The patchy road towards Net-Zero

Blake Goud
6 min readAug 9, 2022


It is more complex than it first appears to tell whether a financial institution is aligned with a long-term emissions trajectory consistent with Net Zero. Financed emissions are important, but using institution-level data (where available) as a target without considering the economy as a whole could lead to ‘paper decarbonization’ that results in the broader economy falling out of alignment unless targets are set considering the full-economy view.

By Dr. Eman Tabet, Research Associate, RFI Foundation

Last month, Finance Watch published a report questioning whether reaching Net Zero goals was possible by just focusing on financed emissions. Their critique centered around the use of Net Zero to justify new fossil fuel investment, with the seeming contradiction between those goals and scenarios such as the International Energy Agency’s, which suggests that the Net Zero ambition is incompatible with investments in new fossil fuel production.

There should be no contradiction post-COP 26 with initiatives such as the Glasgow Financial Alliance for Net Zero (GFANZ), which recently announced guidance for its 450 financial institution members who have committed to reducing emissions towards net zero. However, a lack of clear standards makes it hard to tell whether financial institutions’ plans will reduce total emissions consistent with Net Zero pathways, or whether they will reduce emission intensity (per unit of production) in their portfolios in a way that appears net zero-aligned but produces results for the economy that are misaligned with long-term Net Zero pathways.

The divergence in practice and differences between emissions disclosure rules means that while we work on reaching net zero, total emissions will remain stable or might even increase. While this happens, it will be difficult to tell whether an individual financial institution is aligned or misaligned to Net Zero until after it’s too late to correct course. Different standards include different definitions of financial institution “Scope 3” emissions, which make it hard to compare between institutions.

As reporting standards continue to develop and become more rigorous, they will become better at fulfilling their role in creating consistency. Information providers and toolboxes used to analyze whether financial institutions are making the right transition towards their emissions targets will also continue to improve. In the meantime, on this path towards Net Zero, banks and financial institutions face several unique challenges of navigating standards and frameworks that are at times incongruent.

First, as banks try to transition towards Net Zero, there is pressure on them to navigate through all the data, impact and parameters so as to figure out the most effective ways to create change with different stakeholders advocating for different positions. The most direct method to reduce direct financial risks to investors, by decarbonizing their loan books by selling off all the high emission assets, won’t do anything to the emissions trajectory in the global economy. If sold to an institution that doesn’t care about emissions, it is likely to make it worse (raising rather than lowering the transition risk for the financial sector as a whole).

Without data connecting a financial institution’s financed emissions contributions to the economy as a whole, financial institutions will be challenged in their stewardship role. Financial stakeholders will often focus on institution-specific, short-term, return-oriented goals that may be incongruous with imposing conditions on their corporate clients. Regulators may be focused on an institution’s contribution to overall financial stability and may prioritize risk reduction and reporting compliance objectives. Other stakeholders may see both other objectives as insufficient for long-term objectives for achieving Net Zero.

Third, there is a need for banks to work on improving their data quality, which is an integral, and perhaps inevitable, part of moving towards complying with the developed guidelines. However, they have to find the most relevant data from internal and external sources and deal with differences between those data and the self-reported data from customers that could be more up-to-date and precise than other sources, or it could be cherry-picked to show a better situation than actually exists.

Those challenges have largely been left to banks to overcome. And with current frameworks remaining patchy, there is an increasing need for providing methodologies that produce comparable estimates. The needs are especially great for emerging economies, where data is much scarcer, to inform decision-making pertaining to climate-related financial risks.

With so many definitions around how to accurately measure climate risk, which can vary from institution to institution as well as among their customers, it becomes increasingly muddled to look at the available data for comparing one institution to another. Top-down analyses, such as that developed by our work at RFI, help provide consistent and comparable emissions data down to individual bank level. This type of data may not be the be-all and end-all of climate data, but taken for what it is (an ‘order of magnitude’ estimate) it can offer a better picture of the general trajectory for the financial sector as a whole, and for each institution’s contribution towards that trajectory and their alignment with national and international targets.

Top-down estimates can provide a wayfinding tool for banks to use for strategy & planning even as they work towards more granular sectoral data for their customers. Financial institutions can use the top-down models to analyze and evaluate specific subsector targets and responses and identify where they will benefit most from getting new and better data. All of this in turn provides an important input for pushing forward the engagement strategy highlighted by Finance Watch as a critical step forward.

But the question remains: how do we look at institution-specific climate data and connect it to economy-wide trajectories? This is where it becomes a necessity to look at the details of interlinkages between country-level trends and bank-level trajectories. For example, forecasted and required policies in the Inevitable Policy Response can turn into constraints used to limit risk by rapidly reducing exposure to sectors that are likely to have significant transition risk over the forecast period. At the bank-level, this can satisfy investor and regulator concerns about risk exposures, while at an economy-wide level it can draw financing away from transition-related investments that would support the intended outcome of the policies.

Transitioning towards Net Zero is a journey, and one that is bound to go through several stages. The outlines of those stages can be observed from the focus points of different frameworks. The SBTi current framework, for example, is geared towards short-term emission reduction (aligning with 2030 targets) and portfolio decarbonization for financial institutions. Meanwhile, long-term Net Zero takes the opposite approach, that requiring more than mere tweaking of portfolios for financial institutions to be considered as aligned. It requires consistent financing of what is important for the economy’s Net Zero transition, which requires financing for decarbonization (including transition) as well as climate solutions.

There is a lot banks can do in the short run, even without individual customer-level data. Using estimated data, each individual bank can take the top-down estimates and extrapolate the sub-sectoral emissions of the high-emitting sectors and compare them to the country-wide averages. Banks can supplement this data with information about individual clients’ alignment with Net Zero if they have set verified Net Zero targets through initiatives such as SBTi. For example, if they know that there is a large concentration of their borrowers aligned to the SBTi guidelines, they can focus efforts for transition finance with those clients and take more rudimentary steps such as engaging in support of better data collection from other customers.

Financial institutions can use top-down analysis to streamline their efforts. Instead of letting data gaps or weaknesses become an impediment to getting started, top-down analyses can be useful for conducting a gap analysis to understand interlinkages between customer exposures in different sectors. Subsequently, it can help to develop an understanding of what the economy as a whole needs to align to a Net Zero trajectory even where granular data is unavailable.

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Blake Goud

Promoting adoption of responsible finance in Islamic markets & Islamic finance. CEO @RFIFoundation.