Today, many businesses such as banks, insurance companies, and other service providers realize the importance of Customer Relationship Management (CRM) and its potential to help them acquire new customers retain existing ones and maximize their lifetime value. Artificial Intelligence adapts characteristics of human problem-solving skills and then applies them as algorithms easily comprehended by computer systems. Such systems are routinely and widely used today by banks, hospitals, corporations, militaries and homes around the world. Data mining gives an opportunity, uses a variety of data analysis and modeling methods to specific trends and relationships in data detection. This helps to understand what a customer wants and anticipate what they will do. In this paper, the authors examine the application of k-means clustering and classification multilayer perception of artificial neural network on CRM in the case of EFT of POS service of the Bank Muscat. The results demonstrate the final dataset consists of 110000 records in which different clustering models at k values of 6, 5, and 4 with different seed values has been used as an input for the multilayer perception neural network model and evaluated against their performances. Thus, the cluster model at k value of 6 with default seed value has shown a better performance by using Weka-3-7-2 tool.