Agricultural Risk Transfer

CHAPTER 4Agricultural Data and Proxies

4.1 INTRODUCTION

Exposure analysis, underwriting and pricing of agricultural risk transfer products require a large amount of data, including historical insurance claims, climate data, crop yield data, mortality statistics, satellite imageries and outputs from physical models. Data from different sources need to be combined to obtain meaningful estimates of past and future risks for a single risk and for entire portfolios of risks.

However, agricultural data and proxies often include inconsistencies and limited time spans, and show trends over time so that historical data do not necessarily reflect future loss potentials. Most agricultural production systems have gone through industrialisation and verticalisation in recent decades, which typically decreases the vulnerability to localised losses but increases the loss potential from systemic events. Trends in production statistics are often driven through improved technology, specialisation and verticalisation, changing weather patterns and new biosecurity regulations for epidemic diseases.

This chapter first introduces different sources of climate data and statistical methods to examine and remove data consistency and trends. Data from satellites and other remote sensing devices are discussed with a focus on vegetation indices (VI) and forest area burnt. Different sources of crop yield data are presented thereafter, including the main statistical concepts to prepare the data for pricing ...