## 3 Materials and Methods  
The study investigates how banking performance is influenced by automation through mechatronic systems and AI in the EU countries. The selected time is six years (2017-2022), which was chosen to capture significant trends in the evolution of automation in the banking sector, as well as its impact on banking performance, considering the major economic and technological transformations that took place during this time. Additionally, the 6-year period ensures a relevant analysis of economic and financial data, allowing for the identification of meaningful relationships between the studied variables. To reach the goal of our study, we selected a group of variables, as presented in Table 1. Data on financial indicators were collected from the International Monetary Fund, \"Financial Soundness Indicators\" [106] and from the Eurostat database, European Commission, and European Central Bank [107-109]. The choice of these variables is justified by the multidimensional exploration of the effect that banking performance has on robotic process automation and digitalization in EU countries. Automation has become a fundamental element in the transformation of the banking sector, significantly impacting operational efficiency and customer interaction. In this context, ATMs are relevant as mechatronic systems, while chatbots and robo-advisors represent advanced software technologies, both contributing to the digitalization process. ATMs (automated teller machines) are considered mechatronic systems due to their integration of mechanical engineering, electronics, and software, characteristics that define the concept of mechatronics. According to [PERSON] [25], mechatronics involves the combination of mechanics, electronics, and computer science to develop efficient automated solutions. ATMs perform tasks such as cash dispensing, deposit processing, and account balance verification through advanced electromechanical components. Furthermore, these devices are integrated with complex software systems that enable connectivity to central banking infrastructures, ensuring real-time transaction processing [110]. Simultaneously, software-based automation, illustrated by the use of banking chatbots and robo-advisors, has fundamentally changed how banks interact with their clients. These technologies leverage artificial intelligence (AI) and natural language processing (NLP) algorithms to understand and respond to user requests. For instance, banking chatbots can autonomously handle simple interactions, such as account balance inquiries or payment initiation, while robo-advisors provide personalized financial recommendations by analyzing clients' financial data [111]. These software solutions reduce dependence on human personnel while enhancing the accessibility of financial services [112]. Integrating ATMs as mechatronic robots and chatbots or robo-advisors as software solutions demonstrates the convergence of mechanical and digital technologies in the banking sector. While ATMs optimize physical operations through advanced hardware mechanisms, chatbots and robo-advisors extend automation into the digital realm, facilitating a more personalized user experience [113]. As emphasized by Hashstudioz Technologies [114], the application of artificial intelligence in fintech is reshaping the global financial ecosystem by enhancing its performance and efficiency. This combined approach allows banks to better meet the demands of the modern market. Therefore, ATMs, chatbots, and robo-advisors are significant components of banking automation, contributing to increased efficiency and enabling banks to adapt to the demands of an increasingly digitalized market. By leveraging these solutions, the banking sector not only improves its operational performance but also positions itself as a leader in digital transformation within the global economy.