The paper discusses the problem of identifying digital bank business models, emphasizing the need for a clear understanding of this concept in the context of digital banking. It highlights the increasing popularity of the business model concept in the digital economy and its application in various fields, including banking. The paper analyzes existing research on bank business model identification and points out the challenges in distinguishing digital bank business models from traditional ones. It argues that the identification of digital bank business models must be done at the bank level rather than the banking system level. The paper proposes a methodology based on statistical clustering algorithms to identify groups of countries with similar trends in digital banking development. Five indicators are used to assess the readiness of countries for digital banking transformation. These indicators include account ownership with mobile money services, automated teller machines, commercial bank branches, and domestic credit to the private sector. The analysis shows that countries can be clustered into three groups based on their level of digital banking development. The first group consists of countries with high banking system development and a readiness to adopt digital technologies. The second group includes countries with average banking system development. The third group consists of countries with low banking system development, which may be either developed stock market countries or developing countries with young banking systems. The paper concludes that the identification of digital bank business models is a complex process that requires a clear understanding of the current business model and the availability of relevant indicators. The research aims to provide a framework for identifying digital bank business models and developing regulatory measures for different types of banks.The paper discusses the problem of identifying digital bank business models, emphasizing the need for a clear understanding of this concept in the context of digital banking. It highlights the increasing popularity of the business model concept in the digital economy and its application in various fields, including banking. The paper analyzes existing research on bank business model identification and points out the challenges in distinguishing digital bank business models from traditional ones. It argues that the identification of digital bank business models must be done at the bank level rather than the banking system level. The paper proposes a methodology based on statistical clustering algorithms to identify groups of countries with similar trends in digital banking development. Five indicators are used to assess the readiness of countries for digital banking transformation. These indicators include account ownership with mobile money services, automated teller machines, commercial bank branches, and domestic credit to the private sector. The analysis shows that countries can be clustered into three groups based on their level of digital banking development. The first group consists of countries with high banking system development and a readiness to adopt digital technologies. The second group includes countries with average banking system development. The third group consists of countries with low banking system development, which may be either developed stock market countries or developing countries with young banking systems. The paper concludes that the identification of digital bank business models is a complex process that requires a clear understanding of the current business model and the availability of relevant indicators. The research aims to provide a framework for identifying digital bank business models and developing regulatory measures for different types of banks.