Fraud Call Detection using Pre-Data Feeding Method by Financial Institution

Fraudulent calls have become a pervasive threat, leading to significant financial losses and compromising the security of individuals and organizations. This project focuses on the development of a fraud call detection site aimed at combating these malicious activities and preventing financial fraud. Leveraging advanced technologies such as machine learning and anomaly detection, the site is designed to accurately identify and block fraudulent calls in real-time. The project encompasses extensive research on existing detection methodologies, the implementation of a user-friendly interface for reporting and monitoring suspicious activities, and the integration of robust algorithms to enhance detection accuracy. By providing an effective tool for detecting fraudulent calls, this project aims to reduce the incidence of financial fraud, protect potential victims, and contribute to a safer communication environment. The outcomes of this project are expected to offer valuable insights and practical solutions in the ongoing battle against fraud in the telecommunications sector.