BlockFin: AI and Blockchain Synergy for Secure Digital Financial Systems

The ever-growing technology has set a new record for digital transactions taking place all over the world. The forging of digital transactions has paved the way for a new medium of interconnected transactions. However, the inclusion of digital transactions has led to the need to combat the various security issues that occur parallel to it. The limitations of digital transactions include its dependence on technology and various technological gaps between people, which may lead to privacy concerns. Money laundering is one of the main types of fraud in transactional data. It is the process of converting money obtained from criminal illicit activities such as break-ins and drug trafficking and converting into such that it is legally obtained. The dataset used in this paper follows the rules related to all processes of cashing in and transferring. Money laundering hurts both people and the economy, which results in loss of investor confidence and reduced tax revenues. The leveraging of the combined power of machine learning (ML) and blockchain technology has proved to be a promising strategy for combating fraudulent activities. The fusion of blockchain and ML techniques not only provides security but also reduces the risk of fraud and increases transparency in comparison to the previous state-of-the-art techniques and experimentation. It is observed that a maximum accuracy of 91% is attained using the K-nearest neighbor algorithm (KNN). Furthermore, the integration of blockchain ensures security through the use of Smart contracts, providing an additional layer of security.