Forecasting UPI Transaction Value in India

The Unified Payment Interface (UPI) has a revolutionized the landscape of digital payment in India by facility seamless real time transaction across multiple bank and Financial Institutions. This study investigates the impact of customer-initiated transactions and total transactions value in India's UPI ecosystem using machine learning regression model. The study utilizers data set of 1811 (n) obtained from the NPCI website. For the analysis of the data received researcher adopted comparison of Linear Regression, Random Forest (RF), XGBoost algorithm to predict total transaction value-based customer-initiated transactions. The finding reveals that RF model achieves the significant as compare to the other models in terms of R2, RMSE, and MAE. The study contributes to the understanding of digital payment ecosystem that provide empirical evidence for the effective UPI retail sales growth of ensemble learning models in financial transaction predictions.