COMPARATIVE STUDY BETWEEN MUTUAL FUND AND OTHER FINANCIAL INSTITUTIONS

Abstract

In the era of digital transformation, the financial services industry is witnessing rapid evolution, driven by technological advancements and changing investor expectations. Among various financial instruments available in the market, mutual funds have emerged as a popular choice for retail and institutional investors due to their flexibility, diversification benefits, and potential for high returns. On the other hand, traditional financial institutions such as banks, non-banking financial companies (NBFCs), and insurance firms continue to offer conventional investment options like fixed deposits, recurring deposits, and life insurance plans that appeal to conservative investors seeking capital protection and guaranteed returns. The fundamental difference between these two categories lies in the risk-return profile and market exposure. This study aims to conduct a comprehensive comparative analysis of mutual funds and other financial institutions by evaluating various factors such as return on investment (ROI), risk, liquidity, investor accessibility, regulatory framework, and long-term performance. What makes this study unique is the incorporation of advanced analytics through Machine Learning (ML) and Deep Learning (DL) models. These AI-driven methods are used to predict fund/instrument performance, identify investor patterns, and provide insights into market trends. Models such as Random Forest and XGBoost are applied to classify instruments based on risk and performance, while deep learning architectures help in modeling complex financial behaviors. The integration of AI technologies into financial performance evaluation offers a predictive edge, enabling better investor decisions and personalized portfolio recommendations. This research is relevant for investors, financial advisors, and policymakers aiming to understand the evolving dynamics of the Indian investment ecosystem and the role of intelligent systems in optimizing asset allocation strategies.