Abstract: This paper explores the use of budget planning features as an E-banking service for monthly income earners who make use of electronic banking (E-banking) platform for their monthly expenditure transactions. In order to investigate the underlying need for incorporating budget planning as an E-banking service, a Google online survey on 155 University staff was carried out. Results show that 29% of them live above their monthly income and in dire need of a budget planner. Based on this, the monthly income and monthly expenditure were modeled using Binary Logistic regression. A computational algorithm for classifying previous transaction data of a salary earner was developed. Implementation architecture for deployment of the E-banking budget planner was also presented. A simulation carried out on 10 years classified data from bank transaction details of a salaried earner was used to train and test the model in python (spyder platform). Results show 82% accuracy in prediction of salary earner's budget for......
Key Word: Algorithm, E-banking, budget, income, expenditure, regression, simulation.
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