Multidisciplinary AI and Data Science Applications in Fintech: A Case Study from Parul University
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.
Authors
- Sanjay Agal (ORCID: https://orcid.org/0000-0003-0352-0418)
- Nikunj Bhavsar
- Krishna Raulji
- Kishori Shekokar
Institutions
- Parul University (IN)
Publication Details
- Journal
- International Journal of Latest Technology in Engineering Management & Applied Science
- Published
- 2025-06-16
- DOI
- https://doi.org/10.51583/ijltemas.2025.140500068
- Primary Topic
- Applied Advanced Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00