Enhancing Financial Insights: Integration of various Machine Learning Techniques - Gunjal, S. N.; Shiyamala, S.; D. Halle, Priyanka; Deshpande, Anuradha S; Gade, Minal Vilas; Jadhav, Tushar (International Journal of Intelligent Systems and Applications in Engineering, 2024)
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.