Prediction of Customer Satisfaction in E-banking Services Through Neural Network Approach

Today, banking sector is expanding rapidly with new e-banking services. As the growing concern for E-banking services that have made the efforts the need towards customer satisfaction in this area. Adoption of technology is imperative in the scenario of COVID-19 pandemic where physical banking has very less scope to sustain in competitive environment and also to deliver superior services to their customers. With the use of this, banks can meet customer expectations as well as can attract new customers through this channel. This study aims to contribute towards the impact of different variables of efficiency, accuracy, ease, and customer services on the customer satisfaction. This study considers to predict the customer satisfaction by regression and neural network model by establishing linear and nonlinear relationship. A quantitative study using 552 surveys completed by customers of public and private sector banks in Rajasthan (India). In Initial Analysis, the prediction is made by the regression model and in the second phase normalized importance of four predictors was using through neural networks particularly Artificial Neural Network (ANN). The findings are helpful for decision makers to implement policies to promote customer satisfaction through E-banking services.