Assessing Catastrophe Risk Transfer at Tokyo Marine Insurance Company

Thesis Abstract

This study investigates how catastrophe risk transfer mechanisms are utilized and optimized within Tokyo Marine Insurance Company to manage exposure to aggregated portfolio losses arising from natural disasters and extreme weather events in Japan and key global markets. Despite Tokyo Marine’s established reinsurance program and capital market solutions, gaps remain in understanding how transfer structures influence risk-adjusted profitability, capital adequacy, and resilience to correlated catastrophe losses, particularly in the context of evolving climate-risk profiles and changing regulatory expectations. The aim is to assess the effectiveness, efficiency, and strategic fit of catastrophe risk transfer (CRT) instruments, including proportional and non-proportional reinsurance, catastrophe bonds, industry loss warranties, and securitization via special purpose vehicles, in achieving optimal risk transfer, cost containment, and solvency metrics. Specific objectives are to (1) map the current CRT architecture and its alignment with the firm’s risk appetite; (2) quantify the cost–benefit profile of each CRT instrument under baseline and stressed loss scenarios; (3) examine the impact of CRT on solvency position, using internal risk-based capital (RBC) and Solvency II-like metrics; (4) evaluate decision-making processes and governance around CRT selection, including model risk and operational risk considerations; and (5) develop a data-driven framework to inform strategic CRT decisions under climate and regulatory uncertainty. The methodology adopts a mixed-methods design, combining a quantitative analysis of historical loss data, premium adequacy, and capital impact with qualitative insights from risk management interviews. The population comprises Tokyo Marine’s global underwriting portfolio, reinsurance treaties active from 2018–2024, and associated market data. A stratified random sample of 60 treaty documents and 30 catastrophe scenarios is used, paired with 25 semi-structured interviews of risk managers, actuaries, and senior underwriters. Data collection instruments include a structured treaty catalog, loss-history databases, actuarial models, and interview guides designed to elicit decision rationale, governance processes, and perceived limitations of CRT tools. Validity and reliability are enhanced via triangulation of documentary evidence, expert review of the modeling framework, and a pilot test of interview protocols. Analytical techniques encompass regression analysis to identify determinants of CRT cost efficiency, event-study style assessment of capital impact around major events, scenario analysis using stochastic catastrophe models, and a multi-criteria decision analysis (MCDA) to compare instrument attractiveness under varying risk appetites. The theoretical framing draws on the Basel-style risk management theory and the contingent-claims theory of insurance, complemented by the Resource-Based View to assess how CRT capabilities contribute to competitive advantage. A conceptual model is developed to link CRT instrument choice, operational risk, regulatory capital, and profitability outcomes. Expected findings indicate that a diversified CRT portfolio yields measurable reductions in solvency volatility and improved cost efficiency relative to reliance on traditional proportional reinsurance alone, with non-proportional limits and industry loss triggers offering superior performance under high-severity, low-probability events. The analysis is anticipated to reveal trade-offs between transfer costs, basis risk, and capital relief, with optimal configurations varying by line of business and geographical exposure. The study will identify governance gaps in model validation, data quality, and scenario framing that influence CRT decision quality and propose an integrated governance and analytics framework. The contribution to knowledge lies in providing a empirically grounded assessment of CRT effectiveness within a leading insurer operating in a complex, interconnected risk environment, and in offering a decision-support toolkit that integrates quantitative risk metrics with qualitative governance considerations. The study concludes that a holistic CRT strategy—combining targeted non-proportional reinsurance, catastrophe-linked securities tailored to gilt-like risk profiles, and robust model risk management—enhances financial resilience and strategic flexibility. Recommendations include refining data capture for loss and exposure, expanding the use of parametric and industry-wide instruments for tail-risk coverage, strengthening model governance, and aligning CRT decisions with climate-adaptive capital planning and regulatory expectations.