The latest update from the Network for Greening the Financial System (NGFS) marks an important inflection point for climate risk practitioners. For the first time, the NGFS is explicitly signalling that non-linear climate risks — including tipping points, feedback loops, and compound shocks — deserve serious attention in financial risk frameworks. It explicitly highlights that E3ME-FTT is a model that captures many of the factors in the guidance. 

NGFS has been instrumental in bringing climate risk into the mainstream of financial supervision. Its scenarios have become the global reference point for banks, asset owners, asset managers, and insurers and it’s exciting to follow their evolution into non-linear dynamics. The new guidance makes one thing clear: a “smooth” view of climate and transition risk is no longer enough. 

What does the latest NGFS guidance mean for you? 

If you are a risk practitioner at a financial firm, here is the practical interpretation: 

1. The new guidance is not saying “NGFS data is now fully non-linear” 

A key point: the NGFS is not saying that its own scenario data will suddenly become fully non-linear or that it now comprehensively captures tipping points. 

Rather, the NGFS is saying something more subtle and important: firms should recognise the limits of any single model set and actively account for non-linear, tail, and compound risks. 

2. Scenario analysis is moving from “box-ticking” to “risk realism” 

Climate impacts do not occur in isolation. Physical and transition shocks often arrive together, and existing economic weaknesses can amplify them. These dynamics are inherently non-linear and difficult to capture with traditional, equilibrium-style models.  

As the NGFS now openly acknowledges, accurately representing these dynamics is one of the biggest challenges in climate risk analysis. The good news is there are solutions available on the market. 

If NGFS isn’t enough on its own, what should you look for? 

The NGFS guidance encourages using more than one model or approach to measure climate risk and urges practitioners to understand the strengths and limitations of approaches used.  

When assessing additional data or model providers, risk teams should ask: 

1. Do they explicitly model non-linear shocks, tipping points, and feedback loops? 

   
   

2. Can they capture compound risks (e.g., physical and transition risks occurring together)? 

   
   

3. Do they model policy mechanisms directly, rather than relying on abstract ‘red-herring’ proxies such as shadow carbon prices?  

   
   

4. Can their outputs be downscaled to sector, region, and asset-level impacts, rather than remaining purely macro? Do they look at sectoral output dynamics, price-wage dynamics, demand impacts and fuel costs, for example? 

   
   

5. Do they allow you to test multiple plausible futures, rather than a single, smooth transition path? 

What this means in practice 

For most firms, “good practice” now looks like this: 

• Deep-dive into providers to make sure you select one that you understand and is in line with the latest non-linear guidance 

  
  

• Use a climate-informed baseline that recognises non-linear transition and hazard impacts 

  
  

• Stress-test your portfolios not only against “likely” transitions, but against plausible extreme outcomes

  
  

• Integrate insights into investment strategy 

  
  

  The NGFS has helped the financial system recognise climate risk. Its latest guidance helps the industry mature. Now is the time to ask a more sophisticated question: “What happens if the future isn’t smooth, or linear?” That is where non-linear scenarios, specialist models and deeper granularity move from “nice to have” to essential.