Efforts for better services are achieved by small steps such as analyzing data of the customer. What issignificant for the customer should as well significant for the banking institution. Transparency and a better understandding of the pattern behavior of customers can be used for the good of both partners such as good relationships in the future eventually be beneficial for the customer as well as a banking institution. The responsibility of both sides is crucialto understand the accountability of customers and banking institutions. The method of identification of user messagesof the banking application proposed in the article involves the use of user data for information processing, taking intoaccount the peculiarities of the use of mobile devices and the user's dialogue with bank messages. Also, the proposedmethod allows you to rank messages to identify the most important messages and get the desired result by providing effective recommendations in favor of each of the participants in customer interaction with the bank. The introduction ofmodern educational programs \'Information Control Systems and Technologies\', \'Artificial Intelligence Systems\' and\'Systems Analysis\' in the field of information technology, allows users and managers to interact with the bank's customers sufficient information to make informed recommendations for effective management decisions. The article considers the conceptual model of interaction of users and managers on interaction with users of the bank, use of technologies and algorithms of artificial intelligence, machine learning processes to formalize the process of dialogue, systematization and ranking of messages and notifications between customers and managers. The Conceptual model of interaction of the user of banking services with messages is presented. The article also describes the features of the dialoguebetween the user of banking services and the manager for the implementation of algorithms for interaction with customers. The example of the city block of bank users considers and takes into account the difference in the amount of information received by the bank, which must be sent during different periods of the week and take into account theamount of information to be sent, which will be significantly less and, consequently, the number of necessary services.will also be smaller. In this example, taking into account the amount of information that can be consumed during differrent periods of the week, the number of services that can be provided to the user will also be much smaller. The reflection of such interactions in the model is an important aspect, as noted in the article.