• Rekha Dangi
• Charu Kavadia
• Shourya Dev Singh Rathore
• Shriya Ameta
• Yakshi Choubisa

AI is becoming a big force in the financial world today in areas such as credit scoring, fraud detection, etc. But since these machines have become increasingly intelligent, they have been increasingly opaque, and so it has become hard for human beings to grasp how they manage to arrive at a specific conclusion. Legacy systems are not able to handle huge and dynamic financial data sets and keeping up with emerging fraud techniques. Deep networks and other cutting-edge AI and ML techniques can produce the optimal outcomes but are sure to be viewed as "black boxes" and reduce the degree of accountability and transparency. This paper outlines the manner in which XAI tools like decision trees, LIME and SHAP facilitate regulators and users to gain confidence while opening the systems to the underlying complexity. The most effective methods of judging credit and fraud detection are support vector machines, Random Forests, and neural networks, says this report. It should be noted that the combination of XAI perspectives can greatly enhance the explanation of the decision-making process and have high prediction accuracy for ensemble or hybrid models. In general, transparency is the balancing of regulatory compliance and minimizing bias and leads to a more dependable automation of financial decisions.

Explainable Artificial Intelligence (XAI), Artificial Intelligence (AI), Machine Learning (ML), Credit Risk Assessment, Predictive Analytics, Fraud Detection, and Bias Mitigation.

"Enhancing Transparency in AI Models for Credit Scoring and Fraud Detection : A review", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 6, page no.244-249, June-2025, Available :http://www.jetir.org/papers/JETIRGW06038.pdf

"Enhancing Transparency in AI Models for Credit Scoring and Fraud Detection : A review", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 6, page no. pp244-249, June-2025, Available at : http://www.jetir.org/papers/JETIRGW06038.pdf