2025, Vol. 6, Special Issue 2
Ethical AI in lending and credit scoring for sustainable communities
Author(s): Bharghav Madhiraju, Bharath Kumar Vemuri, Guthi Divya and T Lavanya Kumari
Abstract: In a perfect society, everyone would have the same chance to get credit, buy property, or start a business. Credit is known to be an important tool for reaching personal goals and handling money problems. But the traditional way of judging credit has had problems for a long time. As a result, not only are inequalities reinforced, but broader economic potential is also constrained. Recently, new developments in Artificial Intelligence (AI) have brought helpful new options. Unlike older methods, AI can look at large and different types of data, helping to find patterns that were missed before. If used carefully, AI can help make lending decisions that are fairer and more accurate. This study looks at how AI can be used to improve access to financial services, reduce unfairness in credit checks, and improve services like fraud detection and support for different languages. Despite these advancements, AI must not be viewed as a flawless remedy. If not carefully constructed, AI systems risk perpetuating the very biases they are intended to eliminate. Furthermore, decision-making may occur within opaque "black box" models, making outcomes difficult to interpret. If training data contains historical prejudices or if fairness is not embedded into development processes, further harm can result. Therefore, a responsible and ethical approach to AI development in finance is not only recommended but necessary. This research focused on responsible AI design within financial systems. A neural network was employed to forecast credit scores, and a technique known as SMOTE was applied to ensure demographic balance within the training data. However, predictive accuracy alone was not prioritized. Fairness evaluations, including metrics like demographic parity and equalized odds, were conducted to assess group-level impacts. To increase model transparency, interpretability tools such as SHAP and LIME were utilized, enabling the rationale behind decisions to be examined more closely. The study demonstrates that an inclusive financial environment can be supported through the ethical application of AI. Systems that are fair, open, and responsible are more likely to give people equal access to financial services. This study provides a clear plan that banks and other financial institutions can use to apply AI in the right way, so more people can get the financial opportunities they deserve.
DOI: 10.22271/27084515.2025.v6.i2Sc.709
Pages: 285-290 | Views: 170 | Downloads: 47
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How to cite this article:
Bharghav Madhiraju, Bharath Kumar Vemuri, Guthi Divya, T Lavanya Kumari. Ethical AI in lending and credit scoring for sustainable communities. Asian J Manage Commerce 2025;6(2S):285-290. DOI: 10.22271/27084515.2025.v6.i2Sc.709
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