Improving investment decisions with dynamic climate models

🌍Typology of climate scenarios by MSCI Inc. and United Nations Environment Programme Finance Initiative (UNEP FI) 🔹 1. Fully Narrative Scenarios These scenarios are qualitative descriptions of potential climate futures. ✅ Strengths: - Easily customizable - Useful for high-level strategic discussions - Can capture complex risks that are difficult to quantify ⚠️ Limitations: - Subjective and vulnerable to bias - Lack of numerical outputs makes them hard to integrate into risk models 🔍 Example Providers: - University of Exeter & Universities Superannuation Scheme 🔹 2. Quantified Narrative Scenarios This type builds on fully narrative scenarios by adding expert-driven quantitative estimates (macroeconomic forecasts, asset class returns, regional physical risks). ✅ Strengths: - Balances qualitative storytelling with numerical data - Allows for scenario comparisons without requiring sophisticated models - Easier to communicate results with clear quantitative insights ⚠️ Limitations: - Can give a false sense of precision if assumptions are weak - Still dependent on subjective expert input, leading to potential biases 🔍 Example Providers: - MSCI Sustainability Institute & University of Exeter – Estimating physical climate risks based on expert-defined damage functions. - IEA - WEO 🔹 3. Model-Driven Scenarios These scenarios rely on integrated quantitative models to project how climate change and transition risks might evolve under different policy and economic conditions, using macroeconomic models, IAMs, and energy system models. ✅ Strengths: Highly structured and data-driven, reducing subjectivity. Can produce detailed, sector-specific outputs useful for investment decisions. Widely used by regulators and financial institutions for stress testing. ⚠️ Limitations: - Expensive and time-consuming to develop and maintain - “Black box” nature of complex models makes interpretation difficult - Results are only as good as underlying assumptions and data inputs 🔍 Example Providers: - NGFS – Climate scenarios for central banks and financial supervisors - IEA – Net-Zero Emissions by 2050, STEPS & APS scenarios - IPCC – SSPs & RCPs 🔹 4. Probabilistic Scenarios Probabilistic models go beyond single-scenario forecasting by assigning probabilities, variance, and uncertainty estimates to different climate outcomes. ✅ Strengths: - Models uncertainty, improving risk management - Enables sophisticated stress testing for asset prices, portfolios, and corporate exposure - Valuable for insurance, catastrophe modeling, and financial risk assessments ⚠️ Limitations: - Highly complex and computationally demanding - Requires strong assumptions about uncertainty - Limited research on how climate change affects probability distributions 🔍 Example Providers: - NGFS & IPCC Probabilistic Models #ClimateFinance #ScenarioAnalysis #SustainableInvesting #RiskManagement #climatescenarios

A multi-agent simulation provides context when markets are likely to tip toward climate action, rather than financing distraction, i.e., greenwashing. Researchers have mapped conditions that may drive corporate climate action. Their simulation, testing 25 companies and 25 investors over 100-year scenarios, reveals specific thresholds that transform market behavior. The data shows that ESG disclosure alone doesn't change corporate conduct. The shift happens when ESG-conscious investors control 20% of market capital. At this point, companies begin investing 0.5% of their capital in emissions reduction, matching current climate leaders' investment levels. The simulation overturns assumptions about greenwashing. Despite costing 50% less than real mitigation efforts, companies abandon greenwashing because it fails to deliver long-term returns for sustained investment. The research also quantifies the value of information: companies receiving clear climate risk data increased mitigation spending by 15% even without investor pressure. In scenarios combining informed companies with engaged investors, market wealth ended 40% higher than in non-action scenarios. This suggests two practical levers for accelerating climate action: build critical mass among ESG investors while improving climate risk transparency. Kudos to Xiaoxuan Hou, Jiayi Yuan, Joel Leibo, and Natasha Jaques from the University of Washington and Google DeepMind.

Climate-related disasters may cause $12.5 TN in losses by 2050. How are investors preparing? This powerful new methodology from Institutional Investors Group on Climate Change (IIGCC) offers a way forward and includes a data tool as well. What to know: -The new Physical Climate Risk Appraisal Methodology (PCRAM 2.0) was designed for real-asset developers, managers, and capital providers. -It is applicable to both public and private sector assets and is geography agnostic. -The methodology combines insights from climate science, engineering, and finance to support a user to incorporate PCRs into asset appraisal. -PCRAM 2.0 is relevant to investment decision-makers, offering practical applications for both institutional investors and businesses to consider as they navigate uncertainty. Benefits for Investors: 1. Standardisation: Provides a consistent process for evaluating and managing investments in climate-resilient Real Estate and Infrastructure. 2. Risk and Opportunity: Focuses on resilience benefits like predictable cash flows, enhanced credit quality, and efficient long-term cost management. 3. Efficient Resource Management: Encourages a holistic approach to risk management, ensuring effective resource allocation for building resilient assets. 4. Building Investor Knowledge: Helps institutional investors navigate uncertainty Explore the methods, the data tracker, and share your thoughts here: https://lnkd.in/eKMdBSwj #climaterisk #climatefinance #investors #physicalrisk

