Responsible AI framework for Credit Scoring

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We hope this article sheds light on what might seem like a dry or overly technical topic—Responsible AI in Credit Scoring—and turns it into something meaningful, engaging, and even vital. Credit scoring isn't just an abstract problem for financial analysts, technologists, or regulators to solve. It's a mechanism that affects livelihoods, shapes opportunities, and touches lives, often in profound ways. In exploring how we can make AI-driven systems in this space more ethical, transparent, and fair, this article addresses questions that are as much about human dignity as they are about algorithms. If nothing else, we hope this piece encourages you to see the critical intersection of technology, ethics, and society in a new light and inspires you to think more deeply about how AI shapes our world

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This study is important because the increasing use of AI in credit scoring has significant implications for financial inclusion, fairness, and ethical decision-making. While AI enhances efficiency and accuracy, it also raises concerns about bias, transparency, and accountability, potentially leading to unfair lending practices. By systematically reviewing existing research, this study provides valuable insights into responsible AI practices, helping financial institutions, policymakers, and researchers develop fairer, more transparent, and ethically sound credit scoring systems. Ensuring responsible AI adoption is crucial for maintaining trust in financial systems and protecting consumers from unintended discrimination.

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