Taking Anhui Province as a case study, this research addresses the pain points of traditional weather index insurance for rice cultivation. It proposes applying the Lasso algorithm to screen multiple weather factors for optimizing the payout index. Using June wind speed as the core quantitative factor, a risk assessment framework based on historical meteorological and yield data is constructed. Simultaneously, it innovatively integrates blockchain technology throughout the insurance lifecycle, establishing a decentralized system for policy purchase, underwriting, claims processing, and data sharing. Leveraging smart contracts enables automatic claims settlement triggered by meteorological data, significantly reducing underwriting and claims assessment costs while enhancing transparency and mitigating moral hazard and adverse selection. To further promote market adoption, the study designs incentive mechanisms and referral programs to improve information disclosure and user engagement. Overall, this innovation enriches the agricultural insurance system both theoretically and practically, substantially reducing information asymmetry and basis risk, and holds potential to stabilize farmer incomes and foster the healthy development of the insurance industry.
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Share and Cite
Chang, J., Zhu, J. (2025) Optimization of Weather Index Insurance for Rice Cultivation Based on Relaxed Lasso-blockchain Hybrid Technology: A Case Study in Anhui Province. Hong Kong Financial Bulletin, 1(6), 44-50. https://doi.org/10.71052/hkfb2025/PSHK2570