Risk Management in the Financial Sector: An Artificial Intelligence-Based System for Fraud Detection

Banking fraud is a serious and ongoing problem that involves attempting to deceive financial institutions in order to gain money or other benefits. Every year, banks lose millions of dollars due to various types of fraud, such as fake documents and other forms of deception. Online transaction fraud and fraudulent bank loan applications are among the most common types of fraud. To address this issue, a study has been conducted to investigate a system that utilizes machine learning techniques to identify suspicious activities and detect irregularities in online transactions. By analyzing large amounts of data, this system can quickly and accurately identify potential fraud, helping banks to minimize financial losses and protect their customers' assets. In addition to detecting fraud, this technology also improves risk management for banks and their customers. By providing an early warning system for potential fraud, the system helps customers to avoid becoming victims of fraud and reduces the need for costly and time-consuming investigations. Overall, this study offers a promising approach for combating banking fraud and protecting the interests of banks and their customers.