We propose a novel credit screening framework that substitute’s conventional collateral and credit history prerequisites with trust proxies sourced from informal entrepreneurial network structures. The system targets micro, small, and medium enterprises (MSMEs) in emerging markets, where conventional financing constraints arise from severe information asymmetry and adverse selection. Our methodology first constructs a directed graph from observable informal ties, such as mobile money transactions or trade credit relationships, and then computes two key network metrics: betweenness centrality, which captures an entrepreneur’s role as a trusted intermediary, and triadic closure coefficient, which reflects local social enforcement against strategic default. To address network endogeneity, we compute these metrics via an Exponential Random Graph Model (ERGM), which generates a posterior distribution over the network positions. These distributions function as instruments in two-stage least squares regression, isolating the causal effect of network position on repayment probability and correcting for simultaneity bias between credit access and network centrality. The resultant forecast default probabilities are then embedded into a dynamic screening mechanism founded on a principal-agent model, in which the lender presents a menu of contracts designed to differentiate high-risk from low-risk borrowers via risk-adjusted pricing. This mechanism transforms the conventional binary credit decision into a continuous, incentive-compatible interest rate schedule. The entire pipeline is implemented as a cloud-based API, and mobile money transaction logs serve as the primary data source. Our contribution consists in replacing static collateral with dynamic, network-derived trust signals, thereby broadening credit access for firms that are collateral-poor yet occupy central positions in networks. This approach is important because it can reduce credit rationing in informal economies without requiring a structured financial system, thereby supporting MSME growth in settings with limited resources.