Multidisciplinary AI and Data Science Applications in Fintech: A Case Study from Parul University
Sanjay Agal,
Nikunj Bhavsar,
Krishna Raulji and
Kishori Shekokar
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Sanjay Agal: Artificial Intelligence and Data Science, Parul University, Vadodara, 391760, India.
Nikunj Bhavsar: Artificial Intelligence and Data Science, Parul University, Vadodara, 391760, India.
Krishna Raulji: Artificial Intelligence and Data Science, Parul University, Vadodara, 391760, India.
Kishori Shekokar: Artificial Intelligence and Data Science, Parul University, Vadodara, 391760, India.
International Journal of Latest Technology in Engineering, Management & Applied Science, 2025, vol. 14, issue 5, 649-661
Abstract:
This case study from Parul University explores AI and data science applications in FinTech. Using a mixed-methods approach, we analyse real-world implementations in fraud detection, credit scoring, and customer engagement. Results show a 25% improvement in credit scoring accuracy, 40% faster fraud detection, and 30% higher customer satisfaction. The study demonstrates how multidisciplinary approaches enhance operational efficiency and financial inclusion while underscoring the need for ethical frameworks and institutional support. Findings offer a strategic blueprint for educational and industrial adoption.
Date: 2025
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