Currently, 1.4 billion people worldwide remain unbanked, with one notable challenge being the struggle to adhere to compliance regulations without possessing official personal documents. Regulatory requirements, often presented in unstructured formats using natural language, are scattered across documents originating from diverse jurisdictions. Innovative recognition approaches, such as recognising individuals through digital activity trails, offer potential solutions to this challenge. This paper introduces a conceptual model aimed at addressing financial inclusion challenges, with a particular focus on a formal rule-language designed to model financial inclusion services and to structure existing requirements related to user recognition. Our study also applies the proposed rule-language to a real-world use case, employing formal quantitative verification to validate its effectiveness in representing and comparing critical decisions within a financial inclusion context. The proposed framework demonstrates versatility by being applicable to both centralised and decentralised finance systems.