Underwriting the Risks Associated with a Changing Climate
Written by Jonathan Schoelkopf & Ryan Rosario
Overview
As the economy adjusts to the increasing risks associated with climate change, insurance will continue to innovate in parallel. The purpose of this article is to discuss the challenges and obstacles that the industry faces as it adapts alongside other industries as well as spotlight some companies taking advantage of this opportunity. To begin, it’s important to understand some foundational activities and indicators associated with insurance companies. The first is underwriting, or the process of assessing and evaluating the risks associated with the “thing” the company is insuring. For a lot of new-age InsurTech companies, this is their competitive advantage. They have access to data, be it real-time or historical, that allows them to better understand risk and more accurately price the risks they are insuring.
Another term important to understand is the concept of loss ratios for an insurance company. It is a financial metric used to understand the accuracy of the aforementioned underwriting as well as other factors such as claim management. It is calculated by dividing the total amount of claims paid out by the insurer by the amount of premiums earned by the company. This output can be seen as the percentage of premiums spent covering claims. While varying heavily between different industries as well as year to year, a general benchmark is a 40-60% loss ratio.
The challenge with underwriting when it comes to climate change is that the risks are changing! Traditional risk assessment models, once reliable, are increasingly challenged by the unpredictability and severity of weather-related events. Historical data is becoming less and less of a benchmark in understanding climate risks, and that is part of this unique opportunity for the industry.
Case Study: Crop Insurance for Changing Climates
As climate change intensifies, urban areas worldwide are experiencing an increased frequency and severity of flooding events. Traditional insurance models, heavily reliant on historical data, struggle to accurately assess and price flood risks in these rapidly changing environments. This challenge has prompted a surge in innovation within the InsurTech sector, aiming to provide more accurate, dynamic, and responsive flood risk assessment tools. Many companies have emerged in an attempt to take on this problem, and better predict how weather events (or lack thereof) will impact crop yields for that year.
Historically, obtaining crop yield insurance involved a process that was heavily reliant on historical yield data and regional averages. Farmers seeking insurance would typically provide records of their past crop yields to insurers, who would then use this data, along with regional yield averages, to estimate the risk of future crop failure and determine the premium rates. This approach, while simple, isn’t fit to adapt to the rapidly changing risks caused by climate change including increased frequency of extreme weather events, shifting growing seasons, and evolving pest/disease patterns. These changes introduced new complexities that traditional one-size-fits-all methods weren’t equipped to manage. Many insurance companies as a symptom of these changes have increasing loss ratios which presents the opportunity we will be discussing today.
In the modern era, the process of obtaining crop insurance has been transformed by a slew of technological innovations. Companies now utilize satellite imagery, drone technology, and Internet of Things (IoT) sensors to gather real-time data on weather conditions, soil moisture, and crop health. Machine learning algorithms analyze this data to predict yields and assess risks with unprecedented accuracy, factoring in complex climate variables. This data-driven approach allows for the development of customized insurance products that reflect the specific risks of each farm, including coverage options triggered by specific weather events or crop yield thresholds. Such innovations not only provide farmers with more relevant and responsive insurance coverage but also enhance the overall resilience of the agricultural sector to the impacts of climate change.
Salient Predictions is a company capitalizing upon the rapidly expanding market of climate insurance, focusing on revolutionizing weather forecasting through advanced machine learning and climate expertise. It provides highly accurate sub-seasonal to seasonal (2 to 52 weeks in advance) weather forecasts by combining novel ocean and land-surface data with machine learning. Salient's approach to weather forecasting is distinguished by its use of deep neural networks to analyze a wide range of climate data, aiming for a two-fold accuracy improvement over competitive forecasts. This statistical model enables the system to navigate through the complexities of atmospheric physics, providing predictability across all aspects of the climate system. By leveraging billions of weather and climate predictors and generating millions of API data points weekly, Salient offers a breakthrough in predictability for various industries including agriculture, energy, finance, and supply chains.
Salient's work, such as providing actionable insights for AB InBev's agricultural planning through reliable seasonal forecasts, demonstrates its potential to transform how industries plan for and respond to weather variability. In summary, Salient Predictions is making a significant impact on the InsurTech industry by addressing one of the most challenging aspects of climate risk management—accurate, long-range weather forecasting.
