Integration of Blockchain and Machine Learning in Banking Sector

<p>The architecture design by integrating the Blockchain and Machine Learning has gained salience in information systems and information technology research. However, there has not been significant work on the comprehensive and sequential applications of Blockchain integrated Machine Learning in Banking Sector for data validation, data storage, data security and data privacy. We aim to bridge this gap in the literature and discuss how the integration of blockchain and Machine Learning can improve backward and forward linkages in Banking Sector, Machine learning tools allow banks to transform their data streams into actionable insights. The study considers use cases of bank details, transactions and other personal data to demonstrate the application of Machine Learning<br> in data collection, fraud detection, onboarding and data processing and blockchain technology for data validation, data storage, data security and data transmission. SHA256 algorithm for encrypting data in the blockchain and salting the encrypted data are utilized to make Banking.<br> systems decentralized, efficient, fault tolerant, and interoperable. The technology coupling in banking sector can create externalities such as shared benefits, improved coordination between value chain actors, and real-time decision-making for optimal resource allocation and their sustainable utilization in Banking.</p> <p> </p&gt