Climate risk analysis workflow challenges

Climate Change Risk Assessments 🌎 Climate-related financial disclosure requirements are expanding across jurisdictions, increasing expectations for companies to assess and report on climate-related risks and opportunities. A structured climate change risk assessment (CCRA) is central to meeting these evolving regulatory demands. CCRAs evaluate both physical risks—such as extreme weather events, water stress, and sea level rise—and transition risks, including policy changes, carbon pricing, and shifts in market or technology landscapes. They also help identify potential opportunities linked to decarbonization, energy efficiency, and new revenue models. Scenario analysis is a core component. It enables companies to test strategic resilience under divergent climate pathways, including high-emissions futures and low-emissions transitions aligned with the Paris Agreement. Most regulatory frameworks now require both perspectives. Benefits of a robust CCRA include improved risk management, reduced exposure to disruptions, and strengthened alignment with investor expectations. Insights from these assessments can be embedded into enterprise risk systems, capital planning, and strategic roadmaps. Key challenges include short-term thinking in risk registers, limited access to forward-looking climate data, and misalignment between climate risk analysis and existing sustainability goals. These gaps can reduce the effectiveness of disclosures and slow organizational response. Recommended approaches include leveraging established scenarios (e.g. IPCC, IEA), integrating outputs into ERM systems, using frameworks like ISSB and TCFD for structure, and applying competitive benchmarking to validate assumptions. Cross-functional engagement improves practical relevance. As regulatory standards converge, CCRAs are becoming a baseline expectation. Those who develop structured, forward-looking assessments will be better positioned to adapt business models, manage uncertainty, and align with capital markets under increasing climate scrutiny. Source: Ramboll #sustainability #sustainable #business #esg #climatechange #risk

⚠️ 4 critical mistakes in your physical risk scenario analysis…  And how to avoid them    Having worked on scenario analysis with dozens of financial institutions and corporates, I see 4 common errors that vastly reduce the usefulness of the assessments and leave firms exposed to climate shocks. These are:  - Confusing Average Scenarios with Extremes  - Misalignment of Time Horizons  - Narrowing the Range of Relevant Hazards  - Ignoring Second-Order Effects and Correlations    Through our team’s experience supporting on climate scenario analysis, financial stress testing and risk modelling, we have developed strategies to help you avoid these pitfalls.     Below is our downloadable for identifying and addressing these 4 errors. It’s free for you to download and use as a resource with your risk and modelling teams. 👉 Newsletter subscribers get the earliest access to these new resources and also get a deep dive into overcoming these 4 errors.  Subscribe today and don’t miss out: https://lnkd.in/eAtjsNbA #ClimateRisk #PhysicalRisk #ClimateChange #RiskManagement #SustainableFinance #StressTesting #ScenarioAnalysis 

As we’ve discussed in previous posts, regulators expect climate risk to be integrated into ECL frameworks. ECL requires scenario weighting. But on the climate side, we don’t have these weights ready. This is where EDHEC’s research offers a practical breakthrough (https://lnkd.in/e3bNRgQM). It developed a way to introduce scenario probabilities for climate risk. This is a great starting point for aligning climate risk with ECL-style calculations. While there are many useful outputs from this research, here I want to focus on Step 1: assigning scenario probabilities and comparing this to what we intuitively do in ECL. In typical ECL modelling: - The baseline scenario gets most of the probability weight (often 70-80%), - With downside and upside scenarios splitting the rest. But in the climate space, this intuition breaks down. According to EDHEC scenario probabilities: -“Climate Catastrophe” receives 57.5% probability. -The “Baseline” scenario receives only 5%. In other words, climate catastrophe becomes the “new baseline”. The whole risk modelling approach needs to change. Currently, we are modelling climate risk as if catastrophe is a tail event, while sleepwalking into catastrophe being the most probable scenario. Other scenarios, e.g. net zero, delayed transition, climate distress, should be modelled in comparison to this “new baseline” of catastrophe, not the other way around. This is not just a technical nuance. If we are serious about integrating climate risk into ECL, this reframing is necessary.

Published in February 2025, this paper conceptually investigate 𝗖𝗹𝗶𝗺𝗮𝘁𝗲 𝗥𝗶𝘀𝗸 𝗦𝘁𝗿𝗲𝘀𝘀 𝗧𝗲𝘀𝘁𝗶𝗻𝗴 (𝗖𝗥𝗦𝗧) 𝗲𝘅𝗲𝗿𝗰𝗶𝘀𝗲𝘀 𝘁𝗼 𝗮𝘀𝘀𝗲𝘀𝘀 𝘁𝗵𝗲 𝗶𝗺𝗽𝗮𝗰𝘁 𝗼𝗳 𝗰𝗹𝗶𝗺𝗮𝘁𝗲-𝗿𝗲𝗹𝗮𝘁𝗲𝗱 𝘀𝗵𝗼𝗰𝗸𝘀 𝗼𝗻 𝗳𝗶𝗻𝗮𝗻𝗰𝗶𝗮𝗹 𝗶𝗻𝘀𝘁𝗶𝘁𝘂𝘁𝗶𝗼𝗻𝘀 (such as banks, pension funds, and insurance companies) and on financial system stability. Authors distinguish between climate, economic, and financial modeling steps, and classify #CRST exercises into six types of climate shocks and four different approaches (macro-financial, micro-financial, non-structural, and disaster risk). Several key limitations in current CRST approaches are identified: (i) 𝗻𝗲𝗴𝗹𝗲𝗰𝘁 𝗼𝗳 𝗰𝗲𝗿𝘁𝗮𝗶𝗻 𝗰𝗹𝗶𝗺𝗮𝘁𝗲 𝘀𝗵𝗼𝗰𝗸 𝘁𝘆𝗽𝗲𝘀 (Green Swan and Minsky-type events); (ii) 𝗼𝘃𝗲𝗿𝗿𝗲𝗹𝗶𝗮𝗻𝗰𝗲 𝗼𝗻 𝗺𝗮𝗰𝗿𝗼 𝗺𝗼𝗱𝗲𝗹𝘀 (with low sectoral and spatial granularity); (iii) 𝗶𝗻𝗰𝗼𝗺𝗽𝗹𝗲𝘁𝗲 𝗺𝗼𝗱𝗲𝗹𝗶𝗻𝗴 (lack of feedback effects); and (iv) 𝗹𝗶𝗺𝗶𝘁𝗲𝗱 𝘀𝗰𝗼𝗽𝗲 (subset of causal channels and asset classes). Authors argue that these limitations may lead to significant underestimation of potential system-wide financial losses and offer suggestions for improving CRST approaches. #riskmanagement #climaterisk #transitionrisk #stresstesting #physicalrisk #scenarioanalysis #mertonmodel #intergratedassessmentmodel #riskmitigation #riskmeasurement #riskassessment #climatestresstest #internalmodeling #Greenswan #spatialgranularity #transmissionchannels #assetclasses #financialrisk #FRM #financiallosses #Minskytypeevents #information #resources #knowledge #financialstability #climatechange #netzero #CCUS #disasterrisk