We propose a new mechanism to design risk-pooling contracts between operators to improve service resilience during disruptions. We formulate a novel two-stage stochastic multicommodity flow model to determine the cost savings of a coalition under different disruption scenarios and solve it using L-shaped method along with sample average approximation. Computational tests are conducted for network instances with up to 1024 scenarios. The proposed model is applied to a regional multi-operator network in the Randstad area of the Netherlands, for four operators, 40 origin-destination pairs, and over 1400 links where disruption data is available. Using the proposed method, we identify stable cost allocations that could yield a 66% improvement in overall network performance over not having any risk-pooling contract in place. We illustrate the sensitivity of the HTM operator's bargaining power to different network structures and disruption scenarios.