A fuzzy–blockchain framework for crowdsourced fund allocation (FB-CFA) to startup MSMEs

Purpose Access to finance remains a major constraint for startup micro, small and medium enterprises (MSMEs), particularly within decentralized crowdfunding environments where uncertainty, fraud risk and inefficient fund allocation persist. Emerging technologies such as fuzzy logic and blockchain offer potential solutions to improve transparency, risk evaluation and automated funding decisions. This paper aims to develop and validate a fuzzy – blockchain framework for crowdsourced fund allocation to startup MSMEs by integrating fuzzy inference with blockchain-enabled smart contracts to support transparent, secure, and risk-aware funding decisions. Design/methodology/approach This study proposes a hybrid fuzzy–blockchain framework for crowdsourced fund allocation to startup MSMEs. Financial inclusion indicators, including mobile money usage, digital payments, account ownership, credit access, crowdfunding activity, startup age and employee size, were collected from the Financial Inclusion Data Story GitHub repository, derived from the World Bank Global Findex Database. This method uses several components, including data normalization, correlation analysis, triangular fuzzy membership functions, a 27-rule Mamdani inference system and the verification of blockchain transactions and smart contracts, to manage fund allocation. Findings The findings suggest that the proposed strategy leads to greater transparency and risk-aware allocation of funds across the Seed, Series A and Series B investment stages. Blockchain authentication manages transaction reliability while fuzzy inference processes can reduce uncertainty in funding decisions and fraud evaluations. Research limitations/implications The results indicate that integrating fuzzy decision models with blockchain verification significantly improves transparency, reduces fraud vulnerability and optimizes funding allocation to MSMEs across different investment stages. Practical implications This study relies on simulated crowdfunding transactions and secondary financial inclusion data sets, which may not fully capture real-time investor behavior or regulatory variations across crowdfunding platforms. Social implications The framework provides fintech platforms and policymakers a flexible model to help make decisions about safe crowdfunding, allowing for automatic risk evaluation and clear tracking of investments in startups. Originality/value The results illustrate the effectiveness of integrating fuzzy decision models with blockchain-based technology to improve trust, automation and governance in decentralized crowdfunding systems to promote the growth of MSMEs.