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Rachit2527/Financial-Assistant

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AI-Powered Financial Insights Platform

Description:

Developed an AI-powered platform with multiple financial models aimed at enhancing decision-making, automating reports, and providing personalized advice. Integrated state-of-the-art generative AI models using HuggingFace's Mistral-7B-Instruct-v0.3 and the LangChain framework for seamless conversational capabilities.

OVERVIEW

The page has these features: Features

Financial Question Answering

Financial Question Answering

Financial Sentiment Analysis with Text Generation

Financial Sentiment Analysis with Text Generation

Generative AI for Personalized Financial Advice

Generative AI for Personalized Financial Advice

AI Driven Financial Report Generation

AI Driven Financial Report Generation

Credit Risk Assessment

Credit Risk Assessment

Key Features:

Automatic Financial Question Answering (QA) System: Implemented a model capable of answering financial-related queries using financial context understanding. Users can ask questions on a wide range of financial topics such as investments, banking, and economic trends, receiving accurate, data-driven responses.

Financial Sentiment Analysis with Text Generation: Developed a sentiment analysis model to analyze financial news and reports, determining the sentiment behind statements (positive, neutral, or negative) while also generating predictive financial text based on the sentiment outcome.

Generative AI for Personalized Financial Advice: Built a personalized financial advisory system that generates custom investment recommendations based on user inputs like risk tolerance, financial goals, and current assets. The AI provides tailored strategies for long-term wealth creation and risk mitigation.

AI-Driven Financial Report Generation: Created a generative model that automatically compiles financial reports. By inputting key data metrics, the system generates detailed reports with insights on portfolio performance, asset allocation, market trends, and other relevant financial indicators.

Credit Risk Assessment: Designed a credit risk evaluation model to predict the creditworthiness of a customer based on factors such as financial history, income, and liabilities. The system provides a risk score and suggestions for risk mitigation.

Technologies Used:

--LangChain for prompt engineering and building conversational AI pipelines.

--HuggingFace API leveraging Mistral-7B-Instruct-v0.3 for generative text capabilities.

--Streamlit for creating an interactive web interface to showcase model functionalities.

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