Impact of Digital Payments on the Operational Efficiency of Banks
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Digital payments, bank, operational efficiency, UPI Unified Payments Interface, threshold effect, india, FinTech Financial Technology, commercial banks, CIR Cost-to-Income Ratio, CAR Capital Adequacy Ratio, DPII Digital Payment Intensity Index, System GMM Generalized Method of Moments, technological infrastructure, NPAR Non-Performing Assets Ratio, DCE Digital Cost Elasticity, EFT National Electronic Funds Transfer, RTGS Real-Time Gross Settlement, IMPS Immediate Payment Service
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Abstract
The purpose of this paper is to examine the relationship between digital payment channels and the operational efficiency of commercial banks in India using a panel data set of 68 commercial banks in India for the period 2015-2024. For measuring the intensity of utilisation of digital payment channels, a Digital Payment Intensity Index (DPII) is constructed, and a novel threshold panel model is developed based on system GMM estimation in order to deal with endogenous problems. The research is a step forward from existing studies, which are considered a linear approach and a channel-agnostic approach. It is found that a non-linear relationship between DPII and efficiency exists; in particular, the improvement in efficiency in terms of Cost-to-Income Ratio is modest until the threshold level of DPII at 0.41 is reached. However, after passing the threshold level, each marginal increase in DPII leads to a decrease in the Cost-to-Income Ratio three and a half times more quickly. In terms of a channel-based approach, it is shown that UPI contributes most efficiently by reducing costs 3.9 times faster than credit card transactions, even with 0 MDR. Our contribution includes integrating Technology Acceptance Model, Diffusion of Innovations, and Resource Based view into a valid framework and proposing a new concept called Digital Cost Elasticity for FinTech literature. For managers, our findings suggest that crossing the digital payment threshold and investing in digital skills are more important than technology spending. For regulators, our results imply that charging fees on UPI could hinder operational efficiencies that banks can achieve via scale. Our study adds granular and causal evidence to FinTech literature and enables banks to benchmark their digital strategies in the post-UPI environment.
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[...] The degree to which banks benefit from digital payments depends on multiple organizational factors - and contrary to popular belief, banks with larger assets and higher tech infrastructures are less likely to enjoy efficiency gains. Academically speaking, our paper contributes to the FinTech discussion by providing a new empirical framework and metrics, and extending TAM-DOI-RBV integration. Practically, banks should prioritize digitizing customer experience and focusing on efficiency over profitability. References Albarrán-Torres, C Mobile gamble-play apps, in: Digital Gambling. Routledge, pp. 193-221. doi:10.4324/9780203730690-7. Chavali, K., Kumar, A Adoption of mobile banking and perceived risk in GCC. Banks and Bank Systems 13, 72-79. doi:10.21511/bbs. 13(1).2018.07. Coombs, W.T Diffusion of innovations theory, in: Heath, R.L. [...]
[...] Since digital adoption rate may be endogenous (better banks may digitize faster), we use the System GMM estimator (Windmeijer, 1998). A novel proxy for digital adoption rate is used as an instrumental variable - the number of district level 4G tower per km2 in 2014. The 4G roll-out process was nationally managed, thus is exogenous and valid as an instrument. Interaction effects (moderation analysis): CIR?? = ? where: One-period lag of Cost-to-Income Ratio, capturing persistence. SIZE?? Log of total assets, used as a proxy for bank size. [...]
[...] Giachetti, C Aligning with competitors when adopting new product technologies, in: Competitive Dynamics in the Mobile Phone Industry. Palgrave Macmillan, pp. 138-164. doi :10.1057/9781137374127.0012. Hordofa, D.F Impact of Mobile Banking Adoption on the Technical Efficiency of Commercial Banks in Ethiopia: An Analysis from 2010 to 2022. Preprint. Research Square. doi:10.21203/rs.3.rs-3146976/v1. Hussain, S., Gupta, S., Bhardwaj, S Corrigendum: A helping hand in banking: how off-site customer-to-customer interactions impact the mobile banking usage behaviour and financial well-being. International Journal of Bank Marketing 44, 610-611. doi:10.1108/ ijbm-01-2026-0055. [...]
[...] For regulators, our results imply that charging fees on UPI could hinder operational efficiencies that banks can achieve via scale. Our study adds granular and causal evidence to FinTech literature and enables banks to benchmark their digital strategies in the post-UPI environment. Introduction The banking sector globally is experiencing a revolutionary change due to the advancement of FinTech (Venaik, Garg and Agarwal, 2024). Digital payment solutions and mobile banking apps play a vital role in this innovation trend (Albarrán-Torres, 2018). [...]
[...] Control Variables For our empirical model, we use Capital Adequacy Ratio Non-Performing Assets Ratio (NPA) and Loanto-Deposits Ratio (Yuhasril, 2019) for banking-indicators and GDP growth rate and dummy variable for COVID-19 pandemic period (2020-2021) for macroeconomic variables. These will help us determine shock-related increases in digital financial services . 3.4. Model Specification and Estimation Approach CIR?? = + DPII?? DPII?? > + + where: CIR?? Cost-to-Income Ratio for bank ? in financial year DPII?? Digital Payment Intensity Index for bank ? in year ? Threshold parameter for digital intensity, estimated from the data. Indicator variable equal to 1 if the argument is true, and 0 otherwise. Collection of control variables including bank and macroeconomic factors. [...]
