Economic Insights: The Computational Intelligence Perspective on Finance
artificial intelligence; blockchain technology; cloud computing; machine learning; natural language processing; predictive analytics; risk mitigation; sentiment analysis
Using technological advancements and shifting risk landscapes as a driving force, this abstract investigates the revolutionary approaches that have reshaped risk mitigation in contemporary contexts. Introducing a new era of proactive risk management has been made possible by the combination of artificial intelligence (AI), machine learning (ML), and predictive analytics. Organizations are able to recognize patterns and anticipate potential risks with an accuracy that has never been seen before, thanks to these technologies, which analyze vast datasets. By extracting valuable insights from unstructured data sources, natural language processing (NLP) and sentiment analysis broaden the scope of risk assessment with their respective capabilities. Blockchain technology improves both transparency and security, particularly in the realm of financial transactions, thereby lowering the likelihood of fraudulent activity. Cloud computing makes dynamic risk modeling easier to accomplish, which in turn makes it possible to simulate real-time scenarios. The cumulative effect of these innovations not only improves the efficiency of risk reduction, but it also helps organizations develop risk management frameworks that are more agile and resilient. When navigating the complexities of a risk landscape that is constantly shifting, it is essential to strike a balance between technological advancements, ethical considerations, and transparency. 2026 by Apple Academic Press, Inc.
Nanda, Sudhansu Sekhar; Biswal, Sthitipragyan; Indoria, Devadutta; Palav, Manesh R.; Babu, S. B. G. Tilak; Patil, Anand
Computational Intelligence Solutions for Real-Life Problems;pp.113-130
Restricted Access; Hardcopy may be available in the library
https://doi.org/10.1201/9781998511013-7 https://www.scopus.com/pages/publications/105024027044?origin=resultslist
Nanda S.S., Faculty of Management Studies, Sri Sri University, Odisha, Cuttack, India; Biswal S., Symbiosis School of Banking and Finance, Symbiosis International, Pune, India; Indoria D., Department of Commerce, Vikram Dev University, Odisha, Jeypore, India; Palav M.R., Department of MBA, Global Business School and Research Center, Dr. D. Y. Patil Vidyapeeth, Maharashtra, Pune, India; Babu S.B.G.T., Department of Electronics and Communication Engineering, Aditya Engineering College, Andhra Pradesh, Surampalem, India; Patil A., School of Business and Management, Christ University, Karnataka, Bangalore, India