Wells Fargo NA, USA.
International Journal of Science and Research Archive, 2025, 14(01), 988-995
Article DOI: 10.30574/ijsra.2025.14.1.0112
Received on 02 December 2024; revised on 14 January 2025; accepted on 17 January 2025
Cloud-based credit scoring systems represent a transformative shift in financial technology, leveraging artificial intelligence and machine learning to revolutionize creditworthiness assessment. These platforms integrate traditional and alternative data sources, enabling real-time processing and comprehensive risk evaluation. The evolution from conventional methods has enhanced accessibility for underserved populations while maintaining robust security measures and regulatory compliance. Through advanced technical architecture incorporating data collection, processing, and analysis layers, these systems deliver faster, more accurate credit decisions. The implementation of sophisticated fraud detection mechanisms, coupled with machine learning algorithms, has significantly reduced false positives and improved risk assessment capabilities. Industry leaders like TransUnion demonstrate the practical success of these innovations through improved operational efficiency and expanded market reach. Despite challenges in data quality management and regulatory compliance, the future of credit scoring continues to advance with blockchain integration, enhanced real-time processing, and innovative fraud detection capabilities.
Cloud Computing; Credit Risk Assessment; Machine Learning; Financial Inclusion; Data Security
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Narendra Bhargav Boggarapu. Advanced cloud-based real-time credit scoring models: Leveraging big data and AI. International Journal of Science and Research Archive, 2025, 14(01), 988-995. Article DOI: https://doi.org/10.30574/ijsra.2025.14.1.0112.
Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0