The relevance of the study is due to the influence of platform solutions, which radically transform many business processes and significantly optimize customer transactions. The scientific article examines the main trends in the development of modern digital technologies in relation to the Russian financial sector. In the context of the development of the digital economy, the issue of digital transformation of business is becoming the most urgent. Drivers of digital transformation are an important, but poorly studied topic that requires special attention. The article formulates the goals of digital business transformation and, on this basis, compiles a list of drivers of digital business transformation as driving forces that contribute to, and often force the company to carry out digital transformation. Digital technologies are becoming more common and are actively entering people’s lives. This process engulfs the banking sector to a greater extent, since it turned out to be especially receptive to new market requirements and is inextricably linked with the need to adapt to business processes. This relationship can be optimized using artificial intelligence tools, of which business rule support systems and expert systems are prioritized in terms of application. A single company management loop allows you to extract data from system sources of formation on the server, to integrate and organize the available information in the required format. AI-powered analytics applications let you select the information you need from disparate sources. Shaping a data cube is a task that various analytic applications can already handle. In the promising future, tools for extracting information will continue to improve, so those with the necessary data will have an advantage in the market. The increasingly complex external environment for the functioning of the Russian banking system and the resulting transformational consequences are characterized by constant changes. Today, systems based on the use of artificial intelligence are actively developing, automating the work and interaction of various market agents in a specific sector of the public sphere and implying large-scale network effects.