The paper by Onyshchenko Yuliya explores the concept of business models in the context of digital banking and aims to identify digital bank business models. It highlights the increasing popularity of the business model concept in the digital economy and its application in various fields, including banking. The study focuses on the dynamic development of information and telecommunication technologies and their impact on banking, particularly in the context of digital banking models. The paper discusses the challenges in identifying digital bank business models due to the lack of distinct features that can differentiate them from traditional bank models at the banking system level. It proposes a method using statistical clustering algorithms to identify countries with a developed foundation for digital banking, based on five indicators: account ownership with mobile money service providers, automated teller machines (ATMs), commercial bank branches, and domestic credit to the private sector. The research is conducted among 61 countries in Europe and North America, and the results show three distinct clusters of countries with varying levels of digital banking development. The paper concludes that understanding the current business model is crucial for banks to successfully transition to new models, but this transition is risky due to the high probability of failure.The paper by Onyshchenko Yuliya explores the concept of business models in the context of digital banking and aims to identify digital bank business models. It highlights the increasing popularity of the business model concept in the digital economy and its application in various fields, including banking. The study focuses on the dynamic development of information and telecommunication technologies and their impact on banking, particularly in the context of digital banking models. The paper discusses the challenges in identifying digital bank business models due to the lack of distinct features that can differentiate them from traditional bank models at the banking system level. It proposes a method using statistical clustering algorithms to identify countries with a developed foundation for digital banking, based on five indicators: account ownership with mobile money service providers, automated teller machines (ATMs), commercial bank branches, and domestic credit to the private sector. The research is conducted among 61 countries in Europe and North America, and the results show three distinct clusters of countries with varying levels of digital banking development. The paper concludes that understanding the current business model is crucial for banks to successfully transition to new models, but this transition is risky due to the high probability of failure.