The rapid growth of Internet banking has necessitated advanced systems for secure, real-time decision making. This paper introduces BankNet, a predictive analytics framework integrating big data tools and a BiLSTM neural network to deliver high-accuracy transaction analysis. BankNet achieves exceptional predictive performance, with a Root Mean Squared Error of 0.0159 and fraud detection accuracy of 98.5%, while efficiently handling data rates up to 1000 Mbps with minimal latency. By addressing critical challenges in fraud detection and operational efficiency, BankNet establishes itself as a robust decision support system for modern Internet banking. Its scalability and precision make it a transformative tool for enhancing security and trust in financial services.