Established in 2015, PCAF is a collaborative, industry-led partnership that provides a standardised methodology for financial institutions to assess and disclose the greenhouse gas (GHG) emissions associated with their loans and investments, commonly referred to as "financed emissions." The initiative aligns with the Greenhouse Gas Protocol and other climate-related frameworks, and has so far engaged over 500 global financial institutions who represent more than $90 trillion in assets.
Financed emissions typically make up the vast majority of a financial institution’s climate impact, far exceeding operational emissions due to the scale of capital deployment. The complex challenge of accurately measuring these emissions has led to inconsistent disclosures. Enter the PCAF standard, which provides a consistent and transparent framework for quantifying climate exposure, identifying decarbonisation opportunities, and meeting stakeholder and regulatory expectations.
The relevance of PCAF has intensified amid a broader environment of increased regulatory requirements and stakeholder expectations. New climate disclosure rules such as the recommendations under IFRS S2, the Corporate Sustainability Reporting Directive (CSRD), and the Sustainable Finance Disclosure Regulation (SFDR), mandate more detailed and verifiable climate-related disclosures and signal a global push towards net-zero alignment in financial markets.
Managers are facing increased scrutiny from investors and stakeholders, and ESG matters have increasingly become associated with value creation or market intelligence. Even Blackrock - who withdrew from the NZAM - still maintains it will use sustainability data in its investment decision-making (BlackRock 2025).
Understanding financed emissions is critical for financial institutions to manage climate-related risks, inform investment strategies, and enhance reputational credibility. Transparent disclosure under PCAF enables firms to demonstrate accountability, respond to investor demands, and build resilience in the face of a low-carbon economic transition.
PCAF-compliant institutions are expected to measure and disclose GHG emissions. Scopes 1, 2, and relevant categories of Scope 3 that are attributable to their financial portfolios. These emissions are allocated proportionally based on the financial institution's exposure to each entity or asset class.
Explainer: When a financial institution invests in or lends to a company or project, it is considered partially responsible for the emissions that result. Instead of counting all the emissions, the institution only accounts for the share that matches its level of financial involvement. This means emissions are divided up based on how much of the company or project the institution has financed.
PCAF currently provides methodologies for a wide array of financial instruments, including listed equity and corporate bonds, business loans and unlisted equity, project finance, commercial and residential mortgages, motor vehicle loans, and sovereign debt.
The PCAF data quality score is based on the type of data used to calculate financed emissions. There are three main data options, ranked in order of quality:
Options 1 and 2 are considered higher quality than Option 3. However, financial institutions often use a mix of these, depending on what data is available for each company. In such cases, the overall data quality score is based on an average across all assets.
Each of the three data options includes more specific sub-categories, which correspond to one of five data quality scores. A score of 1 reflects the highest quality data (typically verified emissions), while a score of 5 indicates low data quality due to limited information.
While a score of 5 is less reliable, it is often the starting point for financial institutions when better data isn't available. The PCAF scoring system is designed to promote ongoing improvement: as higher-quality data becomes available over time, institutions are expected to progress up the hierarchy and improve their scores accordingly.
PCAF offers multiple benefits to financial institutions seeking to understand and reduce their climate impact, meet evolving disclosure requirements and maintain or improve stakeholder relations.
Nonetheless, the framework is not without limitations. High reliance on estimated data, particularly for Scope 3 emissions, can compromise the accuracy and utility of disclosures. This is a consistent theme with carbon calculations. A recent SBTi survey has suggested that a lack of access to credible Scope 3 data is preventing companies from setting credible baselines, tracking decarbonisation initiatives, and achieving targets.
In many cases, emissions must be derived from publicly available financial proxies or generalized emission factors, which vary significantly in quality. Moreover, the financial attribution method based on Enterprise Value Including Cash (EVIC) can obscure actual risk exposure in complex investment or lending structures.
