Integrating Artificial Intelligence and Blockchain for Secure Financial Transactions: A Computer Science Perspective
Keywords:
Artificial Intelligence, Blockchain Technology, Financial Transactions, Fraud Detection, Machine Learning, Deep Learning, Smart Contracts, Cybersecurity, Distributed Ledger, FinTech SystemsAbstract
The rapid expansion of digital financial systems has significantly increased the need for secure, transparent, and efficient transaction mechanisms. However, traditional financial infrastructures remain vulnerable to fraud, cyberattacks, data manipulation, and centralized control risks. This paper presents an integrated approach combining Artificial Intelligence (AI) and Blockchain technology to enhance the security and reliability of financial transactions from a computer science perspective. AI techniques, including machine learning and deep learning models, are employed for real-time fraud detection, anomaly identification, and predictive risk assessment. Simultaneously, Blockchain provides a decentralized, immutable ledger that ensures transparency, traceability, and tamper-proof record keeping of financial activities. The proposed hybrid framework enables intelligent transaction validation through AI-driven decision-making followed by secure verification and storage using blockchain-based smart contracts. This integration improves detection accuracy, reduces fraudulent activities, and enhances system trust without compromising performance efficiency. Furthermore, the study highlights key implementation challenges such as scalability, computational overhead, and integration complexity. The results indicate that combining AI with blockchain significantly strengthens financial transaction security compared to conventional systems. This research contributes to the development of next-generation intelligent financial infrastructures suitable for banking, fintech, and global digital payment ecosystems.
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