Application of artificial intelligence technologies in lean management models of commercial banks

To reduce operational losses and maximise the value of their products, banks are implementing various management models, in particular those based on the lean approach. The use of digital solutions in the activities of financial organisations allows businesses to maintain and strengthen their competitiveness in the financial services market. The purpose of the article is to consider the specifics of the application of lean management methods in commercial banks as well as the possibilities of their optimisation with the help of artificial intelligence (hereinafter referred to as AI) technologies. On the basis of statistical data of the Bank of Russia, reporting documents of “Sber”, and data of the marketplace “Banki.ru”, the dynamics of changes in the methods of customer service of Russian banks over the last 5 years has been studied. Despite the increase in the number of remote services, the growth of operational costs is revealed. At the same time, customer satisfaction has barely grown, with the main reasons for dissatisfaction being quality and speed of service. Following the analysis of scientific and practical literature, the main categories of losses in banking business have been identified, as well as the directions of optimisation and increase of the efficiency of financial institutions through the application of the lean management approach. Specific consideration is given to the integration of the AI technologies and methods, including machine learning, natural language processing, and process mining, into the established lean practices. This study demonstrates the potential for these techniques to enhance the efficiency of the lean management procedures and directly contribute to business processes of a commercial bank.