This chapter provides an overview of how the degree of alignment of finance with climate policy goals – primarily those of the Paris Agreement – is currently assessed. It explains the scope, dimensions and assumptions that underpin such assessments at the level of financial assets, portfolios, and institutions. The chapter further reflects on different complementary metrics that are being proposed, the methodological approaches behind such metrics, as well as different data and information needs and remaining gaps. It highlights where further efforts are needed on methods, metric, and data, including to address remaining greenwashing risks and strengthen environmental integrity.
OECD Review on Aligning Finance with Climate Goals
Assessing Progress to Net Zero and Preventing Greenwashing
Green Finance and Investment
Abstract
To assess progress in aligning finance with climate goals (Chapter 3) and inform the development of more effective policies and actions (Chapter 4), credible and interoperable metrics need to be further developed. Since the adoption of the Paris Agreement, significant progress has been made in this area, notably in relation to climate mitigation alignment assessments, but greenwashing risks remain due to a lack of comparability and transparency of underlying methodologies as well as coverage gaps.
Financial flows and stocks could be considered aligned with the Paris Agreement if they support socio‑economic systems that are consistent with low‑greenhouse gas emissions and climate-resilient development pathways. This involves scaling up finance for activities contributing to climate goals (including climate solutions and transition activities) and redirecting finance away from activities undermining climate mitigation and resilience goals. There is not yet a common agreed‑upon framework to track progress towards climate alignment of finance.
A range of complex methodological choices and assumptions influence the results of climate‑alignment assessments of finance. Assessments can be based on different metrics, temporal perspectives, activity scopes, scenarios, and aggregation approaches among other dimensions. For example, the inclusion of offsets in corporate‑related alignment assessments can be a strong driver of alignment results but should be treated with caution due to opacity and additionality concerns. Where methodologies and assumptions are not transparent enough, this can lead to greenwashing, as preferred results can be cherry-picked.
Climate‑alignment assessments of finance notably require the selection of a benchmark, such as climate scenarios. For such assessments, granular data on investment and financing needs to be matched with climate‑related characteristics of underlying assets, and compared against climate policy goals. Climate change mitigation scenarios enable such comparisons. However, care should be taken to select scenarios that can be considered aligned with the Paris Agreement, and transparency should be ensured when downscaling global scenarios to sectors and jurisdictions, which requires further assumptions, notably about burden sharing. Relevant benchmarks for climate change resilience remain very scarce.
While data and methodologies have improved, comprehensive climate‑alignment assessments for mitigation are not yet possible for all layers of finance and remain exploratory for climate resilience. Methodologies and data are not yet mature for several large asset classes, such as private equity and loans. Blind spots could hide large amounts of financing continuing to go to climate‑misaligned activities, raising greenwashing concerns. Such concerns increase further when attempting to aggregate asset‑level alignment assessments at the level of financial portfolios, institutions, and financial jurisdictions.
Different metrics and methodologies, based on complementary perspectives, provide a more holistic and nuanced assessment of the climate alignment of finance. Taking the example of alignment assessments at the level of financial institutions, emissions‑related metrics need to be complemented with metrics reflecting portfolio composition practices, including investments in climate solutions and GHG‑intensive assets, as well as more qualitative information about engagement, strategy, and governance.
Compared with climate change mitigation, conceptual and data gaps to assess the alignment of finance with climate‑resilient development remain much more acute. Initial analyses identify several gaps, particularly in asset‑level data on climate exposure and vulnerability and in the availability of relevant policy goals as reference points.
To assess progress in aligning finance with climate goals (Chapter 3) and inform the development of more effective policies and action (Chapter 4), credible data, methodologies, and metrics are needed. Significant efforts have been made since the adoption of the Paris Agreement to develop such inputs into climate‑alignment assessments, but further work is required towards a more comprehensive and common framework.
As introduced by Jachnik, Mirabile and Dobrinevski (2019[1]) and summarised in Figure 2.1, the scope of Article 2.1c is all‑encompassing. It covers any economic transaction by private and public actors, both domestically and internationally. While approaches to assess the climate alignment of finance can be considered for financing sources by both actors, the focus in this review is on approaches to assess alignment of finance issued or underwritten by private actors.
Assessing progress towards the climate alignment of finance requires analyses across all layers of finance, including real‑economy investments, financial assets, financial institutions, and financial jurisdictions. Climate alignment of financial assets is inherently linked to that of real‑economy assets and investments. More aggregate assessments at the level of financial institutions and jurisdictions are especially policy relevant. Within each of these layers of finance, both financial stocks and flows need to be tracked. Assessments of financial flows and stocks provide complementary and interrelated insights into trends over time, as the accumulation of flows, measured per unit of time, results in stocks, observed at a given point in time (Kreibiehl et al., 2022[2]).
Source: Authors.
At a conceptual level, financial flows and stocks could be considered aligned (or misaligned) with the Paris Agreement mitigation and adaption climate policy goals if they contribute to socio‑economic systems that are consistent (or inconsistent) with low‑greenhouse gas and climate‑resilient development pathways. The notion of climate alignment of finance, hence, not only relates to mobilising and scaling up finance towards activities contributing to climate policy goals, but also progressively driving finance away from activities that undermine such goals.
In practice, the climate alignment of finance to activities contributing to or undermining climate goals is assessed by comparing against one or more reference point(s) reflective of the level of ambition needed to reach climate policy goals and targets (Noels and Jachnik, 2022[3]; Jachnik and Dobrinevski, 2021[4]). For climate change mitigation, such a reference point has mainly taken the form of climate change mitigation scenarios that translate the temperature goal of the Paris Agreement into specific pathways (see more in Section 2.2.1).
Complementing outcome‑based approaches based on climate mitigation scenarios, another practical approach to potentially define alignment is based on activity classifications, such as those provided by some taxonomies (Noels and Jachnik, 2022[3]). In practice, approaches based on activity classifications often explicitly or implicitly build on outcome‑based approaches, e.g., by defining a specific criterion based on a threshold derived from a scenario. However, such approaches may not necessarily make it possible to make comprehensive assessments (e.g., many taxonomies only define activities contributing to climate goals but not those undermining such goals). As such, they underpin some of the partial data points presented in Chapter 3 to take stock of available evidence to assess progress.
Article 2.1c of the Paris Agreement refers to aligning all finance with both a pathway towards low greenhouse gas emissions and climate‑resilient development. So far, efforts have focussed more on assessing alignment with mitigation policy goals. For climate change adaptation, there is much less availability and consensus on the types of reference points that could be used to assess alignment. This remains an area where definitions and concepts will continue to evolve as new reference points and evidence become available. While this chapter reflects such a state of development and thus primarily focuses on climate change mitigation (Section 2.2 at the level of financial assets and Section 2.3 at the level of financial portfolios, institutions, and jurisdictions), its last section (Section 2.4) addresses early developments for climate change resilience. Over time, such assessments could become integrated into one alignment assessment with climate goals. However, current practices treat both mostly separately, as different information is required to make such assessments.
