The aim of this research is to improve the public sector financial data processing system by presenting an interpretive structural model (ISM) of virtual treasury modeling with a neobank approach. Given the lack of previous research and the novelty of the subject, this research intends to propose a new model that can be applied to the virtual treasury process with a neobank approach in the public sector and to present a comprehensive model in this regard. This research has been carried out in two main stages. First, the factors studied were obtained by reviewing the research literature, and then the relationships between them were examined and finalized by experts including 22 senior financial managers in the public sector, including the Court of Audit, the Central Bank, and the Armed Forces. This approach helps the research to have both theoretical support and practical compatibility with the specific conditions of treasury in the public sector. Based on the research results, implementing the neobank solution (especially regarding fast and efficient payments and liquidity management) in the context of artificial intelligence and blockchain technologies will result in the realization of the main research topic, namely improving the financial data processing system in the public sector. Based on the strategies of virtual treasury with the neobank approach, important consequences, especially optimal liquidity management and continuous monitoring with electronic surveillance and supervision, are achieved in the implementation of the main research topic.