Purpose: To examine how income and interest rate affect mobile banking transactions in India’s financial system during the digital era from January 2016 to December 2022. Design/Methodology/Approach: The authors first test the stationarity of variables using ADF and PP tests, followed by a residual-based Granger and Johansen cointegration tests. The dynamic ordinary least squares (DOLS) method is used to estimate the long-run coefficients whereas the short-run coefficients are examined through the ECM. Additionally, FMOLS, CCR, IRF and diagnostic tests are applied to ensure the robustness of the results. Findings: The stationarity tests indicate that all selected variables are integrated at their first differences. Furthermore, the Engle-Granger and Johansen cointegration tests confirm a long-term relationship. The DOLS results show that income (Y) and short-term interest rate (SR) significantly influence money demand through mobile banking in the long run. In the short run, the coefficients of income and interest rate are not statistically significant; however, the negative and significant error correction term (ECT) indicates adjustment toward long-run equilibrium. Additionally, the FMOLS, CCR, and IRF models support the robustness of the long-run results, and diagnostic tests confirm the accuracy of the findings. Originality/value: This study makes a unique contribution by examining the effects of income and interest rate on mobile banking in the digital era, as the dependent variable instead of the traditional measure of money demand—an area with minimal empirical research. It provides a deeper perspective on how these factors shape mobile banking transactions in an evolving financial sector. By bridging traditional economic theory with modern financial practices, this study enhances our understanding of liquidity preference in the digital age and demonstrates the ongoing relevance of Keynesian concepts in today’s digital finance environment.