Integrating Blockchain and Artificial Intelligence for Securing Payment processes Against Fraudulent Transactions

In recent years, the fast growth of digital payment processes has raised large safety concerns, which include fraud and data breaches, prompting the need for robust safety mechanisms. Existing techniques, which include conventional rule-based systems, regularly fall quick in adaptability and accuracy, leading to multiplied vulnerabilities within the economic zone. This study proposes a unique integration of Blockchain technology with Artificial Intelligence (AI), specially making use of Generative Adversarial Networks (GANs), to enhance the security of monetary transactions. The technique includes growing a decentralized ledger device to make sure transparency and immutability, coupled with a GAN framework for real-time anomaly detection. Then behavior experiments the use of a complete dataset of monetary transactions to validate the effectiveness of the included technique. The consequences imply a considerable improvement in detecting fraudulent activities, accomplishing higher accuracy and decrease false positive rates in comparison to conventional methods. This research no longer most effective addresses the crucial safety gaps found in contemporary monetary transaction systems however additionally demonstrates the potential of integrating Blockchain and AI to create an extra stable monetary environment. The findings recommend that this integrated technique can serve as a scalable solution for enhancing transaction safety, providing valuable insights for both academia and industry practitioners.