AI-POWERED FINANCIAL TECHNOLOGY FOR IMPROVED INVESTMENT DECISION-MAKING AND RISK MANAGEMENT
Keywords:
Artificial Intelligence, AI, Machine Learning, Data Science, Financial Technology, Retail Investing, Smart Money, Risk Management, Personalized Financial Recommendations, Portfolio OptimizationAbstract
This paper outlines the creation of a groundbreaking AI-based retail investment application that utilizes the wisdom of renowned fund managers in the United States. Designed to bolster individual investors' decisions, manage risks, and encourage dollar-cost averaging, the App effectively addresses several challenges typically faced by retail investors, such as limited financial literacy, time limitations, and the struggle to make well-timed investments and risk evaluations. The App offers tailor-made investment advice aligning with users' individual preferences and risk tolerance, allowing them to mirror the strategies employed by successful fund managers. It also features a comprehensive analytics dashboard for tracking portfolio performance and delivers alerts about shifts in leading funds' portfolios. With a user-centric design, the application ensures accessibility and ease of use for both beginner and seasoned investors alike. Through a robust market research process encompassing interviews, feedback, and surveys, we identified the difficulties retail investors encounter and their desire for inventive financial solutions. The application taps into the industry's shift towards AI and fintech solutions, meeting the surging demand for digital investment tools. The App's ultimate goal is to enhance the retail investing experience by addressing prevalent investor challenges and delivering customized solutions. It empowers individual investors to traverse the financial market more confidently and achieve their financial objectives. The paper wraps up by underlining the prospective advantages that retail investors can reap from this approach.
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Copyright (c) 2020 Rudrendu Kumar Paul, Sourav Nandy (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