Climate‑alignment assessments are typically developed for specific financial asset classes (listed and private equity, corporate debt, sovereign bonds, real estate, infrastructure) due to differences in underlying asset characteristics and data sources (Noels and Jachnik, 2022[3]). However, existing methodologies assessing the alignment of finance with climate mitigation goals for different asset classes have common dimensions (Institut Louis Bachelier, 2024[5]; Noels and Jachnik, 2022[3]; PAT, 2020[6]). After the selection of the financial asset class coverage, these common dimensions include a selection of climate change mitigation scenario(s), choice of climate performance metric(s), and aggregate alignment analysis (Figure 2.2). Unpacking these different methodological dimensions, as done in the remainder of this chapter, helps enhance understanding of differences in the results of alignment assessments.
The composition of financial portfolios differs greatly depending on the type of investor or financial institution, its mandate, and strategy. A complete coverage of financial asset classes in climate alignment assessment methodologies is, therefore, desirable to avoid hidden pockets of climate‑misaligned finance and set aligned incentives for investment strategies and decisions.
Source: Updated from (Noels and Jachnik, 2022[3]).
Existing climate‑alignment assessment methodologies across financial asset classes have focussed more on listed corporate equity than other asset classes (Table 2.1). In principle, these methodologies can be used for other types of corporate‑related financial assets, such as private equity and corporate bonds and loans. In practice, however, different data and application considerations need to be made. While all asset classes are covered by at least one methodology provider, the lack of more systematic coverage across asset classes shows that such methodologies are still maturing. On that basis, this section reviews approaches for corporate‑related financial assets (Subsection 2.2.2) and sovereign bonds approaches (Subsection 2.2.3).
Climate‑alignment assessments for individual financial assets were originally designed mostly with emissions metrics in mind, as they relate more clearly to the Paris Agreement temperature goal. Some climate‑alignment assessments consider non‑emissions‑based metrics, such as investments in climate solutions (e.g., renewable energy), which can also be compared to reference points tailored for each asset class. Moreover, complementary metrics have been developed to consider progress on concrete actions that can be taken to influence emissions. Such complementary metrics are discussed in the following subsections where relevant, as well as in the context of alignment assessments at the level of financial portfolios and institutions (Section 2.3).
As highlighted by Figure 2.2, the choice of climate change mitigation scenarios is, for any asset class, a critical methodological dimension in climate‑alignment assessments and other climate‑related analysis of finance. This section, therefore, starts with an overview of key considerations of relevance to inform accurate use scenarios for such assessments (Subsection 2.2.1).
Note: Last updated in August 2024. LSEG was formerly included as FTSE, S&P Sustainable1 was formerly Trucost. ESG Book was formerly Arabesque.
Source: Authors, updated from (Noels and Jachnik, 2022[3]) based on publicly‑available information and, for some providers, bilateral consultations.
2.2.1. Using climate change mitigation scenarios as reference points
Climate change mitigation scenarios can serve multiple purposes related to finance and investments. Many climate‑related analyses and metrics in the financial sector rely on such scenarios, both in the context of climate‑related risk assessments and management and for assessing the contribution to and alignment of finance with climate goals. For instance, model-based scenario assessments have been used to quantify the investment needs and the associated reallocation of the investment portfolio to align the energy system with the mitigation actions implied by the Paris Agreement (McCollum et al., 2018[7]). However, as climate‑related assessments and metrics based on scenarios are highly sensitive to the characteristics of such scenarios, their choice and use needs to be made with care to avoid unintended incentives, maximise environmental integrity, and minimise greenwashing risks.
Several conditions are important to enhance the relevance, applicability, and use of scenarios in finance. This section provides a succinct update on the analysis done by Noels et al. (2023[8]), which analysed common practices and gaps of scenarios commonly used in the financial sector, which stem from the International Energy Agency (IEA), the Network for Greening the Financial System (NGFS), the Institute for Sustainable Futures of the University of Technology of Sydney (ISF‑UTS), and the European Commission Joint Research Centre (JRC). The dimensions analysed and summarised below relate to: (1) the degree of consistency of climate mitigation scenarios with the Paris Agreement’s long‑term temperature goal and emission reduction objective; (2) their applicability for use in the financial sector, notably in terms of sectoral and geographical granularity; and (3) the characteristics of mitigation strategies and input assumptions, including in relation to feasibility and uncertainty. After selecting an ambitious, fit-for-purpose scenario(s) with certain characteristics, it needs to be downscaled to the financial asset level.
Selecting climate change mitigation scenarios consistent with the Paris Agreement
To ensure environmental integrity, climate change mitigation scenarios used in financial sector alignment assessment must be consistent with the Paris Agreement temperature goal and long‑term emissions objective. The formulations of this goal and objective are, however, not specific enough to define emissions levels or benchmarks as such and, thus, leave room for a range of interpretations, pathways, and underlying scenarios (Schleussner et al., 2022[9]). Against this backdrop, Pouille et al. (2023[10]) provide a set of criteria to assess the Paris consistency of scenarios’ level of ambition:
To be in line with the Paris Agreement’s Article 2.1 long‑term temperature target scenarios must remain below 1.5°C by 2100 with limited overshoot (<0.1°C), with 50% chance and remain well‑below 2°C throughout the century (i.e., have very high likelihoods of not exceeding 2°C).
In addition, to be in line with Article 4 of the Paris Agreement, scenarios must see an early peak in GHG emissions and reach net‑zero GHG emissions in the second half of the century. A higher level of stringency filters scenarios that peak at the latest in 2025 and achieve net‑zero GHG emissions in the second half of the century, and a lower level of stringency filters those scenarios that peak at the latest in 2030 and achieve close to net‑zero GHG emissions in the second half of the century.
Table 2.2 summarises the extent to which scenarios commonly used in the financial sector are consistent with these criteria. For each criterion, a scenario is assessed as consistent with either the stringent application (dark blue) or less stringent application (light blue), or as not consistent (purple). Out of the nine scenarios considered (based on their most recent available version), three are fully consistent with all temperature and emissions criteria (black rectangles). The criterion that is least complied with across all scenarios is the limitation of temperature overshoots of 1.5°C over the century. However, the updated results displayed in Table 2.2 compared to Noels et al. (2023[8]) make it possible to observe that the most recent versions of the scenarios are more consistent than their previous iterations.
Note 1: The black boxes indicate the scenarios that are consistent with the less stringent interpretation of the Paris Agreement.
