1
Research Scholar, Department of Computer Science, VISTAS, Chennai.
2
Associate Professor, Department of Computer Science, VISTAS, Chennai.
Abstract
Increasing the revenue and profitability is the top most priority of a business. One of the major factors affecting the profit of a business is Customer Churn. Early prediction of customer churn and customer retention plays a vital issue in Customer relationship management. Retaining a customer is cost effective than attracting a new customer. This paper demonstrates a frame work for predicting customer churn in banking industry using the transactional data. It also compares with various other models. It uses the Behavioral aspects of the customer through the transactions made by them. It has been implemented through attention based Hybrid GRU BiLSTM model.
Britto, M. M. J., & Gobinath, D. R. (2021). Improved Churn Prediction Model In Banking Industry And Comparison Of Deep Learning Algorithms. Int. J. of Aquatic Science, 12(2), 2521-2529.
MLA
Mr. M. John Britto; Dr. R. Gobinath. "Improved Churn Prediction Model In Banking Industry And Comparison Of Deep Learning Algorithms". Int. J. of Aquatic Science, 12, 2, 2021, 2521-2529.
HARVARD
Britto, M. M. J., Gobinath, D. R. (2021). 'Improved Churn Prediction Model In Banking Industry And Comparison Of Deep Learning Algorithms', Int. J. of Aquatic Science, 12(2), pp. 2521-2529.
VANCOUVER
Britto, M. M. J., Gobinath, D. R. Improved Churn Prediction Model In Banking Industry And Comparison Of Deep Learning Algorithms. Int. J. of Aquatic Science, 2021; 12(2): 2521-2529.
)