Big Data Mining Model to Predict Electronic Payment System Using Machine Learning

  IJRES-book-cover  International Journal of Recent Engineering Science (IJRES)          
© 2022 by IJRES Journal
Volume-9 Issue-2
Year of Publication : 2022
Authors : Wesley Odeh Odumu, Ezekiel Endurance Chukwuemeke Igbonoba
DOI : 10.14445/23497157/IJRES-V9I2P102


MLA Style: Wesley Odeh Odumu, and Ezekiel Endurance Chukwuemeke Igbonoba. "Big Data Mining Model to Predict Electronic Payment System Using Machine Learning" International Journal of Recent Engineering Science  vol. 9, no. 2, Mar-Apr. 2022, pp. 7-17. Crossref,

APA Style: Wesley Odeh Odumu, & Ezekiel Endurance Chukwuemeke Igbonoba. (2022). Big Data Mining Model to Predict Electronic Payment System Using Machine Learning. International Journal of Recent Engineering Science, 9(2), 7-17.

This research presents a data mining model developed to predict the relationship between Nigeria's electronic payment (e-payment) systems. This proposes a data mining approach to establish the relationship between electronic payment and its impact on the economy. The Waikato Environment for Knowledge Analysis (WEKA) machine learning tool was used to develop the model using a simple regression technique. This predicts the usage in terms of volume and value of the following adopted electronic payment channels. The aim is to determine the performance measurement of the electronic payment system in the Nigerian banking sector. The data mining model developed can predict e-payment transactions over a number of years. The dataset used to assess and validate the authenticity of the model developed was obtained from the Nigeria Inter-Bank Settlement System (NIBSS) and the Central Bank of Nigeria (CBN). The result obtained indicates a positive relationship and contribution of e-payment networks to cost-effective progress with the modern move to a cashless economy in Nigeria. This equally impacted positively on the banking performance. The study revealed that the developed model would prove to be a preemptive and predictive tool for Nigerian banks to better policy formulation, financial advisory services, and performance measurement.

Big Data, Data Mining, E-payment, Electronic Payment Channel, Machine learning.

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