Fraud Detection Analysis In Data Science
Originally published on Medium on Jul 22, 2020, this article explores how data science techniques are used to detect and prevent fraudulent activities across industries such as banking, e-commerce, and finance. It covers the role of machine learning, predictive analytics, anomaly detection, and data-driven models in identifying suspicious transactions and reducing financial risk. This page contains a brief preview of the original article. To read the complete guide with detailed explanations and real-world examples, continue reading on Medium using the button below.
