Smart SIP for Teens: A Gamified and Explainable Machine Learning Framework for Early Investment Habit Formation

Abstract: Early financial literacy plays a crucial role in shaping long-term economic well-being. However, most digital investment platforms are designed for adult users and they lacks in educational, motivational, and transparency features suitable for teenagers. This paper presents Smart SIP for Teens, a comprehensive, gamified, and explainable financial learning platform aimed at fostering disciplined saving and early investment habits among teenagers. The proposed system combines machine learning-based personalization using the XGBoost algorithm to recommend suitable Systematic Investment Plan (SIP) strategies based on user-specific attributes such as age, savings behavior, financial goals, and risk tolerance. To address trust and transparency concerns, Explainable Artificial Intelligence (XAI) techniques using SHAP values are employed to interpret model decisions. Gamification elements such as reward points, streaks, badges, and milestones are incorporated to improve engagement and investment habit formation. Experimental evaluation demonstrates improved user engagement, consistency in saving behavior, and enhanced understanding of investment concepts. The results validate the effectiveness of combining personalization, explainability, and gamification in delivering impactful financial education solutions for teenage users.

Keywords: Systematic Investment Plan, Financial Literacy, Teenagers, Gamification, Machine Learning, XGBoost, Explainable AI, SHAP Values