Machine Learning-Based Mobile Payment System for Empowering Low-Income Earners in India
Abstract
In the contemporary era, mobile phones have become indispensable, serving as communication devices and offering myriad applications. Among these applications, mobile payment systems hold great potential in driving the transition to a cashless economy. However, India's current mobile payment landscape is limited by its dependency on bank accounts. This poses a significant challenge for low-income earners who lack access to banking services or perceive minimal benefits in owning an account due to their limited financial resources. As a result, they are unable to leverage existing mobile payment systems. Despite bank branches in approximately 40,000 out of 600,000 Indian villages, a staggering 80% of households possess mobile phones. The heavy reliance on cash-based transactions leaves India's economy susceptible to disruptions. To address this, the proposed research project aims to develop a user-friendly and secure mobile payment system that operates independently of bank accounts, ensuring inclusivity for all individuals, irrespective of their banking status.
Moreover, the system will be compatible with any mobile phone and will not require an internet connection. By implementing such an innovative system, India can make significant strides toward achieving a truly cashless economy. Additionally, integrating machine learning techniques in the system can enhance security, fraud detection, and user personalization, further optimizing the user experience and driving the adoption of mobile payments.
Downloads
Published
Issue
Section
License
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
