Dr. Rajeev Kumar Arora is a distinguished technology leader, senior architect, and researcher with over two decades of experience in software development, project leadership, and innovation across global IT enterprises. Holding a Ph.D. in Computer Science, he brings deep expertise in spatial systems, artificial intelligence, machine learning, deep learning, cloud computing, cloud-based and traditional ERP systems, and big data analytics. Dr. Arora has contributed significantly to both industry and academia, leading high-impact projects in healthcare IT and digital transformation.
Throughout his career, Dr. Arora has held senior roles at prestigious organizations such as The Hackett Group, Nicklaus Children’s Hospital, Tata Consultancy Services, IBM, Capgemini, and Cognizant. He has authored numerous peer-reviewed publications in the fields of cloud security, AI in healthcare, and blockchain, and served as a reviewer, judge, and technical committee member at several international conferences.
A recognized voice in the tech community, Dr. Arora is a fellow or senior member of many esteemed professional bodies, including IEEE, British Computer Society, IETE, ACM, and AAAI. He also holds multiple Oracle and Google certifications and is a certified PMP and Scrum Professional. His contributions extend to book authorship and editorial roles, and his leadership has been acknowledged in global media and at prominent tech forums. Dr. Arora continues to shape the future of intelligent systems, cloud computing, and digital innovation through his multidisciplinary research and thought leadership.
Dr. Rajeev Kumar Arora’s research interests focus on Artificial Intelligence, Machine Learning, Deep Learning, Cloud Computing, and Big Data Analytics. He is particularly engaged in healthcare IT, cybersecurity, geospatial systems, and blockchain-based solutions.
Leveraging Big Data and Artificial Intelligence to Optimize Operational Efficiency and Strategic Decision Making in the Banking Sector
The banking industry is undergoing a significant transformation driven by the integration of Big Data analytics and Artificial Intelligence (AI) technologies. This paper presents a comprehensive analysis of how these tools are being employed to address cri tical challenges in the financial sector, including credit risk assessment, fraud detection, regulatory compliance, and customer engagement. Utilizing machine learning algorithms and advanced data processing techniques, financial institutions can extract a ctionable insights from vast and heterogeneous data sources in real time. The application of predictive analytics enhances risk modeling, while natural language processing (NLP) facilitates automated customer interaction and sentiment analysis. Furthermore , AI driven automation improves back office operations, reducing costs and improving accuracy. The paper also discusses architectural frameworks for AI Big Data deployment in banking and evaluates the ethical and regulatory considerations associated with t heir use.
This study underscores the potential of Big Data and AI to not only streamline banking operations but also to redefine strategic planning and customer centric innovation in a highly regulated environment