Using intelligent prediction machine and dynamic workflow for banking customer satisfaction in IoT environment

Abstract

Performance of prediction and workflow is very important for enterprise process automation. It has advantages such as increasing the efficiency of banking operations, improving resource utilization and increasing banking flexibility for business execution. The retail banks’ branch offices distributed information technology system. Traditional operating systems have limitations which make it difficult for branch banking to support other new user services. Connecting with other bank systems or computer devices poses a difficulty. The method proposed in this paper is based on artificial intelligence and dynamic workflow technology. The method is implemented by an object-oriented and edge computing method, which could be used to create a flexible banking system in an IoT environment, allowing new transaction business processes to be added and modified, requiring real time in cloud computing in IoT. This makes banking user services flexible and more competitive in terms of achieving customer satisfaction. Through this study, we devised a unified process control module to help users implement flexible banking transaction processes, decreasing banking system development time and error rates during banking system development and maintenance. Our process can also increase the usability of banking computer servers and transaction system stability, giving banking services more flexibility and increased competitiveness.