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@article{176534,
        author = {Gaurav Mirkute and Dnyaneshwari Arbat and Sarika Bawaskar},
        title = {Financial Dashboard for Investment Recommendation and Tracking},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {6121-6124},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=176534},
        abstract = {The "Financial Dashboard for Investment Recommendation and Tracking" is a comprehensive web-based platform designed to offer personalized investment planning and tracking services. The system collects essential user information such as age, salary, expenses, savings, financial responsibilities, and future goals to generate tailored investment suggestions.
It recommends a range of investment options, including stocks, mutual funds, fixed deposits (FDs), cryptocurrencies, and commodities, based on each individual's financial situation and risk tolerance. The platform leverages machine learning algorithms, specifically collaborative filtering, and content-based filtering, to analyse user data and preferences for more accurate and personalized investment recommendations.
The collaborative filtering approach uses the preferences of users with similar profiles to suggest suitable investments, while the content-based filtering method focuses on an individual’s profile and past behaviour to ensure relevance. These advanced algorithms enhance the platform's accuracy, delivering customized strategies that align with the user's financial goals and risk capacity.
In addition to personalized recommendations, the platform includes a tracking mechanism that monitors the growth of investments over time, offering users real-time insights and performance reports.
Overall, the "Financial Dashboard for Investment Recommendation and Tracking" aims to empower individuals to make informed financial decisions, helping them achieve long-term stability and growth in their investments.},
        keywords = {collaborative filtering, content-based filtering, real-time insights, recommendation system, risk tolerance.},
        month = {April},
        }