Blockchain-enabled Parametric Insurance for Climate Risks: An Empirical Evaluation

Thesis Abstract

This study addresses the growing vulnerability of agricultural and small-business communities to extreme climate events and the inefficiencies in traditional insurance mechanisms that hinder timely payouts. The problem is the misalignment between trigger-based payouts and actual liquidity needs, compounded by opacity in claims processing and high transaction costs. The aim is to evaluate the feasibility, performance, and governance of blockchain-enabled parametric insurance for climate risks, with a focus on payout timeliness, transparency, and risk transfer effectiveness. Specific objectives are (1) to design a parametric product framework linked to verifiable climate indices and forge a secure smart contract–driven payout mechanism; (2) to assess stakeholder perceptions, trust, and adoption barriers among policyholders, insurers, and regulators; (3) to quantify payout latency and operational costs relative to traditional insurance under varying climate scenarios; (4) to model financial resilience outcomes for insured entities under different indemnity triggers; and (5) to provide policy and technical recommendations to scale blockchain-enabled parametric solutions. The study adopts a mixed-methods research design, integrating quantitative event-based simulations with qualitative insights from industry stakeholders. The population comprises micro, small, and medium-sized enterprises (MSMEs) in climate-sensitive sectors (agriculture, tourism, and logistics) and staff at three regional insurers that have pilot-tested blockchain-based parametric products in Southeast Asia and Sub-Saharan Africa. A purposive sample of 600 insured entities will be drawn for survey data, supplemented by 30 in-depth interviews with risk managers, actuaries, IT officers, and regulatory officials. Climate event data will be sourced from national meteorological services and satellite-derived indices (e.g., precipitation anomalies, wind speed, drought indices) over a ten-year horizon. Instruments include a structured questionnaire measuring trust in technology, perceived value, and willingness to adopt, a semi-structured interview guide for expert insights, and a data log from the sandbox smart contracts platform to capture payout events, latency, and cost metrics. Validity and reliability will be established through pilot testing, triangulation across data sources, and Cronbach’s alpha checks for multi-item scales. Analytical methods combine descriptive and inferential statistics with blockchain-specific performance metrics. Payout timeliness and cost efficiency will be evaluated using time-to-payout analyses and survival models, while regression analysis (mixed-effects models) will examine determinants of user adoption and satisfaction. The study will also employ event studies to assess financial resilience outcomes post-event, and cost-benefit analysis contrasting blockchain-enabled parametric payouts with conventional indemnity products. A theoretical lens will be anchored in Technology Acceptance Model (TAM) and Institutional Theory, complemented by the Risk-Management Theory of Insurance, to interpret adoption dynamics and governance challenges. The conceptual model posits that perceived ease of use, perceived usefulness, and regulatory legitimacy positively influence adoption, which in turn improves payout speed, transparency, and resilience metrics. Expected findings include (i) reduced payout latency from an average of 7–10 days under traditional systems to near real-time disbursement within 24 hours for predefined triggers, (ii) lower administrative and fraud-related costs due to automated smart contracts and immutable audit trails, (iii) higher trust and willingness to pay among policyholders when verifiable index data and transparent processing are available, (iv) measurable improvements in liquidity ratios and recovery times for MSMEs after climate shocks, and (v) evidence of governance challenges related to cross-border data sharing, data quality, and regulatory compliance that influence adoption rates. The study anticipates identifying a positive association between regulatory clarity and faster scaling of parametric blockchain solutions, moderated by the sophistication of the technical interface used by beneficiaries. Contributions to knowledge include an empirical assessment of blockchain-enabled parametric insurance in a developing-economy context, an integrated framework for evaluating payout efficiency, trust, and resilience, and practical guidelines for policymakers and insurers regarding product design, data governance, and digital infrastructure requirements. The research will also extend the literature on fintech-enabled risk transfer by demonstrating how immutable smart contracts and verifiable climate indices can align incentives among stakeholders while delivering timely relief. The main conclusion is expected to be that blockchain-enabled parametric insurance can significantly enhance payout speed and transparency, provided that data quality, regulatory alignment, and user-centric interface design are jointly addressed. Recommendations include standardized yet adaptable trigger frameworks, robust data governance protocols, interoperability standards for meteorological data, and phased scaling strategies with continuous monitoring and independent audits.