The frequency and severity of extreme weather events have increased dramatically in the past few decades, with a recent United Nations report revealing that climate-related disasters saw an 83% increase in the past two decades alone. This has been gravely impacting business practices worldwide. Two of the most exposed sectors to climate-related losses in this regard are the banking and insurance sectors.
In the banking sector, several studies have established that climate change is one of their biggest emerging risks. A KPMG analysis for instance, revealed that 77% of the banks they assessed disclosed that climate-related risks could have a material or adverse impact on their businesses.
Mark Carney, the former Governor of the Bank of England, says that the stage is set for what could possibly be climate risk’s “Minsky moment”, a sudden and vast realisation of the enormity of climate risk, possibly leading to sudden drops in asset values for vulnerable companies.
Read our blog on Global Banking Imperatives to Tackle Climate Risk to know more.
Understanding Climate Risk Analytics:
As the impact of climate change becomes glaringly evident, it has become imperative for financial and business leaders to assess their vulnerabilities to climate change and develop risk mitigation strategies. Climate Risk Analytics (CRA) in this regard has emerged as a new domain that plays an important role in identifying risks associated with climate change. At present, the Climate Risk Analytics market is valued at $40 billion and is projected to rise further in the coming years. The analysts at the Bank of America in this regard estimate that the climate adaptation market will increase to $2 trillion a year over the next five years.
By using advanced data and analytics tools, CRA helps banks and insurers gain a more clear understanding of their exposure to climate risks at various time frames and under several plausible scenarios. CRA involves analyzing a range of data sources, including weather patterns, sea level rise projections, and environmental regulations, to assess the potential financial impacts of climate-related events such as natural disasters, changes in weather patterns, and shifts in consumer behaviour.
The goal of climate risk analytics is to help banks and insurance companies mitigate or manage climate risks in order to protect their financial interests. They do so by helping them:
Monitor Exposure to Climate Risks: It helps banks and insurers understand how climate change impacts their operations and investments and enables them to identify climate risk blind spots.
Develop Risk Mitigation Strategies: By understanding their vulnerability to climate risks, CRA enables entities to craft appropriate risk management strategies and minimise losses.
Aid the decision-making process: By providing helpful insights, it aids in the decision-making process. For instance, by analyzing the potential impacts of climate-related risks on the assets in their portfolios, banks can make more informed decisions about which investments to make and which to avoid. Likewise, it helps insurance companies ensure that premiums are set at a level that accurately reflects the risk being insured.
Build Resilience: Further, by using multiple scenarios for assessment, it can consider a broad range of outcomes. Thus by using advanced analytics tools, they can identify potential climate-related risks in their portfolios’ potential financial future. This allows them to mitigate these risks before they become significant problems, helping them build the resilience of their organisation and ensure their long-term stability.
Develop cost-effective climate change adaptation strategies: By providing them with a probable picture of their financial future, climate risk analytics also allows banks and insurers to take a more proactive approach and develop cost-effective climate change adaptation strategies.
Climate Risk Analytics: Driven by Data
Data is key in driving climate risk analytics. While many factors play an important role in CRA, such as strong computing systems capable of crunching more data and effective frameworks, data remains the paramount factor, as any assessment tool is only as good as its inputs. In this regard, high-frequency climate data sets covering a large gamut of physical risks with global coverage and high-resolution is essential for credible risk analysis.
As the importance of climate risk analysis becomes more apparent, several new approaches and tools are being developed to monitor climate risks accurately, including open systems, edge processing, space-based systems, cloud computing and artificial intelligence, among others. This is driven by unprecedented advancements in science and technology. Among these approaches, satellite data has emerged at the forefront of the climate data landscape because of its ability to capture huge troves of data at various resolutions at high frequency and at an economical cost. Currently, over 50% of Essential Climate Variables, key indicators of the earth's changing climate, can be tracked only through satellites.
Though satellite data plays a crucial role in climate intelligence, the terabytes of such data are of low value unless appropriate intelligent modelling is used to carve out actionable climate data sets from the mountains of raw data. Climate intelligence firms with strong analytical skills and computational capacity thus play an important role in deriving and consolidating actionable data sets from various satellites. To learn more, read our blog on What is Climate Intelligence & How Can Satellite Data Help?
Credible climate data for a gamut of physical risks available at a high frequency and at an economical cost is the most pressing requirement for banks and insurance companies today to minimize climate-related financial and operational risks. By using advanced Climate Risk Analytics tools to assess the risks associated with various investments and strategies, banks and insurers can help to identify the most effective ways to reduce climate and environmental risks and transition to a more sustainable future. While climate risk analytical models may be marked by a certain level of inaccuracies, credible, high-frequency data for as many physical risks as possible can enhance the management of climate and environmental-related risks to banks and insurance firms