Significant changes taking place in both the global and Russian banking systems require an immediate response from market participants to emerging challenges. Reducing decision-making time forces any commercial Bank to digitalize and automate all key front-and back-office processes. Currently, most management decisions in banking are made either by experts or on the basis of one-time calculations of the economic efficiency of individual projects, which does not allow rapid and high-quality scenario analysis of the development of the situation in various market conditions. The purpose of the research is to develop a new dynamic controlled economic and mathematical model, a new method for optimal adaptive management of the process in question and to implement its instrumental computer software system. The hypothesis of this study is that the use of a new dynamic controlled economic and mathematical model, as well as the new above-mentioned methodology, would increase the efficiency of this process in terms of the selected quality criterion in comparison with the results of program control. The novelty of this article is the development of a new deterministic dynamic economic and mathematical model for making optimal adaptive management decisions by the Bank, the method of its solution developed by the authors, and the creation of an appropriate modeling computer software package. The paper presents the main stages of creating the proposed discrete controlled dynamic economic and mathematical model in the presence of a given quality criterion-Cost Income Ratio of the Bank’s Retail unit. Using a real-life example, an algorithm for solving the problem of adaptive control optimization is presented; computer modeling of their formation is implemented for all the results obtained, and the analysis of the obtained variants of optimal solutions is carried out. Based on the proposed dynamic model, it is possible to solve other problems of optimizing software and adaptive management of processes that determine banking activities and develop automated information systems for implementing support for managerial decision-making in this area.