Note 2: IEA NZE is the International Energy Agency Net Zero Emissions by 2050 Scenario. JRC GECO 1.5°C is the EU’s Joint Research Centre GECO 1.5°C scenario. NGFS4 NZE 2050 is Network for Greening the Financial System Net Zero 2050. NGFS4 LD is Network for Greening the Financial System Low Demand. UTS‑ISF NZE is University of Sydney Institute for Sustainable Futures Net Zero. G, M, and R are three different models through which the scenarios are run, respectively GCAM, MESSAGE, REMIND.
Source: Authors’, updated in August 2024 from (Noels et al., 2023[8]).
Table 2.2, however, also shows that several scenarios do not provide sufficient information to allow for a full assessment of their Paris consistency (grey boxes). This is in particular the case for features of GHG emissions pathways (early peak and net zero in the second half of the century), which are an important aspect of the Paris Agreement’s emissions objectives in Article 4.1. It is also challenging to assess whether scenarios keep temperatures well below 2°C throughout the century, as this requires information on temperature outcomes at several levels of likelihoods, rather than the median outcome only.
Matching the granularity and scope of financial assets with that of scenarios
After identifying the degree of Paris consistency of scenarios at an aggregate level, understanding whether scenarios are fit‑for‑purpose to be used in climate‑alignment assessments of finance requires looking at their applicability. This depends on the scopes and granularity of the models behind the climate scenarios with respect to sectoral, geographical, emissions, and temporal dimensions. Where the scenarios’ scope and granularity are insufficient for assessments at the level of financial assets or asset classes, further methodological assumptions need to be made (Noels and Jachnik, 2022[3]). Notably, providers of target setting and alignment assessment methodologies have developed several techniques to downscale scenarios, primarily to the company‑level for corporate‑related assessments (Subsection 2.2.2), but increasingly so as well to country‑level for assessments of sovereign bonds (Subsection 2.2.3).
The selected models have broadly similar sectoral granularity for emissions pathways and in particular more details for energy supply than for, e.g., industry (IPCC, 2022[11]). In practical terms, however, alignment assessments must address a mismatch between sectoral classifications used in the financial sector and by scenario providers. The nature of activities and actors that underpin financial assets is better characterised by granular (4‑digit) sub‑sectors, typically based on international sectoral classifications (e.g., ISIC, NACE, NAICS, GICS) also used for corporate and financial accounting purposes (Noels and Jachnik, 2022[3]). However, climate change mitigation scenarios rely on sector classifications defined for tracking GHG emissions, such as the IPCC classification (Battiston et al., 2022[12]; Teske, 2022[13]).
Different scenario providers model and disclose pathways for different regions and countries (Figure 2.3). These pathways are also not directly comparable due to different coverage of emissions sources and assumptions. Most scenario providers model national pathways for a handful of large countries, such as the US and China. However, few provide such pathways for a wide range of countries. National pathways for developing countries may differ more from one scenario to the other as illustrated for South Africa in Figure 2.3, possibly reflecting larger uncertainty in the underlying data on which it is build.
For the scenarios in scope, models differ in their temporal scope in terms of start and end year and intermediate data points. Some only have data until 2050 while others do so until 2100. A long‑term horizon is needed to identify short‑, medium‑, and long‑term changes consistent with a long‑term climate objective (UNEP FI & CICERO, 2021[14]). However, the further into the future, the more uncertainty there is around a given datapoint. Further, most models have a modelling start year at or before 2010, meaning that recent years are already projections from an earlier point in time. Only the UTS‑ISF OECM model has a more recent start date, meaning it includes more recent information on emissions‑relevant variables.
Note: Emissions pathways cover energy‑related CO2 emissions.
Source: Authors’, updated in August 2024 from (Noels et al., 2023[8]).
Characteristics of mitigation strategies and assumptions of climate mitigation scenarios
Different climate change mitigation scenarios used in financial sector alignment assessments rely on various combinations of key mitigation options to achieve a given level of ambition (Figure 2.4). As points of comparison, Figure 2.4 also displays four Illustrative Mitigation Pathways used by the IPCC, each focussing on different mitigation options. By gaining insights into the mitigation options that underpin the scenarios they rely on, financial institutions can identify potential inconsistencies with their own transition plans and strategies. Understanding the plausibility of scenarios and sensitivities of scenario assumptions can help enhance engagement with investees toward achieving climate targets. Such information can also inform investment priorities.
Overall, all scenarios that achieve stringent climate goals imply rapid scale‑up and large‑scale deployment of new technologies and mitigation options, with trade‑offs between the different options (Noels et al., 2023[8]). Decarbonising the energy supply is a first essential aspect of all mitigation scenarios that limit global warming. All scenarios considered here see a significant decrease in fossil fuel energy supply and large increases in renewable energy sources (Figure 2.4, Panel A). Some scenarios maintain a higher reliance on fossil fuels combined with a large deployment of CCS technologies (Figure 2.4, Panel B).
Note: The right‑hand side part of the figure represents four Illustrative Mitigation Pathways used by the IPCC, with three of them allowing to keep temperatures below 1.5°C with limited overshoot (IMP Ren, IMP LD, IMP SP).
Source: Authors’, updated in August 2024 from (Noels et al., 2023[8]).
Other mitigation levers include demand‑side mitigation levers, carbon dioxide removals1 (CDR), and agricultural and land use emissions reductions. The latter is, however, not considered by all selected scenarios as most models used in the considered scenarios do not cover the agricultural and land use sector. Demand‑side mitigation levers are relied upon in all scenarios considered here. These include gains in energy efficiency as well as electrification of energy use across sectors (including transportation, industry, and buildings), and for some models, other demand‑side interventions leading to behavioural and lifestyle changes and reduced energy demand.
CDR is a mitigation strategy most scenarios assessed in the IPCC AR6 rely on to reach stringent mitigation goals. All the scenarios commonly used in finance studies here show a limited reliance on CDR in the first part of the century (0‑7Gt in 2050), but some scenarios largely rely on negative emissions thereafter, as is the case for GECO and NGFS delayed transition scenarios. Negative emissions achieved through CDR allow reaching long‑term net negative emissions to ensure a long‑term decline in temperatures (Riahi et al., 2022[15]), but scenarios that achieve stringent temperature limits highlight that CDR deployment can compensate for residual emissions in hard‑to‑abate sectors but not replace substantial emissions reductions in all sectors.
