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.

Artificial Intelligence, Data Science, FinTech, Case Study, Machine Learning, Blockchain, Predictive Analytics, Adaptive Streaming, Cloud Security, Natural Language Processing, Parul University, Financial Inclusion, Operational Efficiency, Educational Integration

1. Agal, S., Sharma, P., Mohan, C. R., Madan, P., M. V., & Arri, H. S. (2023). Using Machine Learning Algorithms to Suggest a Method for Predictive Analysis in Data Mining. 2023 IEEE International Conference on ICT in Business Industry & Government (ICTBIG), 1–5. https://doi.org/10.1109/ICTBIG59752.2023.10456127 [Google Scholar] [Crossref]

2. Singh, N. K., et al. (2023). Deep Learning Model for Interpretability and Explainability of Aspect-Level Sentiment Analysis Based on Social Media. IEEE Transactions on Computational Social Systems. https://doi.org/10.1109/TCSS.2023.3347664 [Google Scholar] [Crossref]

3. Prof. Sanjay Agal. (2023). Advanced Data Structures and Algorithms (p. 204). Xoffencer. https://doi.org/10.5281/zenodo.10074335 [Google Scholar] [Crossref]

4. Mr. Om Prakash Singh, Dr. L. Sridhara Rao, Dr. Sanjay Agal, & Dr. Haewon Byeon. (2023). The Art of Intelligent Machines: Unleashing the Power of Machine Learning (p. 214). Xoffencer International Book Publication House. https://doi.org/10.5281/zenodo.8271928 [Google Scholar] [Crossref]

5. Agal, S. & Gokani, P. K. (2021). An Optimized Bandwidth Estimation for Adaptive Video Streaming Systems Using WLBWO Algorithm. International Journal of Interdisciplinary Telecommunications and Networking (IJITN), 13(3), 95–110. [Google Scholar] [Crossref]

6. Agal, S. & Gokani, P. K. (2022). Bandwidth Estimation and Optimized Bitrate Selection for Dynamic Adaptive Streaming Over HTTP Using RSI-GM and ISSO. International Journal of Computer Vision and Image Processing (IJCVIP), 12(1), 1–15. https://doi.org/10.4018/IJCVIP.2022010107 [Google Scholar] [Crossref]

7. Agal, S. (2023). Available Bandwidth Estimation in MANET Using FPECM-MFL-GRRSU for Adaptive Video Streaming. In Tuba, M., Akashe, S., & Joshi, A. (Eds.), ICT Systems and Sustainability. ICT4SD 2023 (Vol. 765). Springer. https://doi.org/10.1007/978-981-99-5652-4_18 [Google Scholar] [Crossref]

8. Agal, S. & Devija, P. (2020). The Analytical CRM OLAP Analysis Tools and Data Mining. In Fong, S., Dey, N., & Joshi, A. (Eds.), ICT Analysis and Applications, Lecture Notes in Networks and Systems (Vol. 93). Springer. https://doi.org/10.1007/978-981-15-0630-7_1 [Google Scholar] [Crossref]

9. Kaushal, R. K., Agal, S., N. B., Singh, R., & Singh, P. P. (2023). SVM Modeling Simulation to Evaluate the Electric Vehicle Transmitting Points. 2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI), 1–7. https://doi.org/10.1109/ACCAI58221.2023.10199360 [Google Scholar] [Crossref]

10. Byeon, H., Kaur, H., Agal, S., Kumar, S., Manu, M., & Maranan, R. (2023). IoT-Enabled Cloud-Based Fair Provable Data Possession Scheme based on Blockchain. 2023 Second International Conference On Smart Technologies For Smart Nation (SmartTechCon), 276–282. https://doi.org/10.1109/SmartTechCon57526.2023.10391469 [Google Scholar] [Crossref]

11. Thingom, C., Tammina, M. R., Joshi, A., Agal, S., Sudman, M. S. I., & Byeon, H. (2023). Revolutionizing Data Capitalization: Harnessing Blockchain for IoT-Enabled Smart Contracts. 2023 Second International Conference On Smart Technologies For Smart Nation (SmartTechCon), 490–496. https://doi.org/10.1109/SmartTechCon57526.2023.10391104 [Google Scholar] [Crossref]

