Comparative Analysis of Climate Risk Versicherung Pricing Across Markets

Thesis Abstract

This study addresses the escalating fragmentation in climate risk insurance pricing across developed, emerging, and frontier markets, where divergent regulatory environments, capital market depth, and risk assessment practices yield inconsistent premium rates and coverage terms that hinder cross-border portfolio diversification and scalability. The aim is to compare climate risk Versicherung pricing across markets to identify drivers of price dispersion, assess pricing efficiency, and evaluate the impact of climate hazard exposure, parametric structures, and reinsurer capacity on premium levels. Specific objectives include (1) quantify price discrimination by market, peril type (flood, storm, drought), and policy form (parametric vs. indemnity); (2) examine the influence of regulatory stringency, capital adequacy, and actuarial sophistication on pricing; (3) analyze the role of climate model output quality, catastrophe risk capital, and model governance on premium setting; (4) evaluate customer and firm-level heterogeneity in demand and its effect on pricing sensitivity; and (5) propose an integrated framework for harmonizing pricing practices to improve market efficiency and resilience. The methodology employs a mixed-methods research design combining quantitative cross-sectional analysis with qualitative insights. The population comprises climate risk insurance providers and reinsurers operating in three representative markets North America, Southeast Asia, and Sub-Saharan Africa, with a target population of 60 firms and 120 major policy portfolios. A stratified random sample of 36 firms (12 per market) and 180 policy lines (60 per market) will be analyzed. Primary data will be collected through structured pricing data sheets, regulator reports, and semi-structured interviews with underwriting heads and actuaries, while secondary data will include publicly available pricing indexes, catastrophe loss databases (e.g., TRACE, CATIQ), and market concentration metrics. Instrument validity will be ensured via pilot testing with three industry experts and reliability through test-retest procedures and Cronbach’s alpha for scales assessing governance, data quality, and model sophistication. Analytical techniques include descriptive statistics to profile price distributions by market and peril, followed by multivariate regression analyses to test the determinants of pricing (market, peril, policy form, regulatory variables, and model quality). A hierarchical linear modeling (HLM) approach will account for nested data structure (policy lines within firms within markets). ANOVA and post hoc tests will compare mean premium levels across markets and policy forms. Factor analysis will identify latent constructs representing pricing sophistication, regulator stringency, and model governance. The study will also employ a qualitative thematic analysis of interview transcripts to contextualize quantitative findings, triangulating results with regulator and insurer documents. The theoretical framing draws on the Portfolio Theory of Insurance Pricing to explain capital allocation decisions, and the Institutional Theory to interpret regulatory and governance influences on pricing choices. Key expected findings include (i) significant price dispersion across markets driven by regulatory stringency, reinsurance capacity, and model governance quality; (ii) higher pricing efficiency in markets with mature actuarial practices and robust catastrophe risk models, controlling for exposure; (iii) evidence that parametric products exhibit more transparent and stable pricing in high-exposure markets, while indemnity-based products show greater price variability; (iv) positive association between data quality, model validation frequency, and pricing stability; and (v) partial mediation of pricing differences by policy form and reinsurer involvement. The study anticipates identifying gaps in data harmonization, disclosure standards, and model governance that constrain cross-market comparability. Contributions to knowledge include developing a cross-market pricing framework that links governance, data quality, and model risk to premium setting; providing empirical benchmarks for pricing efficiency across climate risk insurance markets; and informing regulators and insurers on harmonization avenues to enhance market resilience and scalability. The main conclusion is that pricing disparities are systematically shaped by governance and data quality, not solely by exposure levels, and that harmonized data standards and transparent model governance can reduce price fragmentation. Recommendations include establishing regional data repositories with standardized taxonomy, mandatory model risk management frameworks, enhanced price transparency obligations, and capacity-building programs to elevate actuarial sophistication in emerging markets.