🤓Here’s one for your holiday reading list: A new report from our Institute aims to help finance practitioners use #climate scenarios, which are a critical tool for quantifying the impact of a warming world on the value of investments. They are, however, challenging to implement for even experienced proponents. Read it here: https://lnkd.in/d_2Uzu9Z The report, which provides a practical guide to climate scenario analysis, classifies climate scenarios into four types, based on their complexity and characteristics. It also advocates for adoption of climate scenario analysis across four levels, which start with using fully narrative scenarios to identify key pathways and continue with quantifying the financial impact of scenarios using quantified or model-driven scenarios, refining the analysis, and integrating the output of climate scenario analysis into decision-making. “The report espouses a holistic approach to climate scenario analysis designed to improve financial decision-making and infuse planning with resilience,” write co-authors James Edwards, executive director for climate risk research at MSCI Research and an Institute fellow for the climate scenario landscape, Nathan Faigle of MSCI Research, and Wenmin Li, an associate for climate risk with the United Nations Environment Programme Finance Initiative (UNEP FI). The authors consider the use of climate scenarios in specific applications, including internal stress testing for both prudential supervision and regulation, and uses of scenario analysis to fulfill disclosure obligations. They further consider scenario analysis in the context of stress testing for investment activities, as well as for risk management and engagement. The report complements work by the Institute and MSCI’s Climate Risk Center to develop a climate scenario informed by market participants’ consensus expectations on how the risks of a changing climate and the transition to a low- carbon economy could impact their investments. “By organizing these scenarios based on their complexity and offering a roadmap for integrating them into investment decision-making, the paper can help stakeholders make informed choices,” notes David Carlin, former head of risk at the UNEP FI, in a foreword to the report. You can find the full report here: https://lnkd.in/dq49hz7V

How do private equity firms measure climate risk? With trillions at stake in the energy transition, investors need hard data—not guesswork. Working with Risilience, Adams Street Partners has produced their latest Task Force on Climate-Related Financial Disclosures (TCFD) report. In this report, Adams Street Partners show how private equity can quantify and manage climate-related risks over time. 𝗞𝗲𝘆 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 𝗿𝗲𝗽𝗼𝗿𝘁: ✔ 52% of active managers now integrate climate risks in investment decisions (up from 46% last year). ✔ 10-year exposure under the Paris Ambition (1.5°C) scenario represents less than 5.5% earnings value at risk. ✔ Less than 1% portfolio exposure to oil, gas, and consumable fuels—reflecting a low-carbon investment strategy. ✔ Increase the number of managers that set net-zero targets for their portfolio. 𝗧𝗵𝗲 𝗽𝗼𝘄𝗲𝗿 𝗼𝗳 𝗰𝗹𝗶𝗺𝗮𝘁𝗲 𝗿𝗶𝘀𝗸 𝗺𝗼𝗱𝗲𝗹𝗹𝗶𝗻𝗴 Adams Street partnered with Risilience, to conduct climate scenario analysis using its Earnings Value at Risk (EVTR) model. 🔹 25,000+ companies assessed to benchmark emissions pathways 🔹 Four climate scenarios modelled—from current policies (3°C warming) to Paris Ambition (1.5°C) 🔹 Market, policy, and technology risks quantified for a 5- and 10-year investment horizon My take: Climate risk isn’t just a compliance exercise—it’s about resilience and opportunity. With scenario modelling, investors can quantify risks, adapt portfolios, and capture the upside of the net-zero transition. 🔹 Is your organisation integrating climate risk modelling into investment decisions? Download the full report here: https://lnkd.in/eExXwqaw __________ For updates on sustainability, climate, and innovation follow me on LinkedIn: http://bit.ly/4fPYlqz.

One of the biggest criticisms we hear about climate scenario analysis is that it is not decision-useful. The scenarios used often miss key factors, understate tail risk and ignore tipping points, creating long-term uncertainty that is too large to make any meaningful decisions.   The BoE has today published a bulletin exploring how financial institutions can use scenario analysis to quantify climate change risks. The bulletin is clear on this point, noting that standard climate scenarios “generally do not provide the level of detail end users need to undertake asset-level financial risk analysis”; however it offers that the solution lies with the end-users of scenarios, and encourages firms to extend scenarios to improve spatial granularity and resolution for physical risks, derive and interpret relevant related variables, determine the extent to which long-term risks are likely to be “priced in” to asset prices over time and understand the interconnectedness of different sectors in the economy.   The key requirement of this solution is data. For one of the BoE’s examples, residential mortgages, this means: Data on individual assets (for example, using Energy Performance Certificates (EPC) ratings to assess the impacts of an aggregate energy price shock on individual households). Data on macroeconomic variables (household disposable income, default rates, household debt-solvency ratios). Data on macroclimate variables (granular flood-risk data and other risks outside the UK).   Scenario analysis can be powerful, even when it has limitations. Any refinement to the scenario and reduction to the limitations only makes it more powerful, and it is fair to conclude that investing in improved data capture and sourcing will be a key step for many firms. In any case, to be decision-useful is sometimes about helping users keep in mind the limitations in models alongside the results, adhering to the "all models are wrong, some are useful" maxim. https://lnkd.in/evbyk3PU