Climate change-induced extreme disasters cause significant economic losses to distribution system operators (DSOs). This paper proposes a resilience enhancement strategy considering insurance investment budgets. The approach simulates distribution system (DS) reconfiguration from insurers’ perspective to determine affordable insurance budgets for DSOs, optimizing resilience within these constraints. First, k-means clustering with Hausdorff distance processes historical typhoon tracks, generating typical fault scenarios via Monte Carlo simulation. The strategy is modeled as a scenario-based stochastic mixed-integer linear program (SMILP). During planning, insurers optimize DS reconfiguration under fault scenarios to determine investment strategies. During operation, insurers develop planning strategies based on these investments, including DG and ESS allocation plus insurance reserves. Commercial solvers and genetic algorithms solve the planning and operation stage models, respectively. Testing on the IEEE 33-bus system verifies the strategy’s validity. Results demonstrate that the combined planning-operation approach considering insurance budgets effectively enhances resilience by reducing both economic losses and load shedding during extreme events. This insurance-investment framework provides DSOs with a practical mechanism to improve disaster preparedness while managing financial constraints.