Neural Network and Classification Approach in Identifying Customer Behaviour in the Banking Sector: A Case Study of an International Bank

The customer relationship focus for banks is in development of main competencies and strategies of building strong profitable customer relationship through considering and managing the customer impression, influence on the culture of the bank, satisfactory treatment; and assessment of valued relationship building. Artificial neural network (ANN) is used after data segmentation and classification, where the designed model register records into two class sets, that is, the training and testing sets. ANN predicts new customer behaviour observations from previous customer observed behaviour after executing the process of learning from existing data. This paper proposes an ANN model, which is developed using a six-step procedure. The backpropagation algorithm is used to train the ANN by adjusting its weights to minimize the difference between the current ANN output and the desired output. An evaluation process is conducted to determine if the ANN has learned how to perform. The training process is halted periodically and its performance is tested until an acceptable result is obtained. The principles underlying detection software are grounded in classical statistical decision theory.