• JEYASRI SEKAR

Real-time fraud prevention in digital banking involves employing advanced technologies such as machine learning and cloud infrastructure to detect and mitigate fraudulent transactions instantly, safeguarding financial institutions and customers from potential financial losses and security breaches. Some challenges in real-time fraud prevention in digital banking include handling large volumes of data in real-time, ensuring the accuracy and reliability of machine learning models, addressing evolving fraud tactics, balancing between false positives and false negatives, and maintaining compliance with regulatory requirements regarding data privacy and security. This paper developed a comprehensive approach to detect and mitigate fraudulent transactions in real-time using cloud-based infrastructure and advanced artificial intelligence techniques. The process begins with data collection from various sources, followed by preprocessing to ensure data integrity and completeness. Feature extraction techniques, including dimensionality reduction, are applied to identify key attributes indicative of fraudulent behavior. Feature selection is optimized using Improved Red Piranha Optimization (IRPO) to enhance model performance. Subsequently, machine learning models, such as Support Vector Machines (SVM), and Naïve Bayes (NB) are developed and deployed to classify transactions as fraudulent or legitimate. By leveraging cloud computing and AI, this framework enables timely detection and prevention of fraudulent activities, contributing to the security and trustworthiness of digital banking systems.

Real-Time Fraud Prevention; Digital Banking; IRPO; SVM; Cloud; Machine Learning

"REAL-TIME FRAUD PREVENTION IN DIGITAL BANKING A CLOUD AND AI PERSPECTIVE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.p562-p570, May 2023, Available :http://www.jetir.org/papers/JETIR2305G77.pdf

"REAL-TIME FRAUD PREVENTION IN DIGITAL BANKING A CLOUD AND AI PERSPECTIVE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppp562-p570, May 2023, Available at : http://www.jetir.org/papers/JETIR2305G77.pdf