AI-Powered Credit Assessment in FinTech: Loan Approval Efficiency and Customer Satisfaction in Financial Institutions
Renuka K
Assistant Professor and Head, Department of MBA, SVR College of Commerce & Management Studies, Affiliated to Bangalore University, Bangalore. Karnataka, India.
Kavya S
Assistant Professor, Department of MBA, SVR College of Commerce & Management Studies, Bangalore. Affiliated to Bangalore University, Bangalore. Karnataka, India.
The rapid advancement of financial technology (FinTech) has profoundly reshaped lending operations in financial institutions, with artificial intelligence (AI) emerging as a pivotal enabler of automated credit assessment and streamlined loan approval processes. AI-powered credit scoring systems employ advanced machine learning algorithms and analyze extensive volumes of structured and unstructured data to assess borrower creditworthiness with greater accuracy, consistency, and efficiency than traditional methods. This study investigates the role of AI-driven tools in enhancing loan approval efficiency and improving customer satisfaction within financial institutions operating in a digital financial ecosystem. Using a quantitative research design, primary data were collected from customers who have engaged with AI-based lending services. The study focuses on how AI-driven credit assessment significantly accelerates loan processing, enhances the accuracy and consistency of lending decisions, and promotes transparency in approval procedures. Despite these operational and experiential benefits, the study highlights challenges related to algorithmic bias, data privacy, and the limited explainability of automated decision-making systems. These challenges emphasize the importance of implementing robust governance structures, ethical AI practices, and regulatory oversight to ensure accountability, fairness, and transparency in digital lending. By demonstrating that AI-powered credit assessment can simultaneously improve operational efficiency and enhance customer satisfaction, this study contributes to the growing body of FinTech literature while fostering higher levels of customer satisfaction and trust. The study’s findings will provide practical insights for financial institutions seeking to integrate AI responsibly and effectively into their lending operations, highlighting the balance between technological efficiency and ethical considerations in AI-enabled credit services.
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