Evaluating the impact of AI and blockchain on credit risk mitigation: A predictive analytic approach using machine learning
Year: 2024
Type: article
Abstract: In recent years, the integration of artificial intelligence (AI), blockchain technology, and machine learning has transformed credit risk mitigation strategies in the financial industry. This paper explores the practical applications of these technologies in identifying, assessing, and managing credit risk, with a specific focus on predictive analytics and decentralized frameworks. Through a comprehensive literature review and case studies, the research demonstrates how AI-driven algorithms, blockchain's transparent and immutable ledger systems, and machine learning models have enhanced the precision and efficiency of credit risk evaluations. Additionally, the study investigates how these innovations are being adopted by financial institutions to create more accurate credit scoring systems, reduce fraud, and optimize operational risk management. While these technologies hold great promise, challenges such as data privacy, regulatory compliance, and implementation costs remain significant barriers. The paper concludes with recommendations for overcoming these challenges and maximizing the potential of AI, blockchain, and machine learning in credit risk mitigation.
Author: ZAHIDUR RAHMAN FARAZI
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4402802149