Blockchain-enabled Dynamic Premium Pricing in Parametric Insurance Models

Thesis Abstract

The increasing adoption of blockchain technology and parametric insurance models has revolutionized the traditional insurance landscape by enhancing transparency, efficiency, and responsiveness to rapidly changing risk environments. However, a significant challenge remains in dynamically determining premiums that accurately reflect real-time risk exposure, thereby ensuring fairness and financial sustainability for insurers, while remaining competitive and attractive to policyholders. This study aims to develop a blockchain-enabled framework for dynamic premium pricing within parametric insurance models, integrating smart contract technology to automate real-time premium adjustments based on verifiable data inputs. The specific objectives are to (1) analyze the current landscape of parametric insurance and blockchain applications, (2) formulate a dynamic pricing model leveraging blockchain-enabled smart contracts and real-time data feeds, (3) empirically evaluate the model's effectiveness in predictive accuracy and operational efficiency, and (4) propose guidelines for implementation within insurance firms. To achieve these objectives, the research employed a mixed-methods approach, combining qualitative case studies with quantitative modeling. The qualitative phase involved in-depth interviews and document analysis of five leading insurance firms that have incorporated or pilot blockchain solutions, aiming to identify operational challenges, data management practices, and regulatory considerations. The quantitative phase involved developing a simulation-based model using historical climate and risk data from the Insurance Data Repository of the National Insurance Authority, encompassing a sample of 1,500 climate-related insurance claims over the past decade. Data collection instruments included structured interview guides, blockchain transaction logs, and insurance claim datasets. The core analytical techniques involved multiple linear regression analysis to assess the relationship between real-time data inputs and premium adjustments, alongside Monte Carlo simulations to evaluate the model’s robustness under varying risk scenarios. Expected findings suggest that a blockchain-enabled dynamic premium adjustment system can significantly improve the alignment of premiums with real-time risk levels, reducing adverse selection and moral hazard, and enhancing operational efficiency by automating underwriting processes. The integration of smart contracts is anticipated to decrease transaction costs by an estimated 15%, while predictive accuracy in premium setting is projected to improve by up to 20% compared to static pricing models. Additionally, the study aims to demonstrate the practical feasibility of deploying such models within existing regulatory frameworks, highlighting the importance of data integrity and interoperability between blockchain platforms and traditional insurance IT systems. This research contributes to the body of knowledge by providing an empirically validated framework for combining blockchain technology with parametric insurance to facilitate adaptive premium pricing. It extends existing technological applications in insurance by introducing a real-time, transparent, and self-executing pricing mechanism rooted in smart contract automation. Theoretically, it draws on the Risk Management Theory and the Innovation Diffusion Theory to explain the adoption and effectiveness of blockchain-enabled solutions in insurance contexts. The main conclusion indicates that integrating blockchain technology for dynamic premium pricing in parametric insurance is both feasible and beneficial, offering substantial improvements in risk assessment accuracy and operational efficiency. Policymakers and industry practitioners are encouraged to consider adopting blockchain-enabled pricing systems, emphasizing the need for regulatory clarity and data governance frameworks. Future research avenues include exploring consumer acceptance, cybersecurity risks, and cross-border interoperability issues. This study underscores the transformative potential of blockchain technology in refining risk-based premium strategies, advancing the evolution of more resilient and adaptive insurance models in an increasingly volatile risk environment.