Digital Financial Twins in Islamic Microfinance: Evidence from Conflict-Affected Rural Economies (2020–2025)

Conflict-affected rural microfinance institutions (MFIs) face significant challenges, such as data scarcity and repayment volatility, which limit their sustainability and outreach. Despite the growing interest in digital technologies, no prior empirical study has evaluated the impact of Digital Financial Twin (DFT) analytics in Shariah-compliant MFIs operating in conflict zones. This study integrates cyber-physical simulation with Islamic microfinance practices to provide the first large-scale evidence on the impact of DFT analytics on financial and poverty outcomes. Using a quasi-experimental design, we combine geospatial conflict data (from ACLED), loan-level records from five Islamic MFIs (N = 48,360 loans across 120 rural districts), and the UNDP Multidimensional Poverty Index. The methods used include multivariate logistic regressions, structural equation modeling (SEM), and GIS mapping, utilizing R (v4.2.2) and lavaan (v0.6-12). Results indicate that DFT deployment is associated with a 5.8 percentage point increase in on-time repayments (OR = 1.27, p < 0.001) and a 5.9 percentage point reduction in default rates (OR = 0.72, p < 0.001). SEM reveals that DFT significantly moderates the effect of conflict intensity (? = 0.29, p < 0.01). GIS heatmaps show that DFT enables sustained outreach in high-conflict areas. This study demonstrates that DFT analytics can improve the performance and resilience of Shariah-compliant MFIs, offering valuable insights for policy regarding digital infrastructure investment in conflict-affected economies.