Challenges of Auditing Climate Change Data

Insightful💡 "They are supposed to be the climate-savers’ gold standard — the key data on which the world relies in its efforts to lower greenhouse gas emissions and hold global warming in check. But the national inventories of emissions supplied to the United Nations climate convention (UNFCCC) by most countries are anything but reliable, according to a growing body of research. The data supplied to the UNFCCC, and published(1) on its website, are typically out of date, inconsistent, and incomplete. For most countries, “I would not put much value, if any, on the submissions,” says Glen Peters of the Centre for International Climate Research in Norway, a longtime analyst of emissions trends. The data from large emitters is as much open to questions as that from smaller and less industrialised nations. In China, the uncertainties around its carbon dioxide emissions from burning coal are larger than the total emissions of many major industrial countries. And companies preparing data for its carbon-trading system have been accused of widespread data fraud. In the United States, an analysis published(2) this month of the air over the country’s oil and natural gas fields found that they emit three times more methane — a gas responsible for a third of current warming — than the government has reported." 1) https://lnkd.in/e-qhZ9nS 2) https://lnkd.in/eKcNgGim Read more https://lnkd.in/exAHHXEE #future #sustainability #climatechange #emissions #data #climateaction #climategoals #unitednations

Physical climate risk data: the more we learn, the less we know? Khalid Azizuddin's recent piece in *Responsible Investor captures well what many practitioners are grappling with today: - asset-level data that remain incomplete or hard to interpret; - physical hazard exposure often disconnected from financial materiality; - little visibility on supply chains or customers; - adaptation and resilience efforts largely ignored; - and a risk of over-simplifying complex realities into a single “score.” Some three years ago, EDHEC Business School set out to address exactly these challenges, working to advance climate risk modelling and make decision-useful for investors, companies, and public authorities. In this work, we have developed: 🔹 a blueprint for a new generation of probabilistic climate scenarios; 🔹 high-resolution geospatial modeling capabilities to allow for geographic and sectoral downscaling, consistent with each scenario; 🔹 an open database of decarbonisation and resilience technologies through the #ClimaTech project, which officially launched this week. While the research is public, the new EDHEC Climate Institute has also been assisting a school-backed venture, Scientific Climate Ratings (SCR), which integrates this research to deliver forward-looking quantification of the #financialmateriality of climate risks for infrastructure companies and investors worldwide. While SCR provides a rating scale for comparability, it avoids the trap of over-simplification. Each rating is backed by probabilistic scenario modelling, analysis of physical and transition risk exposures, and explicit accounting for adaptation measures. The result is a synthesis that remains transparent, interpretable, and anchored in scientific rigour. Together, these initiatives aim to move the discussion from data abundance to decision relevance, equipping practitioners with tools that connect climate science, finance, and strategy.

Can we truly trust #carboncredit validation when auditors are paid by those they audit? #Carbonmarkets rely on third-party auditors to verify emission reductions - but the current model, where project developers hire and pay these auditors, creates a serious conflict of interest. Auditors must assess subjective factors like: (1) #Additionality - would the project have happened anyway? (2) #Leakage - are emissions simply shifting elsewhere? (3) #Permanence - will the impact truly last? These are complex, often qualitative judgments - and when an auditor’s paycheck depends on developer satisfaction, the risk of bias is real. 64% of Verra-certified auditors have been linked to projects with over-credited claims. It's time to rethink the system. (1) Create a global pool of independent auditors (2) Decouple verification from developer influence (3) Prioritize transparency and scientific rigor Credible carbon markets demand credible oversight. Without that, climate action loses trust - and impact. #CarbonMarkets #ClimateIntegrity #Sustainability #ClimateFinance #NetZero #CarbonCredits #ESG #Governance #Transparency #ClimateAction https://lnkd.in/dSNGncR9

