Enhancing Financial Decision-Making: Machine Learning and AI-Powered Predictions and Analysis
Vishal Patil, Kavya Bhand, Kaustubh Mukdam, Kavya Sharma, Manas Kawtikwar, Prajwal Kavhar, Hridayansh Kaware

TL;DR
This paper presents an AI-powered platform that leverages machine learning algorithms for accurate financial predictions, inflation analysis, and educational tools, aiming to improve decision-making in finance.
Contribution
It introduces an integrated AI-driven system combining multiple ML models for financial prediction, inflation analysis, and financial education, with demonstrated high accuracy on real-world datasets.
Findings
Inflation analysis achieves 0.8% MAE and 1.2% RMSE.
Stock prediction accuracy: 98% for Apple, 96% for Google.
Effective use of linear regression, ARIMA, and LSTM models.
Abstract
The proposed system aims to use various machine learning algorithms to enhance financial prediction and generate highly accurate analyses. It introduces an AI-driven platform which offers inflation-analysis, stock market prediction, and E-learning module powered by a chatbot. It has achieved high accuracy where the Inflation Analysis depicts 0.8% MAE, 1.2% RMSE and the Stock Prediction shows 98% and 96% accuracy for Apple and Google stock prices respectively. Key features include historical price trends, inflation rates, short-term future stock prediction, where the data has been extracted using real-world financial datasets. Additionally, the E-learning feature contributes to bridging financial gaps and promoting informed decisions. We have implemented algorithms like linear regression, ARIMA, LSTM where the accuracy has been evaluated using metrics such as MAE, RMSE and the like.
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