Integrating Fuzzy AHP And Monte Carlo-Simulation for Robust Financial Risk Assessment in Road Infrastructure Projects: A Case Study of the Naya Sarai Four-Lane ROB, Jharkhand.

Road infrastructure projects in developing economies are routinely exposed to multidimensional financial risks arising from administrative delays, cash-flow disruptions, land-acquisition bottlenecks, and market uncertainties. Traditional risk-management frameworks, typically reliant on qualitative judgment or deterministic estimates, struggle to capture the combined effects of expert subjectivity and probabilistic cost variability. This study proposes a hybrid Fuzzy Analytic Hierarchy Process–Monte Carlo Simulation (FAHP–MCS) model to quantify and simulate financial-risk escalation for the Naya Sarai Four-Lane Road Over Bridge (ROB) project in Jharkhand, India. Eight major financial risks were identified through documentation review and expert consultation. FAHP was employed to derive uncertainty-sensitive importance weights, which were then integrated into a Monte Carlo cost-escalation model using tailored probability distributions. Results demonstrate that cash-flow failure, delayed payments, land-acquisition delays, material price inflation, and utility-shifting issues dominate the project's financial-risk structure. The probabilistic simulation indicates an 84.84% likelihood of exceeding the approved cost of ₹28.74 crore, with the expected cost centred at ₹31.18 crore. Sensitivity analysis highlights liquidity-related risks as primary cost drivers. The study contributes a robust hybrid modelling framework for improving financial forecasting, risk-based budgeting, and governance of public infrastructure projects.