Customer Investment Prediction

By forecasting. if a client is likely to sign up for a term deposit, the Customer Investment Prediction system effectively illustrates. how machine learning could be enhanced decision-making in the banking industry. The system uses. sophisticated models like Gradient Boosting XGBoost LightGBM CatBoost and SVM to provide. reliable and comparable insights about client investing behavior. Through efficient preprocessing model training. and accuracy evaluation the solution ensures high-quality forecasts that enable tailored financial  strategies.                                      and targeted marketing. Additionally, the user and admin modules enable smooth communication enabling users to. forecast and ask for help while administrators can effectively handle FAQs and user.                                  inquiries. All things considered the project gives financial institutions a reliable scalable. and easy-to-use platform that improves investment conversion rates maximizes resources and raises customer. engagement. This project is 30% accuracy.

1.            Machine Learning Based.  Customer Churn Prediction in Banking by Manas Rahman and V Kumar, published. in 2020 4th International Conference on Electronics, Communication and Aerospace.    Technology      (ICECA),      DOI: 10.1109/ICECA49313.2020.9297529,  ISSN: 2320-8845. 2.    Banking. in Terms of Deposit Prediction Based on Machine Learning and Big Data Analytics, by authors not. specified, published in 2023 IEEE International Conference on Artificial Intelligence. and Computer Applications (AICA), DOI: 10.1109/AICA56173.2023.10374595, ISSN: 978-1-6654-9751-5 3.    Applying Machine. Learning to the Development of Prediction Models for Bank Deposit Subscription. by Sipu Hou, Zongzhen Cai, Jiming Wu, and Peng Xie, published in 2022, available at https://www.researchgate.net/publication/357488 750. 4.        Using Big. Data and Predictive Analytics for Informed Decision-Making in Investment Banking. by Priyanshu Jasaiwal, published in International Journal of Advanced Research in Computer and.  Communication Engineering (IJARCCE), Volume 13, Issue 12, December2024,  DOI:  10.17148/IJARCCE.2024.131258, ISSN Online: 2278-1021, ISSN Print: 2319-5940. 5.    Bank Loan Prediction. Using Machine Learning Techniques by F. M. Ahosanul Haque and Md. Mahedi Hassan, published in American. Journal of Industrial. and Business Management, Volume 14, Article 1412085, December. 25, 2024, DOI: 10.4236/ajibm.2024.1412085,  ISSN  Online: 2164-5175, ISSN Print: 2164-5167.