Moreover, though undeniably useful in terms of scoring, the static nature of the DQS system may present certain issues. For example, there is currently no mechanism to differentiate between verified, high-frequency, and audited emissions data beyond the level 1 score, limiting the granularity of reporting. This may disincentivise innovation or overstate comparability among institutions. These concerns belie deeper questions around just how granular data should be for it to be useful - both for firms and for genuine net-zero.
Manually managing PCAF-aligned emissions accounting presents significant operational challenges, particularly for institutions with complex, multi-asset portfolios. Traditional approaches relying on spreadsheets, emails, and static documents introduce considerable risks of error, data loss, and inconsistency.
Additionally, matching financial exposures to appropriate emission factors or calculating financial attribution using external valuation data (e.g., EVIC) often requires integrating disparate systems and data sources. As regulatory scrutiny intensifies, institutions face growing pressure to ensure that disclosures are both traceable and auditable.
In this context, reliance on manual or semi-automated methods can hinder progress toward high-quality reporting and delay strategic decision-making. Institutions have started to recognise that technological solutions - particularly those utilising automation and artificial intelligence - have emerged as essential tools to solve these problems of disparateness, complexity, and inefficiency.
The advent of Big Data has been nothing short of a revolution when it comes to market intelligence, investment decision-making, and the tracking of sustainability related metrics (a truly modern investment approach requires the integration of all three). However, significant operational challenges remain with data acquisition and analysis across complex portfolios, exposures, and markets. It is no longer good enough to find a signal in the noise; it must be the signal. Utilising the latest in technologies bolstered by methodologies such as PCAF allows firms to capture the best possible data.
Improving data quality isn’t just about better disclosure. Moving beyond disclosure for disclosure’s sake, high-quality emissions data can identify financial inefficiencies and unlock cost-saving opportunities. For example, tracking Scope 2 emissions across office locations can highlight energy-inefficient assets, poor procurement choices, or sites with high-cost utilities. Lower Scope 2 emissions often correlate with reduced electricity consumption and lower bills, meaning more profit, not just better ESG scores.
In markets like the UK, these insights can be doubly financially material. Tax incentives tied to Energy Performance Certificate (EPC) ratings reward energy efficiency, offering a double dividend: lower operational costs and regulatory or fiscal benefits. A data-led strategy around Scope 2 not only boosts environmental credentials but also enhances bottom-line performance and asset valuation.
Harvest was designed to facilitate the direct collection of emissions data from general partners and portfolio companies using structured and highly customisable digital data exchange tools. Efficiency is supercharged with the use of AI document scraping feature Smart Docs, allowing unstructured data to be captured. By capturing emissions data at the source, the accuracy and granularity of reporting is enhanced.
Each data point is accompanied by metadata indicating its origin, verification status, and calculation method, allowing institutions to align the dataset with PCAF’s Data Quality Score framework. This traceability supports both internal governance and external assurance.
Harvest supplements this approach by offering physical activity-based emissions estimation, particularly useful for early-stage or pre-revenue companies where direct emissions data are unavailable. This methodology relies on operational inputs (e.g., energy consumption, materials used) to derive emissions figures and provides a defensible proxy in the absence of primary data.
When direct or estimated emissions cannot be captured, Harvest’s partnership with proxy data providers allows for revenue-based emissions estimates, leveraging sectoral benchmarks and machine learning to produce scalable assessments for publicly listed companies. It is especially effective for supplementing Scope 3 emissions or filling gaps in coverage across large portfolios.
Taken together, these platforms enable a tiered emissions accounting strategy:
Tier 1: Direct data collection through Harvest
Tier 2: Activity-based estimation via Harvest Carbon Calculator
Tier 3: Revenue-based estimation using proxy data providers
This combined approach facilitates higher data quality scores, improves auditability, and equips institutions with actionable, value-creating insights for climate strategy and regulatory reporting.
Sources
Financial institutions - Science Based Targets Initiative
SBTi-The-Scope-3-challenge-survey-results.pdf
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