Smart Tool for Streamlining Mutual Fund Insights through Efficient Data Analysis from Financial News

In the dynamic world of mutual fund investments, research analysts encountered the challenge of efficiently extracting relevant information from a vast array of financial news articles. Each analyst was tasked with monitoring specific stocks and providing comprehensive insights into their performance and future prospects. Manual searching through numerous sources such as Money Control, the Economic Times, and premium platforms like Bloomberg Terminal was time-consuming and resource-intensive. To address this, the study proposed a Smart Tool to streamline Mutual Fund Insights. The tool used several techniques. Langchain facilitated NLP for effective comprehension and response to user queries, while integration with the OpenAI API enhanced the chatbot’s capabilities for generating human-like responses. Employing Streamlit, the study developed a user-friendly interface accessible to analysts with varying technical backgrounds. The implementation also integrated the FAISS Vector Index to optimize information retrieval. By automating information extraction and analysis, the Smart Tool aimed to empower research analysts, enabling more informed and timely investment decisions in mutual funds.