Enhancing financial decision-making: machine learning and AI-powered predictions and analysis
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.
Authors
- Manisha D Karad
- Bajirao Subhash Shirole
- Harish P. Bhabad (ORCID: https://orcid.org/0009-0008-2849-7027)
- Dinesh Patil (ORCID: https://orcid.org/0000-0001-9588-8513)
- Mangesh D. Sanap
- Shridarshan Nemane
Institutions
- Machine Intelligence Research Institute (US)
- Savitribai Phule Pune University (IN)
Publication Details
- Journal
- IET conference proceedings.
- Published
- 2026-02-01
- DOI
- https://doi.org/10.1049/icp.2025.4747
- Primary Topic
- Stock Market Forecasting Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00