From actuarial models to climate models: How CFOs are redefining insurance economics

Today we can all say that each one of us is affected by climate change, it is no longer a thing in the books or a future event. In the recent years, extreme weather events and natural catastrophes are occurring more often, a trend that is projected to accelerate further due to the rapid changes in global climate systems.

India has made notable progress in bringing down its vulnerability to extreme weather conditions, moving from 7th to 49th in the global Climate Risk Index between 2019 and 2022. However, historically it remains among the top 10 most affected country, as the sixth worst in long-term (1993-2022) assessment. It is said that India has 17% of the world’s population but contributes to only 7% of emissions, demonstrating our strong sense of sustainability and agility.

Climate change remains a critical component for insurers in understanding and managing the risks associated with extreme weather situations. Insurers play a key role in helping individuals and businesses recover from natural catastrophes by offering financial protection, risk management insights, advanced modelling and other tools that can play a vital role in advising companies, governments, and municipalities on how to reduce risk and thereby build resilience.

However, the level of preparation depends on the risk assessment, which, in a climate-impacted era, is proving a challenge. With dramatic announcements of targets by the government, the insurance industry must remain committed to this aim. It has urged general insurance companies to implement tighter underwriting through more astute risk assessment models.

Historical data and demographic trends are analysed to assess risk for suitable pricing of insurance products. But when climate change is reshaping risk itself, historical baselines may not suffice when predicting unexpected adverse events. With a climate-impacted ecosystem, risk can no longer be assessed purely by crunching past numbers. For more accurate pricing, underwriting, and capital allocation, it is essential to integrate climate dynamics into actuarial models.

Integrating Climate Data into Underwriting and Pricing

“The past is no longer enough” hence no underwriter can rely just on spreadsheets and historical data.

Traditionally, underwriters have leaned heavily on actuarial models that are built on decades of loss experience. These models deploy mathematical equations to analyse historical weather data to predict future events. However, an increasingly warming world is disturbing these models and affecting their ability to assess the frequency and severity of losses. Floods are hitting cities with traditionally moderate rainfall, heatwaves are becoming more intense, storms are becoming stronger and more frequent, and forest fires more raging.

Resultantly, insurance companies are now increasingly leaning towards integration of geospatial climate data, emissions trends, and global climate scenarios, into pricing models. Climate data for underwriting and pricing strategies now encompasses more than mere weather patterns. For instance, insurers are studying crop yield data, soil fertility levels, water table indicators, etc., to adjudge amount of premiums for crop insurance. By listening to the planet’s data signals and blending traditional actuarial methods with future climate projections, insurers are pricing risk more accurately and innovating in products. For instance, Parametric insurance deploys advanced risk assessment models to deliver crop protection for flood-vulnerable and drought-prone farming communities.

The insurance ecosystem is fast moving from a reactive to a proactive approach and its not about history but what the future will bring along. Rather than pricing-based only on past losses, insurers are factoring estimated future realities into the pricing mix. 

Predictive Models to Address Complexity and Sustainability

The turning of uncertainty into insight is the need of the hour. The complexity of climate risk demands a new generation of predictive models, the ones that combine financial, actuarial, and environmental metrics. For example, the integration of satellite data on sea-level rise with reinsurance loss curves and investment portfolio exposure may throw up more accurate findings. Likewise, underwriters of crop insurance products are using agricultural yield predictors and machine learning based yield forecasting. These insights enable insurers to forecast not only claims patterns but also the financial stability of their capital reserves under different climate scenarios.

Insurers today are not only managing risks – they are reimagining it. They are also ensuring that the returns transcend compliance or sustainability reporting and deliver profitable growth. Moreover, finance teams collaborate with risk officers, data scientists, and actuaries to translate complex environmental variables into tangible financial strategies. The risk assessment models are supposed to bridge the gap between sustainability aspirations and financial realities.

New playbook of Insurance Economics

The failure to account for climate change and only relying on historical data is a task of the past. The sheer scale of integration that actuarial data requires with climate trends is more than a technical adjustment; it’s a fundamental rethinking of insurance economics.

It is our moral imperative to generate accurate models that will ensure robust underwriting and mitigate instances of adverse selection, resulting in portfolio resilience. Again, it will ensure that capital allocation strategies will be better aligned with long-term pricing risks and protect shareholder value. Consequently, insurers will be better equipped to serve policyholders, helping societies absorb the shocks of climate change while building financial resilience.

The rising costs of extreme weather situations and natural catastrophes point out an urgent need for action from various stakeholders to collaboratively build climate resilience. While failures in newer methods may occur but they pale in comparison to the catastrophic unchecked climate related disasters.

This task is difficult but not impossible, proactively adaption of new models will enable us to be better prepared from the rising threats of climate change.