CFOs and Greenwashing: A Love-Hate Relationship?" It’s 2024, and sustainability reporting has moved from “nice-to-have” to “must-have.” But here’s the twist: over half of CFOs are terrified of greenwashing. They’re caught between the push for transparency and the fear of making the wrong claims – and it turns out, achieving accurate sustainability reporting isn’t as clear-cut as balancing the books. According to a recent EY survey, CFOs are facing some big challenges when it comes to sustainability data: Data Dilemmas: Unlike traditional financials, sustainability metrics are messy. From inconsistent measurements to a lack of standardization, capturing reliable data feels like trying to build a puzzle without all the pieces. Complex Supply Chains: With global suppliers, tracking carbon emissions, water usage, or waste output is no small feat. And let’s face it, not every supplier is as transparent as we’d hope. Getting accurate data across borders is tricky business. Evolving Standards: Just when you think you’ve cracked the code, a new reporting framework or standard pops up. These moving targets make it hard to commit to any one set of numbers, and CFOs are rightfully concerned about promising too much (and being held to it). But here’s the kicker. It’s not just about frameworks and data – it’s about people. Many companies are jumping on the sustainability bandwagon, but without the right skills or experience in-house, it’s hard to navigate this complex terrain. Certification is a good start, but experience matters more. When sustainability teams lack the practical know-how, the management team becomes more conservative, cautious, and sometimes even silent. This is where “greenhushing” – the practice of under-reporting sustainability efforts to avoid scrutiny – comes in. If companies don’t have the confidence in their data or the right people managing it, they end up saying less for fear of overpromising. This silence may feel safer, but it also stifles progress and accountability. So, what’s the solution? Hire the right sustainability professionals – those with a balance of certification and hands-on experience. Build robust data systems, embrace clear standards, and support transparency. Because credibility in sustainability reporting is built over time – one accurate, honest report at a time. Is your organization facing these challenges? Are you investing in the right skills to back your sustainability goals? Let’s discuss how companies can create sustainable, transparent, and credible paths forward. #Sustainability #Greenwashing #Greenhushing #ESG #Finance #SustainabilitySkills

Scope 3 emissions calculations in one sheet. For many of us in the decarbonization space, Scope 3 represents the “iceberg” of our carbon inventory—often the largest portion of emissions, yet the most difficult to see clearly. Achieving a credible Net Zero pathway requires moving beyond high-level screening estimates toward granular, auditable data. The standard is clear: we must adhere to the principles of Relevance, Completeness, Accuracy, Consistency, and Transparency. Whether you are looking at Upstream Logistics or Downstream Leased Assets, the fundamental relationship remains the same: GHG = Activity Data × Emission Factor Following is a technical breakdown of how we apply this across the value chain: 1️⃣ The Data Hierarchy Matters The biggest pitfall in Scope 3 is relying too heavily on spend-based data (Input-Output models). While useful for screening, the goal is Supplier-Specific Data. Spend-Based: Value ($) × EEIO Factor (High Uncertainty) Supplier-Specific: Units × Supplier Product EF (High Accuracy) 2️⃣ Upstream Complexity (Categories 1–8) Purchased Goods (Cat 1): This is usually the heavyweight. Moving from average data to supplier-specific cradle-to-gate inventories is critical here. Capital Goods (Cat 2): Remember, we account for these in the year of acquisition. No amortization allowed for GHG accounting. Waste (Cat 5): Specificity wins. Differentiating between landfill, incineration, and recycling factors changes the footprint drastically. 3️⃣ Downstream Impact (Categories 9–15) Use of Sold Products (Cat 11): For manufacturers of energy-consuming goods, this is often the dominant category. The calculation must account for the lifetime expected energy use, not just a single year. Investments (Cat 15): For financial institutions, this is the inventory. The methodology requires allocating the investee’s Scope 1 & 2 emissions based on equity share or debt valuation. 4️⃣ The “Missing” Gases A complete inventory isn’t just CO₂. We must aggregate all Kyoto Protocol gases (CH₄, N₂O, HFCs, etc.) using 100-year GWP to reach a true CO₂e figure. Scope 3 is not an estimation exercise; it is a data acquisition challenge. The companies that succeed in decarbonizing their value chain are those that treat carbon data with the same rigor as financial data. #Decarbonization #Scope3 #GHGProtocol #Sustainability #NetZero #ISO14064 #EnergyManagement #CarbonAccounting

