International Research Journal of Education and Technology

The growing digitization of financial transactions has sparked major worries about security, privacy, and fraud prevention. Traditional online payment systems frequently struggle to protect against sophisticated cyber threats including identity theft, transaction fraud, and data breaches. This article investigates the use of artificial intelligence (AI) with blockchain technology to improve the security, transparency, and efficiency of online transactions. AI-powered predictive analytics and machine learning (ML) models can spot abnormalities and fraudulent behaviors ahead of time, whilst blockchain provides data integrity, decentralization, and immutability.

To build a strong financial ecosystem, the suggested AI-enhanced blockchain framework uses real-time fraud detection algorithms, cryptographic encryption, and smart contracts. Artificial intelligence (AI) methods like natural language processing (NLP) and deep learning examine transaction patterns, identify malicious activity, and improve security measures. Distributed ledger technology (DLT), a feature of blockchain, ensures tamper-proof records, allowing for safe, verifiable transactions without the need for middlemen. The precision of fraud detection, real-time threat prevention, and adherence to financial regulations are all greatly enhanced by this connection.

KEY WORDS - AI-driven fraud detection, Blockchain security, Smart contracts, Machine learning, Decentralized finance (DeFi), Cryptographic encryption, Digital transactions, Cybersecurity, Distributed ledger technology (DLT), Anomaly detection.