Case Study: P&C Underwriting Using Risk Modeling
When it comes to property and casualty (P&C) insurance, underwriters examine various factors, including the physical condition, geography, and potential for claims. Historically, the process of underwriting in the P&C insurance sector consisted of manual assessments and analysis of historical data to gauge risk levels. Insurers have traditionally relied on past experiences and static risk models to make decisions, conducting physical inspections of properties to understand their condition and susceptibility to hazards.
The emergence of geographic risk modeling represents a significant evolution in P&C insurance underwriting, particularly in adapting to climate change. This approach utilizes algorithms and large datasets to analyze the potential impact of geographic and environmental factors on insured properties. By incorporating real-time data on weather events, geological hazards, and the long-term effects of climate change, geographic risk modeling allows insurers to assess risk with greater precision than before. This method not only streamlines the underwriting process by providing a more dynamic and comprehensive risk assessment but also improves the accuracy and efficiency of claim assessments. As a result, insurers can offer more tailored and responsive policies, decrease loss ratios, and enhance protection for policyholders in an increasingly unpredictable world.
When it comes to P&C insurance, innovation can be hard to find. However, Drodat is a diamond in the rough. Drodat is an innovative startup poised at the crucial intersection of property and casualty (P&C) insurance and addressing the challenges posed by climate change. With the ambitious goal of compiling the world's most extensive historical database on US property conditions, Drodat is pioneering a groundbreaking approach to risk assessment and management in the insurance sector. Utilizing advanced drone technology, the company conducts detailed inspections of properties, covering every aspect from roof conditions to foundation integrity and the potential hazards of overgrown vegetation.
This methodical data collection provides an unparalleled depth of insight into property risks, many of which have been exacerbated by the changing climate. The startup's integration of comprehensive property condition data with historical imagery, meteorological data, and maintenance records enables a sophisticated multivariate analysis. This analysis is crucial for quantifying the likelihood of future damage from increasingly prevalent climate-induced events such as storms, floods, and wildfires. The detailed risk assessments offered by Drodat are becoming increasingly vital as climate change continues to amplify the frequency and severity of such natural disasters. Drodat's contribution to combating the impacts of climate change extends beyond mere data collection and analysis. The company's personalized property risk alerts play a pivotal role in informing property owners and insurers about potential vulnerabilities, urging them to undertake preventative measures.
This proactive approach is designed not only to minimize immediate risks but also to foster long-term resilience against the adverse effects of climate change on properties. By recommending targeted risk mitigation strategies—such as the installation of fire-resistant materials or the implementation of efficient drainage systems—Drodat enables property owners to significantly reduce their vulnerability to climate-related damages. Insurers, in turn, can leverage this data to adjust premiums and policy terms dynamically, reflecting the reduced risk profile of proactively managed properties. This symbiotic relationship between data-driven risk assessment and proactive risk management marks a significant shift towards a more resilient and adaptive approach to P&C insurance in the face of climate change.
Ultimately, Drodat's innovative approach represents a vital advancement in the insurance industry's response to climate change. By harnessing detailed property data and cutting-edge analytics, Drodat is not just transforming how risks are assessed and managed; it's actively contributing to the broader efforts to adapt to and mitigate the impacts of climate change, enhancing the resilience of communities and promoting sustainable practices in property management and insurance.
Closing Thoughts
The journey from traditional underwriting and risk assessment methods to innovative, technology-driven solutions signifies a shift towards more tailored and precise insurance models industry-wide. Similarly, the modernization of crop insurance through real-time data collection reflects a significant leap forward not just in terms of technological capabilities, but also in safeguarding the agricultural sector against the increasing impacts of climate change.
These advancements, however, do not come without their own unique set of challenges. Issues like data privacy remain critical hurdles that many customers are hesitant to shift toward. However, the trajectory of InsurTech suggests a promising path forward as the industry continues to adapt in the early stages of this long period of rapid transformation. More importantly, the insurance industry is improving its capacity to manage risk while simultaneously contributing to broader efforts to mitigate and adapt to climate change.
In closing, the intersection of InsurTech and climate change presents a wide range of risks as well as opportunities. As the industry evolves, the continued collaboration between insurers and the communities they serve will be crucial in developing solutions that not only protect but also promote resilience in the face of our planet's changing climate. The journey ahead is complex, but InsurTech remains a shining beacon of hope in protecting our society and paving the journey forward.