Tech Advances Help With Climate Scenario Analysis – So Why Are Some Firms Still Struggling?

Financial services firms are still lagging when it comes to adopting climate scenario analysis into their portfolio monitoring and risk mitigation processes – despite its recognized industry value and the growing regulatory pressure in regions such as Europe (see Verdantix Best Practices: Climate Scenario Analysis). As new regulations demand more detailed climate risk assessments, many financial institutions are struggling with incorporating climate risks into their decision-making processes, due to a lack of tools and specialization. These limitations prevent firms from accurately evaluating how climate change risks – both physical and transition – might impact their operations and investments.

Climate financial data vendors play a critical role in helping to fill this gap, offering solutions for scenario analysis. Providers such as Bloomberg, Moody’s, Riskthinking.AI and S&P Global deliver solutions that enable financial institutions to model various climate futures. 

• Moody’s helps insurance firms and banks assess both physical and transition risks across multi-asset portfolios. 
• S&P Global offers physical risk models that cover 3.1 million asset locations and allow users to drill down by sector. 
• Bloomberg stands out for its expertise in transition risks, using detailed revenue projections and sector-specific climate models to estimate future risks and opportunities. 
• Riskthinking.AI excels in digital twin technology for physical risk modelling, providing insights into over 20 climate hazards, such as floods and wildfires, and their financial implications. 
  
  

These differences in approach demonstrate the breadth of solutions firms can choose from, to select an option that best suits their needs.

Despite these technological advancements, the application of climate scenario analysis to business decisions still poses significant challenges. Climate impacts often unfold over decades, while financial institutions typically operate with much shorter-term investment horizons. This misalignment creates difficulties in comparing long-term climate risk data with immediate business needs. Furthermore, the lack of industry-wide standards in the climate financial data space, coupled with data gaps and modeling complexities – such as tipping points and compound risks – generates blind spots for financial firms. While vendors are working to address these gaps, the challenge for organizations of translating these insights into day-to-day decision-making remains.

As climate risks become more unpredictable and interconnected, financial institutions must adopt more granular, real-time analysis to better navigate the complexities of climate change. With ongoing innovation in climate data tools, and increased regulatory scrutiny, firms that embrace these technologies will gain a competitive edge. In an increasingly unpredictable climate landscape, they will be better positioned to identify risks, capitalize on opportunities and ensure long-term resilience.