Downscaling scenarios to the level of economic and financial assets
To assess the alignment of a financial asset, the chosen scenario needs to be allocated, or scaled down, to the appropriate level of that of the underlying economic entity. Doing so requires assumptions on burden sharing, i.e., the absolute or relative share and speed of emission reductions assigned to the entity. Depending on the financial asset class, such assumptions need to relate to geographical downscaling and/or sector‑specific considerations. There are a few existing approaches to compare entities to sector‑level scenarios or to explicitly allocate macro scenarios to entities (Institut Louis Bachelier et al., 2020[16]; Schwegler et al., 2022[17]; SBTi, 2021[18]).
In the contraction approach (Figure 2.5, Panel A), an entity is considered aligned if it reduces emissions at the same speed as the scenario (at the relevant sectoral and geographical granularity). In this case, a fixed reduction rate is set for absolute emissions or carbon intensities for all entities in each sector and or region.
In the convergence approach (Figure 2.5, Panel B), an entity is considered aligned if it converges towards the (sectoral and/or geographically relevant) scenario by a given point in time. In this case, every entity in each sector/geography needs to achieve the same climate performance, typically in intensity‑based terms, at that point in time. Hence, entities that are already performing well must improve relatively less to be aligned.
In the fair share approach (Figure 2.5, Panel C), an entity-specific carbon budget or scenario is allocated to each entity based on chosen criteria. The market share criterion (by revenue, production, or capacity for example) implies that two entities in the same sector/geography with the same market share receive the same carbon budgets while having different emissions profiles. The historic responsibility criterion distributes the remaining sectoral budget based on historic contributions, which implies for instance that entities having emitted below the budget level in the past may temporarily surpass the budget in the future. The economic efficiency criterion distributes the sectoral scenario based on relative least cost or efficiency (the need for entity‑level data on abatement costs makes this approach challenging).
Most climate‑alignment assessment methodologies for corporate equity and bonds follow a convergence approach (Noels and Jachnik, 2022[3]). On that basis, companies that are currently more emissions‑intensive will need to reduce emissions faster than companies that are already closer to the scenario. The convergence approach may be best suited for large companies with global operations where activities may be less clearly linked to specific countries. On the other hand, a contraction approach is common for absolute emissions‑based metrics, where companies need to reduce emissions at the same rate, regardless of their current and past emissions. However, companies may have different abatement cost curves, investment capacities, and access to financing, especially in developing countries, which could call for a differentiated approach.
The challenges relating to using downscaled scenarios and considering fair shares are particularly pertinent for sovereigns. Geographic variations among countries imply a need to incorporate equity considerations when assessing the alignment of sovereign bond portfolios, given different countries decarbonise at different rates (Noels et al., 2023[8]). While some scenarios include fair share considerations to some degree, some providers make additional changes to reflect this. For example, TPI’s ASCOR framework includes fair share considerations by relaxing certain indicator thresholds depending on the development status of a country (ASCOR, 2023[19]).
Note: GHG emissions performance could be in terms of absolute emissions (e.g., tCO2e) or emissions intensity (e.g., tCO2e per ton of steel). Contraction approach is typically used for absolute‑based metrics, convergence for intensity‑based metrics.
Source: Authors, adapted from (Schwegler et al., 2022[17]).
2.2.2. Alignment and complementary metrics for corporate‑related financial assets
At an aggregate level, existing climate‑alignment assessments of finance for corporate‑related financial assets find a high degree of misalignment (as shown in Chapter 3 Subsection 3.2.2). At the financial asset level, however, Table 2.3 indicates that results frequently differ across assessment providers for the same asset. Indeed, a company assessed as aligned with a 1.5 degrees scenario by one provider can be assessed as not aligned by others. These divergences can be explained by differences in methodology and scope across the dimensions introduced in Figure 2.2, notably, as discussed in the previous section, in terms of choice and use of a climate mitigation scenario. Most providers also run into some data availability issues, but clear progress has been made compared to a previous stocktake (Noels and Jachnik, 2022[3]). Hence, even for listed corporate equity, where methodologies are more available, there is a continued need for increased transparency and comparability. Currently, the correlation and comparability among assessments for the same company are low.
Existing climate‑alignment assessments of corporate listed equities are based on different climate performance metrics. Most rely on GHG emissions performance metrics, although some consider non‑emissions‑based metrics such as capital expenditure plans in certain technologies (Noels and Jachnik, 2022[3]). Different metrics reflect different perspectives, and each has advantages and disadvantages (Table 2.4). For example, absolute emissions contraction metrics can be directly related to the remaining global GHG budget, are simpler, and require less data. However, emissions reductions can be the consequence of a decline in output instead of an improvement in climate performance. To address this concern, intensity‑based metrics are typically considered. Physical intensity metrics reflect emissions performance and efficiency improvements regardless of entity size and growth. On the other hand, data requirements are higher, and comparability between companies with diverse activities may be limited. While all these metrics rely on expanding the currently limited climate data disclosure (see Chapter 4 Subsection 4.2.1), data availability for absolute emissions metrics is better than for intensity metrics.
Note: Results are latest available assessments for alignment in 2050, anonymised for companies and providers. ITR results are assigned to the relevant category as this illustration aims to show the level of alignment and exact temperature results come with a higher level of uncertainty. ‘Not aligned’ means not aligned with a 2 degrees or below scenario as assessed by the methodology provider. ‘Not available’ means either not enough data to apply the methodology or no methodology available for that sector by the provider.
Source: Authors’, updated in August 2024 from an initial version in (Noels and Jachnik, 2022[3]) based on data provided by four selected providers (CDP-WWF, 2024[20]; MSCI, 2024[21]; S&P, 2024[22]; TPI, 2023[23]).
As each metric type comes with pros and cons and provides a complementary perspective, existing climate-alignment methodologies consider one or the other depending on their target audience and, in some cases, use a combination of metrics (Noels and Jachnik, 2022[3]). If providers are transparent about their approach, different assessments can complement each other to have a more comprehensive analysis. However, when providers are not transparent about their metric choice, greenwashing risks arise, including as corporates or financial sector players can cherry‑pick assessment results.
Note: Data needs refers to both needs on corporate GHG emissions data and other corporate output data such as production volumes, value added or financial performance. Data availability is generally higher for listed than unlisted companies.
Source: (Noels and Jachnik, 2022[3]).
The temporal boundary of an alignment assessment, one of the core dimensions introduced in Figure 2.2, significantly influences assessment results (Thomä, Dupré and Hayne, 2018[24]). The three key temporal characteristics of a greenhouse gas performance metric relate to whether it is backward‑ or forward‑looking, whether it considers a short, medium, or long period, and whether the metric is only compared with a scenario at a certain point in time or across a period. Stylised examples in Figure 2.6 illustrate how such characteristics drive alignment results.
