraging high-quality data, advanced machine learning and analysis, and complex algorithms. Yet despite these advances, there are still gaps in our ability to detect fraud at an early stage, thus protecting your business from both the costs associated with false positives and the potential impact on your brand reputation and bottom line. The FBI estimates that $7 billion worth of credit card data is stolen every year. The problem is getting worse: According to a recent study from IBM, more than 1 million cases of credit card fraud were reported in the US in 2018 alone. Crazy right? This article will explore an overview of credit card fraud detection and ML techniques to detect fraud patterns in credit card data using machine learning algorithms such as decision trees or sequence models. What are the Challenges involved in fraud detection? Accurately huge amounts of data are processed daily, and the model d...