Applying predictive analytics to account for climate change in insurance risk management - A case study of Santam

Abstract

Weather-related disasters have become more frequent and severe in the past decade. Insurance companies continuously face increased insurance claims pay outs for property and infrastructure damage, business interruption, and other weather-related insurance claims. This surge in weather-related insurance claims strains the financial resources of insurers, leading to rising premiums for policyholders and potentially reduced coverage in high-risk areas. Moreover, the unpredictability of weather patterns makes it challenging for insurers to accurately assess and price risk, leading to uncertainty in underwriting practices. To mitigate these challenges, insurers are increasingly investing in advanced analytics and data modelling techniques and risk management strategies. However, the long-term sustainability of the insurance industry depends on collaborative efforts to address the underlying causes of climate change.

This case study explores the relationship between weather change-related occurrences and insurance claims, examining the correlation between these events and the financial ramifications experienced by the South African insurance industry. Additionally, the study investigates the specific impact of weather-related events on Santam as well as Santam's property insurance business unit, particularly focusing on the escalation of property and infrastructure damages attributable to such occurrences. Three multivariate linear regression models were developed to assess the relationships between the independent variables (number of weather-related events, average rainfall, minimum and maximum temperatures) and dependent variables (insurance claims incurred, Santam’s net underwriting margin and Santam’s property net underwriting result) . The results of the study show that there is a statistically significant relationship between financial state of the non-life insurance industry and weather-related factors such as temperature, precipitation, and natural catastrophe events. These variables were also found to be key factors in the financial losses incurred by Santam as the results show a significant positive correlation between weather change-related events and weather-related insurance claims. This implies that the higher the frequency of weather-related catastrophes, the higher the number of weather-related claims. This outcome is similar to the previous studies which assessed the impact of climate change on weather-related damages and insurance claims