𝗝𝘂𝘀𝘁 𝗥𝗲𝗹𝗲𝗮𝘀𝗲𝗱: 𝗨𝗡𝗘𝗣 𝗙𝗜 & 𝗚𝗹𝗼𝗯𝗮𝗹 𝗖𝗿𝗲𝗱𝗶𝘁 𝗗𝗮𝘁𝗮 𝗦𝘂𝗿𝘃𝗲𝘆 𝘀𝗵𝗼𝘄𝘀 𝗰𝗹𝗶𝗺𝗮𝘁𝗲 𝗿𝗶𝘀𝗸 𝗶𝘀 𝗰𝗿𝗲𝗱𝗶𝘁 𝗿𝗶𝘀𝗸. 𝗕𝗮𝗻𝗸𝘀 𝗮𝗿𝗲 𝘀𝘁𝗶𝗹𝗹 𝗻𝗼𝘁 𝗱𝗼𝗶𝗻𝗴 𝗲𝗻𝗼𝘂𝗴𝗵. Regulators have raised the bar for climate disclosure, but banks are still a long way from embedding climate risks into their business. 🔸  Collateral value adjustment remains low. Just 12% of banks adjust collateral for physical risk, and only 4% for transition risk. 🔸  ESG integration is fragmented. Over half of banks have internal ESG scoring, but there's no consensus. Few banks tie ESG directly into credit decisions, methods vary and full integration into ratings is rare. 🔸  Scenario analysis is widespread, but validation is not. 85% of banks use NGFS climate scenarios, but fewer than 5% regularly backtest climate impacts in credit models. 🔸  Incorporating climate into key credit metrics is lagging. Metrics like Probability of Default (PD), Loss Given Default (LGD) and Internal ratings-based (IRB) models remain inconsistently or only partially integrated with climate risk considerations. 🔸  Adjustments to ECL (Expected Credit Loss), RWA (Risk-Weighted Assets) and Economic Capital remain low and still in early, exploratory stages. Most banks report financial impact for climate risks between 0-2.5%. For transition risks, this increases to 5-10% but this is not reflected in key metrics. There remains a significant gap in quantification and adoption for capital impact. 🔸 Many banks still rely on expert judgement over data-driven models. While climate risk is assessed across major portfolios, most banks depend on judgement, due to data and methodological constraints. 🔸 Data quality & granularity are key obstacles. Obstacles to robust, forward-looking climate data (especially Scope 3) push banks toward proxies and general averages. 𝗠𝘆 𝗧𝗮𝗸𝗲 The UNEP report shows the banking sector still struggles to consistently quantify and integrate climate risk in credit portfolios, capital models, and client processes. Most banks remain reliant on expert judgment and qualitative overlays, mainly due to the lack of granular, forward-looking data and practical scenario analytics. Scenario analysis exists but is rarely deeply embedded in major decisions, and backtesting is the exception. This is where data-driven platforms are critical. Delivering granular scenario analysis, data harmonisation, and dynamic simulation enables banks to move beyond overlays to defensible, auditable climate risk insights. The leaders will be the banks who industrialise scenario analytics and make regulatory pressure a driver of real competitive advantage. #ClimateRisk #CreditRisk #Banking #ESG #RiskManagement #SustainableFinance Source: https://lnkd.in/eC4S8mRN ___________ 𝘛𝘩𝘦𝘴𝘦 𝘷𝘪𝘦𝘸𝘴 𝘢𝘳𝘦 𝘮𝘺 𝘰𝘸𝘯. 𝘍𝘰𝘭𝘭𝘰𝘸 𝘮𝘦 𝘰𝘯 𝘓𝘪𝘯𝘬𝘦𝘥𝘐𝘯: Scott Kelly

Did you know that weak measurement and verification systems can undermine the credibility of entire sustainability and climate programs? Recent analysis by Senken of more than 2,300 carbon projects found that in some categories, fewer than 16% of issued carbon credits corresponded to real emission reductions, highlighting the risks of inadequate monitoring and verification systems. At the same time, global climate finance and carbon markets depend on rigorous Measurement, Reporting, and Verification (MRV) processes; because one verified carbon credit represents one tonne of greenhouse gas emissions reduced or removed, a unit that governments, investors, and institutions rely on to track real progress. These numbers reinforce a simple but critical lesson: credibility in sustainability is built on systems, not promises. In practice, this means investing in robust monitoring frameworks, conducting independent compliance audits, and ensuring that data can withstand scrutiny from regulators, financiers, and stakeholders. Organizations that prioritize these systems are not only better prepared for evolving disclosure requirements, they are also better positioned to attract investment, manage risk, and deliver measurable impact. As sustainability expectations continue to rise globally, the institutions that will lead are those that understand that accountability is not an administrative requirement; it is a strategic asset. Because in sustainability and climate action, what gets measured, verified, and audited is what ultimately builds trust and delivers lasting results.