Climate Analytics and Parametric Insurance Design for Disaster-Prone SMEs

Abstract

The purpose of this research study is to gain insights into the role of climate analytics in the context of parametric insurance product for small and medium enterprises that are disaster vulnerable. In flood-prone areas, SMEs may suffer from significant economic damages and disruption of business activities, and this can be a prolonged process due to floods, droughts, storms, heatwaves and other climate-related hazards. Conventional insurance may not necessarily be able to offer immediate assistance due to the damage assessment process, verification of claims and the time required to settle claims. The other option is parametric insurance, which is based on a set of climate or disaster-related parameters, such as drought index, wind speed, temperature, flood depth and rainfall level. The study will explore a mix of loss and climate data and hazard models and their associated vulnerabilities to achieve an insurance trigger that is more efficient and practical. The results indicate that climate analytics facilitates robust trigger selection, better estimation of payouts and risk classification for SMEs. The results also show the cost savings that stem from the well-designed parametric insurance and its role in financial resilience and recovery time. But issues of basis risk, affordability, data quality and automated payouts are still significant. With proper data governance, stakeholder engagement and appropriate design, contextually, climate analytics can play a role in the development of more transparent, responsive, and scalable products for disaster-prone small and medium enterprises (SMEs) in the insurance sector, concludes the paper.