Multidisciplinary AI and Data Science Applications in Fintech: A Case Study from Parul University

Sanjay Agal, Nikunj Bhavsar, Krishna Raulji and Kishori Shekokar
Additional contact information
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
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.ijltemas.in/DigitalLibrary/Vol.14Issue5/649-661.pdf (application/pdf)
https://www.ijltemas.in/papers/volume-14-issue-5/649-661.html (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bjb:journl:v:14:y:2025:i:5:p:649-661

Access Statistics for this article

International Journal of Latest Technology in Engineering, Management & Applied Science is currently edited by Dr. Pawan Verma

More articles in International Journal of Latest Technology in Engineering, Management & Applied Science from International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS)
Bibliographic data for series maintained by Dr. Pawan Verma ().