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The digital payment sector is becoming an increasingly important aspect of people’s life as a result of recent advancements in mobile and internet technology, delivering numerous fascinating and helpful services like M-banking. The m-banking system enables consumers to make purchases from anywhere using any electronic device, including mobile phones or tablets. M-banking is expected to have a better future as a result of current movements in international digital markets. The Reserve Bank of India said that the number of mobile banking transactions in India increased by 123% between 2018 and 2019, reaching 1.31 billion in total. More than 60% of Indian internet users use financial services via their mobile devices, according to Boston Consulting Group and Google, and the country’s mobile banking market is predicted to reach $1 trillion by 2023. Yet, these channels are more susceptible to various security risks when it comes to storing or transmitting information. Because there are so many various sorts of hazards, users are reluctant to use these services online. One of the aims of current research is to measure how perceived risk affects mobile banking in terms of intension and usage. The study also uses ML techniques to investigate the impact of other dimensions and measures, such as quality, ethics, simplicity, and demographic factors on m-banking patronage. The data is collected for the study using a structured questionnaire. The information gathered for the study was used to train and test ML models. Data collected were analyzed using various techniques, they are descriptive statistics, correlation and regression, principal component analysis, ML techniques, and other statistical techniques are used, to identify the key dimensions that impact customers’ desire to adapt and utilize m-banking. Research findings may assist in suggesting ways to mitigate m-banking risks prevalent among users, and highlight key factors that drive the user’s intention of usage. Institute can use the study outcomes to improve user access for sustainable growth.

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Exploring the Impact of Security, Confidentiality, and Related Factors on M-Banking Adoption in India: A Machine Learning Perspective

  • 章节

  • 发表日期：

    2025年

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  • M. Jahnavi,
  • Purushottam Bung,
  • N. Nagasubba Reddy,
  • T. K. Murugesan

摘要

The digital payment sector is becoming an increasingly important aspect of people’s life as a result of recent advancements in mobile and internet technology, delivering numerous fascinating and helpful services like M-banking. The m-banking system enables consumers to make purchases from anywhere using any electronic device, including mobile phones or tablets. M-banking is expected to have a better future as a result of current movements in international digital markets. The Reserve Bank of India said that the number of mobile banking transactions in India increased by 123% between 2018 and 2019, reaching 1.31 billion in total. More than 60% of Indian internet users use financial services via their mobile devices, according to Boston Consulting Group and Google, and the country’s mobile banking market is predicted to reach $1 trillion by 2023. Yet, these channels are more susceptible to various security risks when it comes to storing or transmitting information. Because there are so many various sorts of hazards, users are reluctant to use these services online. One of the aims of current research is to measure how perceived risk affects mobile banking in terms of intension and usage. The study also uses ML techniques to investigate the impact of other dimensions and measures, such as quality, ethics, simplicity, and demographic factors on m-banking patronage. The data is collected for the study using a structured questionnaire. The information gathered for the study was used to train and test ML models. Data collected were analyzed using various techniques, they are descriptive statistics, correlation and regression, principal component analysis, ML techniques, and other statistical techniques are used, to identify the key dimensions that impact customers’ desire to adapt and utilize m-banking. Research findings may assist in suggesting ways to mitigate m-banking risks prevalent among users, and highlight key factors that drive the user’s intention of usage. Institute can use the study outcomes to improve user access for sustainable growth.