Backward‑ and forward‑looking metrics serve different yet complementary purposes. Backward‑looking metrics can be used for an ex‑post assessment of alignment, analysing whether an entity has followed a scenario in the past (Institut Louis Bachelier et al., 2020[16]). Forward‑looking metrics are more dynamic as they aim to assess if an entity is on track to comply with the remaining carbon budget for a certain goal. Metrics based on historical data are not enough on their own to assess climate‑alignment due to non‑linearity, non‑stationarity, path‑dependencies and endogeneity issues that imply that extrapolations of past trends do not provide an accurate benchmark for forward‑looking assessments (Bingler, Colesanti Senni and Monnin, 2021[25]).
In terms of period, 2025, 2030, and 2050 are all important policy milestones towards reaching the Paris Agreement temperature goal. The most recent IPCC assessment indicates 2025 as the year when global emissions should peak, as early action is essential in reducing risks of crossing climate tipping points. Further, global emissions need to reach net‑zero between 2045 and 2055, in order to limit warming to 1.5°C with no or limited overshoot (IPCC, 2022[26]). Methodological recommendations for corporate‑related financial assets are consistent with these considerations. SBTi requires that corporate targets and mitigation performance assessments should cover a minimum of five years and a maximum of 10 years (SBTi, 2021[18]). SBTi further recommends companies set long‑term targets and near‑term milestones at five‑year intervals, thereby combining advanced planning (including for large capital investments) with mid‑ and near‑term‑actions.
In relation to the point of measurement, a comparison of a GHG performance metric with a scenario can happen at a point‑in‑time or over a period. As such, the degree of (mis)alignment will depend on the choice of year (Institut Louis Bachelier et al., 2020[16]). Assessments over time provide a more dynamic and nuanced perspective, highlighting changes in trends and allowing for cumulative analysis of divergence between the entity’s performance and the scenario over the years.
Source: Authors.
The coverage of GHG emissions in climate‑alignment assessment methodologies relates both to the types of GHGs and the scope of emissions covered. Most climate-alignment assessment methodologies consider all types of GHGs and the widest scope possible based on available data.
To understand the full extent of global warming, economic actors should measure and disclose emissions of all types of GHGs, i.e., both GHGs with lifetimes around 100 years or longer, notably CO2 and nitrous oxide, as well as Short‑Lived Climate Forcers, notably methane and some hydrofluorocarbons (IPCC, 2022[26]). Some research further suggests that economic actors should indicate the separate contribution of each type of GHG to total (or CO2‑equivalent) emissions in their targets and measurement of progress (Allen et al., 2022[27]).
In contrast to national GHG accounting, which is based on a territorial approach, corporates account for GHG emissions according to the scope 1, 2 and 3 categorisation2. For corporates, building on the GHG Protocol, the SBTi requires that GHG performance metrics (both historic and targets) cover at least 95% of company‑wide Scope 1 and 2 emissions and account for all relevant Scope 3 emissions (SBTi, 2021[18]) . Scope 3 emissions relate to the responsibility of companies along their value chain, both upstream and downstream. The relevance of Scope 3 emissions depends on the sector and where the company sits within the value chain. Estimates indicate they are especially important in sectors such as oil and gas and car manufacturing, for which they account for most emissions across the three scopes (Hertwich and Wood, 2018[28]).
Climate science and literature treat offsets with caution, in terms of risk of delaying or replacing actual GHG reductions, as well as in relation to their environmental integrity and additionally. Reach net‑zero emissions requires urgent absolute emission reductions (Fankhauser et al., 2021[29]). As highlighted in Subsection 2.2.1, these reductions need to be front‑loaded and to cover all emission sources. This means CDRs should be used cautiously, and the use of carbon offsets should be regulated effectively. There are many questions about the integrity and additionally of offsets. For example, over half of the carbon offsets allocated in the Clean Development Mechanism (CDM), the largest crediting mechanism under the Kyoto Protocol, went to projects that would very likely have been developed anyway, highlighting a lack of additionally (Calel et al., 2021[30]). The sale of offsets in the CDM may in fact have significantly increased global emissions. Moreover, across carbon credit market segments, independent assessments find that a large share of carbon credit supply is currently of low quality (Wetterberg, Ellis and Schneider, 2024[31]).
In this context, the current SBTi standard states that offsets cannot be counted as reductions towards meeting a near‑term target set by corporates (SBTi, 2021[18]). Companies must account for reductions resulting from direct action within their operations or value chains. Moreover, the GHG protocol treats biogenic CO2 (both sequestration, e.g., uptake by forests, and emissions, e.g., burning biomass) as separate from Scope 1, 2 and 3 emissions (World Resources Institute & World Business Council for Sustainable evelopment, 2004[32]).
Avoided emissions are currently defined and understood differently by different communities. For a country, in the context of international carbon markets, avoided emissions refer to activities that avoid potential sources of stored GHG emissions from being emitted to the atmosphere within its territory, such as the nonexploitation of fossil fuel reserves, maintaining land use and agricultural practices that retain already‑stored carbon, and avoided deforestation (Jeudy-Hugo, Lo Re and Falduto, 2021[33]) (see also Subsection 2.2.2). For corporates, avoided emissions typically refer to emissions avoided during the use phase by a company’s customer compared to using a more carbon‑intensive product than the less‑carbon intensive product from the company.
Note: Last updated in August 2024.
Source: Authors, analysis based on publicly‑available information of selected frameworks, including (European Commission, 2023[34]; IPSF, 2022[35]; National Treasury, 2022[36]; Securities and Exchange Commission, 2022[37]; Transition Plan Taskforce, 2023[38]; IFRS ISSB, 2023[39]; SBTi, 2024[40]; CDP, 2024[41]; CA100+, 2024[42]).
In all cases, there are no agreed methods or standards to count counterfactuals and calculate avoided emissions. For corporates, as avoided emissions do not occur during the product’s life cycle inventory, SBTi does not allow them to be included in GHG performance metrics and requires that they are accounted for and reported separately from Scope 1, 2 and 3 emissions, including any Scope 3 metric or target (SBTi, 2021[18]). Further, assumptions regarding avoided emissions are vulnerable to the risk of non-permanence of the underlying activities. In the case of countries for instance, “fossil fuels could be kept in the ground (or deforestation avoided) for the time of the financial support from the sale of international credits, but then extracted (or deforested)” (Jeudy-Hugo, Lo Re and Falduto, 2021[33]).
To provide a more comprehensive and nuanced perspective on progress and actions by corporates towards contributing and aligning their business activities with climate goals, an increasing number of frameworks provide guidance on information points and metrics to be disclosed. For nine such frameworks, issued by either civil society organisations, industry associations, or public authorities in specific jurisdictions, Table 2.5 presents an overview of the respective information and metrics they recommend. These are grouped in four categories: GHG emission metrics (including but not limited to alignment assessments), composition of activities and related financing and investment metrics, engagement metrics, and governance and strategy metrics. Many such frameworks have been developed in the context of incentivising corporates to develop and implement credible transition plans, for which broader guidance has also been developed, e.g., (OECD, 2022[43]).