12. Polireddi, N. S. A., Suryadevara, M., Venkata, S., Rangineni, S., Koduru, S. K. R., & Agal, S. (2023). A Novel Study on Data Science for Data Security and Data Integrity with Enhanced Heuristic Scheduling in Cloud. 2023 2nd International Conference on Automation, Computing and Renewable Systems (ICACRS), 1862–1868. https://doi.org/10.1109/ICACRS58579.2023.10404262 [Google Scholar] [Crossref]

13. Qin, M., Kumar, R., Shabaz, M., Agal, S., Singh, P. P., & Ammini, A. (2023). Broadcast speech recognition and control system based on Internet of Things sensors for smart cities. Journal of Intelligent Systems, 32(1), 20230067. https://doi.org/10.1515/jisys-2023-0067 [Google Scholar] [Crossref]

14. Dr. Ihtiram Raza Khan, Dr. Mukta Sandhu, Dr. Sanjay Agal, & Dr. Hemant N Patel. (2023). Principles and Practices of Network Security (p. 239). Xoffencer International Book Publication House. https://doi.org/10.5281/zenodo.7936756 [Google Scholar] [Crossref]

15. Madhavi, M., Agal, S., Odedra, N. D., Chowdhary, H., Ruprah, T. S., Vuyyuru, V. A., & El-Ebiary, Y. A. B. (2024). Elevating Offensive Language Detection: CNN-GRU and BERT for Enhanced Hate Speech Identification. International Journal of Advanced Computer Science and Applications, 15(5). https://doi.org/10.14569/IJACSA.2024.01505118 [Google Scholar] [Crossref]

16. Kartha, R. S., Agal, S., Odedra, N. D., Nanda, C. S. K., Rao, V. S., Kuthe, A. M., & Taloba, A. I. (2024). NLP-Based Automatic Summarization using Bidirectional Encoder Representations from Transformers-Long Short Term Memory Hybrid Model: Enhancing Text Compression. International Journal of Advanced Computer Science and Applications, 15(5). https://doi.org/10.14569/IJACSA.2024.01505124 [Google Scholar] [Crossref]

17. Prof. Sanjay Agal. (2023). AI in Education: Empowering Learning and Teaching (p. 208). Zenodo. https://doi.org/10.5281/zenodo.10154547 [Google Scholar] [Crossref]

18. Rathod, H., & Agal, S. (2023). A Study and Overview on Current Trends and Technology in Mobile Applications and Its Development. In Tuba, M., Akashe, S., & Joshi, A. (Eds.), ICT Infrastructure and Computing. ICT4SD 2023, Lecture Notes in Networks and Systems (Vol. 754). Springer. https://doi.org/10.1007/978-981-99-4932-8_35 [Google Scholar] [Crossref]

19. "Evaluation of Quality of Education Services in Higher Education Institutes (HEIs) in India". International Journal of Emerging Technologies and Innovative Research (JETIR), Vol. 6, Issue 6, pp. 29–32, June 2019. https://doi.one/10.1729/Journal.22328 [Google Scholar] [Crossref]

20. Prof. Sanjay Agal. (2023). Fundamentals of Operating Systems (p. 195). Xoffencer International Book Publication House. https://doi.org/10.5281/zenodo.8435114 [Google Scholar] [Crossref]

• Wind Turbine Design for Low Wind Speed Applications: Advancing Renewable Energy Systems Through Wind Tunnel Experiments
• Fast Identification for Evidences in Crime Scene with Macroscopic Properties and Portable Techniques
• Evaluating the Impact of Hello Interval Timer on OSPF Performance for Real-Time Applications Using OPNET
• The Algorithmic Fortress: Ai-Powered Cybersecurity and Anti-Fraud in The Future of Fintech
• Accident Detection on Curved Roads Using Infrared Sensors in Hilly Regions A Case of Chadoora Tehsil, Badgam (J&K)