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Abstract This article proposes a framework for integrating agricultural zoning data into insurance risk analysis. It is based on combining official public information from the Brazilian zoning program, ZARC, with open insurance data provided by the Brazilian Ministry of Agriculture and Livestock. The methodology presented in this article transforms ZARC information into distributional data and integrates it into a Bayesian model alongside insurance indemnities data, allowing for comprehensive risk analysis. It uses information on soil types from ZARC to develop basic best- and worst-case scenarios and calculate posterior distributions using insurance data. The resulting framework enables the comparison of municipalities, crop types, and overall risk classification. The study applies the framework to analyze the risk of soybeans, corn, wheat, and corn double-crop in Paraná State, resulting in consistent risk classifications across all crops and municipalities. The proposed framework has the potential to enhance agricultural risk management analysis for reinsurers, insurers, government agencies, and private companies. Future research could explore the use of this methodology to compare insurers, analyze risk in structured operations of credit and insurance, and evaluate risks at the farm level. This article presents a potential tool for improving risk analysis and decision-making in the agricultural sector. |