2.2.3. Alignment and complementary metrics for sovereign bonds
While sovereign bonds represent an important asset class within the portfolios of many investors and financial institutions, fewer climate‑alignment assessment methodologies are available. This is, however, an area of active development. Climate‑alignment assessments of sovereign bonds relate directly to underlying countries. Available assessments of countries for use in the financial sector follow different approaches (Noels and Jachnik, 2022[3]), finding different degrees of alignment (Table 2.6. As for corporate‑related financial asset classes, such variations result from different assumptions and perspectives on methodological dimensions (as outlined in Figure 2.2). When such assumptions and perspectives are transparently disclosed and explained, different assessments may be complementary and, if combined, provide a more holistic assessment (Noels and Jachnik, 2022[3]).
Existing climate‑alignment assessments of sovereign bonds are based on different GHG emissions performance metrics. Similar to corporate‑related financial assets, both absolute and intensity‑based emissions metrics can be considered. Absolute emission levels can be measured from the perspective of the amount produced within a country or the amount consumed by a country. Intensity‑based emissions can be calculated on a per capita or per GDP basis for example. Additionally, changes in emissions trends across various years are also considered for alignment assessments, as they could be compared to changes in emissions pathways over the years.
The temporal boundaries for assessing the climate alignment of sovereign bonds are largely the same as for corporate‑related financial assets. It is possible to take a backward‑ or forward‑looking perspective, a short‑, medium‑, or long‑term horizon, as well as a point estimate or time‑series comparison with a climate change mitigation scenario. Choices of different perspectives can lead to different results, similar to how such perspectives may impact alignment results of corporate‑related assets. For sovereign bonds, existing climate‑alignment assessments consider both historical information and targets. For example, they may calculate emissions gaps between projected emissions under current policies and a stated 2030 target, or between emission pathways of Nationally Determined Contributions (NDCs) and a 1.5°C warming scenario (LSEG, 2024, p. 13[44]). They also tend to have a greater focus on medium‑term timeframes, most commonly publishing results for 2030 (Table 2.6).
Note: ‘Not aligned’ means not aligned with a 2 degrees or below scenario as assessed by the methodology. ‘Not available’ means that the country was assessed by the methodology as having a non‑quantifiable target. Countries and methodology providers are anonymised.
Source: Authors' calculations based on data from selected providers (LSEG, 2021[45]; LSEG, 2023[46]; TPI, 2024[47]) and income group classifications from the World Bank.
Like for corporate asset classes, the complementarities that exist between different perspectives imply the need to rely on a range of indicators for a more holistic and nuanced assessment. Aside from alignment assessment methodologies developed with the financial sector in mind, a range of methodologies have been developed within the climate policy research community to assess the climate performance of countries. These put forward additional metrics, e.g., relating to the adoption of climate policies (also discussed in Chapter 4) or to innovation and infrastructure investments (Table 2.7). Further qualitative information can, for instance, relate to ‘willingness’ measures that examine a country’s commitments and progress towards net zero, such as NDCs and engagement in environmental conventions (Barrahhou, Ferreira and Maalei, 2023[48]).
Note: Last updated in August 2024. GHG: Greenhouse gas. ITR: Implied temperature rise. LSEG: London Stock Exchange Group. ASCOR: Assessing Sovereign Climate‑related Opportunities and Risks. CAT: Climate Action Tracker. CCPI: Climate Change Performance Index. ETI: Energy Transition Index. EPI: Environmental Performance Index. GFI: Green Future Index.
Source: Authors, based on publicly‑available information of data providers, including (LSEG, 2024[49]; LSEG, 2024[50]).
Aggregating results across individual financial assets adds another layer of complexity as it requires weighing the contribution of different assets typically relating to different economic sectors, as well as adjusting for the potential double counting of emissions where relevant (PAT, 2020[6]). These issues become even more complex when considering aggregation across multiple asset classes (e.g., corporate‑related equity and debt, sovereign bonds, real estate, and infrastructure) for which, as outlined in Section 2.2, methodologies and assumptions differ.
Despite these complexities, methodologies to assess the climate alignment of financial assets across asset classes have considered approaches to aggregate assessments to the level of financial portfolios held by investors and financial institutions (Subsection 2.3.1). However, existing methodologies and assessment providers do not tend to aggregate an alignment assessment into a single result at the level of a financial institution or financial jurisdiction yet. Such single aggregate assessment may not be desirable as they could obscure misaligned parts and the range of assumptions and complexities associated with the aim of a silver bullet assessment result.
For financial institutions a range of complementary metrics are being considered to assess progress towards net‑zero commitments (Subsection 2.3.2). Alignment assessment methodologies at the level of financial jurisdictions are still very limited and, therefore, not yet included in the methodological review presented in this chapter. However, Chapter 3 does capture examples of available early estimates of data points relating to investments in activities respectively contributing to and undermining climate goals at the level of financial jurisdictions (Section 3.4) in addition to taking stock of those available at the level of financial institutions (Section 3.3).
2.3.1. Aggregate alignment assessments of financial portfolios
Providers of climate‑alignment assessment methodologies are exploring approaches for aggregate asset‑level assessments (Schwegler et al., 2022[17]; Institut Louis Bachelier et al., 2020[16]; CDP & WWF, 2020[51]; Thomä, Dupré and Hayne, 2018[24]; GFANZ, 2022[52]; PAT, 2020[6]). This primarily includes considering options to weigh the contribution of different assets for a given asset class both within a given economic sector (particularly relevant to inform active engagement strategies), and across different economic sectors (the respective assessment of which typically relies on sector‑specific scenarios and metrics). Approaches to aggregate across multiple asset classes are not yet developed, both because of their significant complexity and given the risks of producing opaque and potentially misleading assessment results.
Currently, there is no clear dominant aggregation approach across climate‑alignment assessment methodology providers for corporates, which use different approaches, sometimes tailored for different users of their methodology (Noels and Jachnik, 2022[3]). Approaches to aggregate alignment assessment results across assets within an asset class include:
The aggregated budget approach: the over‑ or under‑shoot of each asset is summed, either for total emissions of the entity, or the share of those emissions financed by the respective investor. In particular, the latter approach requires a complex comparison of the sum of “owned” projected GHG emissions against the sum of “owned” carbon budgets for the underlying holdings.
The weighted average approach: the asset‑level alignment metrics (e.g., Implied Temperature Rise metric) are weighted based on the relative weight of each entity in the portfolio. This weight can either be defined by the ownership stake of a financial institution for equity portfolios or the relative residual value of bond holdings for bond portfolios.
