<p>This paper develops a jump-diffusion model for risky assets, where the jump component is governed by a multidimensional dynamic contagion process. This process captures contagion risks driven by both endogenous mechanisms and exogenous shocks. The insurer aims to maximize the expected discounted utility of cumulative dividends through the joint optimization of dividend distribution, policy issuance, and surplus investment. The model also incorporates dependence between financial and insurance markets. Using the dynamic programming principle, we derive and solve the associated Hamilton-Jacobi-Bellman (HJB) equation under a logarithmic utility function, establishing the existence of optimal strategies. A verification theorem is rigorously proved by leveraging the ergodicity of the dynamic contagion process. To the best of our knowledge, this is the first work to exploit the ergodicity of dynamic contagion processes in insurance optimization, offering a tractable method for solving the associated PDE and verification problem. Under a specific factor structure, we further derive explicit expressions for the optimal strategies. Numerical experiments illustrate how these strategies evolve in response to changes in contagion intensity.</p>