Enhancing Financial Insights: Integration of various Machine Learning Techniques

Authors

  • S. N. Gunjal Computer Engineering Department, Sanjivani College of Engineering Kopargaon (An Autonomous Institute) Affiliated to Savitribai Phule Pune University Pune, Maharashtra, India.
  • S. Shiyamala Professor/ECE, Vel Tech Rangarajan Dr Sagunthala R & D Institute of Science and technology
  • Priyanka D. Halle SPPU, SKNSITS Lonavala
  • Anuradha S Deshpande ASSOCIATE PROFESSOR, Faculty of Science and Technology, JSPM UNIVERSITY PUNE
  • Minal Vilas Gade Associate Professor, E&TC Department, SITRC, Sandip Institute of Technology & Research Centre, Nashik
  • Tushar Jadhav Associate Professor, E and TC, Vishwakarma Institute of Information Technology, Pune 48

Keywords:

Financial Insights, Data Analytics, Finance Technology, Predictive Analytics, Risk Management, Interpretability

Abstract

The convergence of machine learning has catalyzed a paradigm shift in the financial realm, empowering institutions to glean deeper insights and make informed decisions. This abstract explores the multifaceted integration of these technologies, unveiling their impact on financial operations, risk management, predictive analytics, and customer-centric services. By harnessing vast datasets and leveraging sophisticated algorithms, this fusion enables proactive risk assessment, precise predictive models, and personalized financial strategies. However, while revolutionizing the sector, it poses challenges in ethical use, data privacy, and interpretability. This studydelves into the transformative potential and the accompanying considerations in the synthesis of machine learning within the financial domain.

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Published

23.02.2024

How to Cite

Gunjal, S. N. ., Shiyamala, S. ., D. Halle, P. ., Deshpande, A. S. ., Gade, M. V. ., & Jadhav, T. . (2024). Enhancing Financial Insights: Integration of various Machine Learning Techniques. International Journal of Intelligent Systems and Applications in Engineering, 12(17s), 644–650. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4930

Issue

Vol. 12 No. 17s (2024)

Section

Research Article

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