The portfolio‑owned approach: it combines the first and second approach by weighing asset‑level alignment metrics by their respective proportion of the entity’s emissions financed by the investor.
International‑level collective assessment of progress against remaining global carbon budgets and towards the Paris Agreement temperature goal requires minimising double counting of GHG emission reductions and avoidance across actors, including investors and financial institutions. Within the investment and financial value chain, double counting of emissions can occur at multiple levels, namely between financial institutions co‑financing the same entity or activity, between transactions within the same financial institutions, across different asset classes, as well as within the same asset class (PCAF, 2020[53]). Double‑counting is problematic for portfolio‑level assessments of climate alignment if GHG emissions that are counted more than once are interpreted as actual total emissions into the atmosphere, or if the double‑counting distorts the alignment assessment result (Schwegler et al., 2022[17]). Approaches to adjust for double counting are still in the early stages of development (Portfolio Alignment Team, 2020[54]) and most methodologies, while acknowledging the need to address the issue, do not currently explicitly clarify whether and how they do so (Noels and Jachnik, 2022[3]).
2.3.2. Complementary metrics to assess financial institutions’ progress to net‑zero emissions
As highlighted in the previous subsection, a single alignment metric at the level of a financial institution is methodologically challenging to produce and likely to result in opaque and misleading results. Rather, assessing the climate consistency of financial institutions, including tracking progress towards their net‑zero commitments, requires a clear set of complementary, credible, and comparable metrics (OECD, 2023[55]). Doing so can build on the increasing availability of a range of metrics at the level of individual asset classes, as highlighted by Table 2.5 for corporates and Table 2.7 for sovereigns.
Voluntary financial sector initiatives have attracted significant participation by financial institutions globally and influenced their practices to date, as further illustrated by available evidence in Chapter 3 Section 3.3. Such initiatives include the Glasgow Financial Alliance for Net Zero (GFANZ), which also oversees the UN‑convened Net‑Zero Asset Owner Alliance (NZAOA), the International Financial Reporting Standards Foundation’s International Sustainability Standards Board (IFRS ISSB), which integrates the Task Force on Climate‑related Financial Disclosures (TCFD), and the Institutional Investors Group on Climate Change (IIGCC). Voluntary initiatives support actions by market participants and can help develop good practices, as well as contribute to policies and regulations that encourage greater environmental integrity, transparency, and accountability.
These financial sector initiatives have developed frameworks that guide disclosure practices related to climate change actions or outcomes by financial institutions and investors. Their frameworks include the GFANZ Recommendations and Guidance on Financial Institution Net‑Zero Transition Plans, the IFRS ISSB Sustainability Disclosure Standards, IIGCC Net Zero Investment Framework Implementation Guide, the NZAOA Target Setting Protocol, and the TCFD Recommendations. These frameworks have been developed with different audiences and aims in mind, from financial risk management to supporting a shift in investments to contribute to global net‑zero goals. However, several of them cross-reference metrics and methodologies used in others, and build on other frameworks. Many frameworks have been developed with the aim of being living documents that integrate international developments and updates into account.
Guidance by such frameworks on information to be disclosed by financial institutions propose information points and metrics in relation to GHG emissions, portfolio composition, engagement, as well as strategy and governance. The overview of the guidance put forward by the selected frameworks across these four categories, as summarised in Table 2.8, highlights a high amount of information points, i.e., general descriptive disclosure on actions taken by financial institutions as well as on institutional knowledge and practices. In contrast, defining metrics involves specific measures, underpinned by methodological guidance and data requirements, thus leaving less room for different interpretations by a financial institution. Metrics typically measure actions and outcomes by financial institutions, resulting in quantifiable disclosure or measurable qualitative disclosure (e.g., yes, or no related binary data).
GHG emissions information points and metrics serve to capture progress on decarbonisation outcomes, which, in principle, should reflect the impact on real‑economy GHG emissions of input actions in terms of portfolio management, engagement, and strategy. The frameworks largely propose information points and metrics assessed across three sub‑categories, namely (1) historical or current emissions, (2) emission targets, and (3) alignment assessments using a recognised benchmark (including the Paris Agreement temperature goal), discussed in depth in Section 2.2.
Note: M means the framework proposes at least 1 metric, I means the framework proposes at least one point of information but no metric. N means no information or metric is proposed by the frameworks.
Source: (OECD, 2023[55]), based on public reports from GFANZ, (2022[56]), Recommendations and Guidance on Financial Institution Net‑zero Transition Plans; IFRS ISSB, (2023[39]), Sustainability Disclosure Standard: Climate‑related Disclosures; IIGCC, (2021[57]), Net Zero Investment Framework, Institutional Investors Group on Climate Change; NZAOA, (2021[58]), Target Setting Protocol: Third Edition; TCFD, (2021[59]), Implementing the Recommendations of the Task Force on Climate‑related Financial Disclosures.
The portfolio composition category serves to track the changes in a financial institution’s investment or lending approach to change the composition of the portfolio. The frameworks concur that information points and metrics should be included on the portfolio share in low GHG emission assets and climate solutions, and assets that need to be phased‑out but differ in how they express specific metrics. For instance, some frameworks refer to capital invested rather than portfolio shares. Frameworks propose a range of other information points and metrics, for instance, on the proportion of the portfolio with net‑zero targets. They propose even more text‑based information points with little or no overlap across frameworks, thus running the risk of a potential overburdening for reporting institutions.
Information points and metrics that support the effective tracking of engagement activities can help understand the extent to which steps are taken to support the reduction of clients’ emissions and those of the economic actors underlying financial assets. While many information points are proposed by frameworks, metrics on engagement are very scarce. Frameworks mostly put forward information points relating to the overall and climate‑specific engagement and stewardship practices of a financial institution, for instance, on how they identify and escalate engagement activities; engage in dialogue; present and vote on actions; and undertake phase‑out engagement.
Strategy and governance information points and metrics could support an assessment of internal changes to a financial institution’s strategy and shifts in internal processes to incentivise the net‑zero transition. In this area, frameworks propose a large variety of information points on the integration of climate considerations in strategic decision‑making and investment strategies, but very few concrete metrics.
In response to rapidly increasing climate‑related physical risks, a range of stakeholders are analysing physical climate risks to finance and related efforts to increase resilience to climate change. However, while there is a growing landscape of methodologies to integrate physical climate risks in traditional financial risk analysis, the operationalisation of the concept and assessments of alignment with climate resilience as a policy objective is still very limited, which also explains the lack of resilience data points in Chapter 3. This section provides an overview of developments in this area.
