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

Year: 2025

Type: article

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.

Source: International Journal of Latest Technology in Engineering Management & Applied Science

DOI: 10.51583/ijltemas.2025.140500068

Authors: Sanjay Agal, Nikunj Bhavsar, Krishna Raulji, Kishori Shekokar

Institution: Parul University

Language: English

Topic: FinTech, Crowdfunding, Digital Finance

Subfield: Management Information Systems

Field: Business, Management and Accounting

Domain: Social Sciences

Open Access status: hybrid

OpenAlex ID: W4411335670

FWCI:

Cites: 19

Cited by:

Related to: 10