While financial risk and resilience alignment stem from different perspectives and aims, leading to differences in scope and results, they are interrelated and overlap in several analytical dimensions and data requirements (Mullan and Ranger, 2022[60]; UNEP FI, 2022[61]; Bernhofen and Ranger, 2023[62]). The evaluation of the climate resilience alignment of finance flows extends beyond risk analysis, comparing physical climate risks to climate resilience policy goals and reference points while taking into account adaptation actions by companies and the financial sector. This means not only identifying and quantifying risks, but also assessing how economic actors and financial sector participants contribute to reducing those risks in alignment with climate policy. Policymakers and the private sector could then also use such assessments to identify adaptation opportunities and where further public investment may be most needed for societal co-benefits. However, much more conceptual work in this area is needed.
As suggested in Noels et al. (2024[63]), which builds on existing approaches end emerging practices, assessing the climate resilience alignment of finance can involve five interrelated dimensions (Figure 2.7) Physical climate risk assessments for assets, entities and finance stocks and flows are analytical dimensions for both a financial risk analysis and a climate resilience alignment assessment dimensions 1 and 2). This is also the case of the dimension relating to analysing adaptation and resilience actions and strategies by financial system and economic actors (dimension 3). Assessing the alignment of finance with climate‑resilient development, as called for in Article 2.1c of the Paris Agreement, further requires the availability and identification of relevant policy goals and targets (dimension 4). Bringing these dimensions together then allows an assessment of whether finance flows and stocks contribute or not to societies becoming more resilient to the impacts of climate change (dimension 5).
Source: (Noels et al., 2024[63]).
Overall, financial sector physical climate risk analyses and approaches are increasing. A range of commercial data providers provide different data solutions and analyses for different asset classes that can be used to assess physical climate risk for individual assets or financial portfolios. Financial institutions may further aggregate such assessments, and central banks may assess climate risks to the financial centres they oversee at a more aggregate level.
Methodologies to date have largely focussed on assessments of physical climate risks to corporate financial assets (Hain, Kölbel and Leippold, 2022[64]; UNEP FI, 2023[65]). In this context, some research has found that the different physical climate risk assessments lead to a very wide range of results for the same entity (Hain, Kölbel and Leippold, 2022[64]). Methodologies to assess physical climate risks to other large asset classes have, however, been explored for real estate and infrastructure (UNEP FI, 2023[66]; Coloia and Jansen, 2021[67]), as well as sovereign bonds (NGFS, 2024[68])
Challenges, however, remain for assessing climate change risks, such as the absence of comparable methodologies or set of metrics for assessing resilience to physical climate risks, as well as data availability constraints (Simpson et al., 2021[69]). These challenges similarly constrain climate resilience alignment assessments. There are, however, further challenges in the assessment of the climate resilience alignment of finance (Mullan and Ranger, 2022[60]). Notably, quantified adaptation goals remain elusive at the global level, owing to the context and location‑specific nature of adaptation and resilience needs (Jeudy-Hugo and Charles, 2022[70]). Such goals and targets are needed at the national and subnational levels, where they, however, remain rare. more specifically, Noels et al. (2024[63]) highlight that:
The geographical, sectoral, and temporal context of climate resilience alignment assessments influences the choice and prioritisation of climate‑related hazards data and indicators. Although certain hazards, such as flooding and heatwaves, have been more impactful to date, the prevalence of climate-related hazards is heterogeneous across geographies. Hence, there is a need for high granularity in data and location-specific hazard prioritisation to capture risks accurately.
There are a wide range of climate‑related hazards and classifications. Existing climate risks analysis may refer to the same hazard differently and prioritise different hazard. Moreover, some existing methodologies combine acute and chronic climate related hazards, while others capture those in separate analysis. For climate alignment analysis, it may be practical initially to keep those separate as they require different adaptation responses.
Data gaps for climate exposure and vulnerability at the asset level need to be filled. Relying solely on headquarters location data can significantly underestimate climate exposure. Many existing climate risk assessments only analyse climate exposure. Not adequately characterising vulnerability offers only a partial view of overall physical climate risk.
Further developments of typologies and data for adaptation and resilience strategies are needed to inform both climate resilience‑related financial risk and alignment assessments. These should cover real-economy actors and financial institutions. Actions and strategies for reducing exposure are easier to identify as they require less information. Strategies to reduce vulnerability often rely on corporate disclosure, which is currently scarce.
In contrast to climate change mitigation, there is a lack of clear quantitative global policy goals and reference point(s) on adaptation and resilience. Therefore, consistent with the context-specific nature of climate exposure and vulnerability, reference points at national and regional levels are critical for assessing adaptation and resilience alignment. In this context, adaptation relevant policies, goals and targets may be integrated into mainstream policies, such as worker policies, or as part of sustainability-related disclosure requirements.
The final step in a climate resilience alignment assessment involves comparing the level of climate risk and the impact of adaptation actions on reducing that risk with relevant climate resilience policy goals. A metric for real‑economy investments may relate to the share of activities consistent with National Adaptation Plans, while for financial system participants, this may relate to the share of assets under management aligned with climate resilience goals.
Due to the methodological and data challenges highlighted above, evidence on the alignment of finance with climate adaptation and resilience goals is very limited. This explains why the remaining chapters of this report on available estimates of financial flows and stocks (Chapter 3) and of climate‑related financial sector policies and actions (Chapter 4) focus primarily on climate change mitigation.
In this context, it is, however, important to note that climate resilience alignment assessment of finance flows may in any case only partly be quantitative and require complementary types of indicators as some societal resilience goals are difficult to quantify. This lack of quantification is partly due to the insufficient progress in assessing such policies, and the policies themselves may not always be quantitatively formulated. Moreover, resilience alignment assessments may require examining how adaptation reduces exposure and vulnerability for each climate hazard individually.
Further, the climate resilience alignment of real-economy investments and financial system assets may further depend on wider actions, such as public investments in collective adaptation solutions and adaptation actions by other actors within the value chain. It is also dependent on advancements in climate change mitigation, which implies that adaptation goals remain moving targets. Moreover, there are limits to adaptation, especially under high-emission scenarios. This underscores the ongoing need for climate change mitigation efforts to limit global warming and prevent scenarios where adaptation and resilience alignment may no longer or only partly be feasible.
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← 1. CDR refers to anthropogenic activities removing CO2 from the atmosphere and durably storing it (...) but excludes natural CO2 uptake not directly caused by human activities.
← 2. Scope 1 are direct emissions from owned or controlled assets, Scope 2 indirect emissions from the generation of purchased energy, and Scope 3 are indirect emissions from any other up- and down-stream activities related to the company’s product (World Resources Institute & World Business Council for Sustainable evelopment, 2004[32]). These were defined via the GHG Protocol, a reference point for corporate level reporting and accounting.