How Data Quality Works Under PCAF: The Foundation of Credible Financed Emissions Reporting

As the financial sector faces mounting pressure to align with global climate goals, the need for robust, transparent, and comparable financed emissions reporting has never been greater. The Partnership for Carbon Accounting Financials (PCAF) standard is now the global benchmark for measuring and disclosing greenhouse gas (GHG) emissions linked to loans and investments, referred to as financed emissions. At the heart of the PCAF methodology is a rigorous approach to data quality, ensuring that reported numbers are meaningful, actionable, and trustworthy.

In this blog, we’ll explain the PCAF standard, why data quality is essential in financed emissions reporting, explore the five-tier data quality score, and provide real-world examples for each score band. Whether you’re a sustainability officer, risk manager, or portfolio analyst, this guide will help you understand and implement best practices for financed emissions reporting using PCAF.

What Is the PCAF Standard?

At its core, PCAF is a collaborative global initiative designed to standardize carbon accounting for financial institutions. It offers a framework for accurately measuring and disclosing the greenhouse gas emissions associated with loans and investments, empowering financial institutions to assess their environmental impact more comprehensively. PCAF recognizes the influential role of financial institutions in steering the global economy towards sustainability and aims to provide them with effective tools for change. Since 2015, more than 460 global financial institutions that collectively manage $85.6 trillion have committed to PCAF’s accounting framework. 

Key features of the PCAF standard:

• Asset class-specific guidance: Tailored approaches for different financial products.
• Alignment with global frameworks: Designed to complement the GHG Protocol Scope 3 Category 15 and support scope 3 emissions reporting.
• Attribution factor methodology: Calculates the share of an investee’s emissions attributable to the financial institution.
• Data quality scoring: A transparent five-tier system to assess and disclose the reliability of emissions data.

The PCAF standard is now widely adopted by banks, asset managers, and insurers seeking to meet regulatory requirements, set net zero financed emissions targets, and demonstrate climate leadership. 

Why Does Data Quality Matter in Financed Emissions Reporting?

Data quality is the foundation of credible financed emissions reporting. High-quality data enables financial institutions to:

• Set and track science-based targets for portfolio decarbonization.
• Comply with regulatory frameworks and voluntary guidance (e.g., TCFD, ISSB, GHG Protocol, and regional mandates).
• Build stakeholder trust by providing transparent, comparable, and verifiable disclosures.
• Effectively manage climate risk and align portfolios with net zero pathways.
• Conversely, poor data quality can undermine the credibility of disclosures, lead to misinformed decisions, and expose institutions to reputational and regulatory risks.

The Five-Tier PCAF Data Quality Score

The PCAF standard uses a five-tier data quality score to rate the reliability of emissions data and calculation methods for each asset class and exposure. This system helps institutions identify data gaps, prioritize improvements, and communicate transparently with stakeholders.

PCAF Data Quality Scores

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Deep Dive: The Five Data Quality Score Bands

Score 1: Verified, Direct Emissions Data (Highest Quality)

Definition: Emissions data is directly reported by the investee company and has been independently verified (e.g., by a third-party auditor or through a recognized disclosure platform like CDP).

Example: A bank invests in a listed company that publishes an audited sustainability report, including verified Scope 1 and Scope 2 GHG emissions. The bank uses the reported numbers, applies the PCAF attribution factor based on its shareholding, and assigns a data quality score of 1.

Why it matters:

• Highest level of accuracy and credibility.
• Enables precise portfolio emissions tracking and target-setting.
• Preferred for regulatory and stakeholder disclosures.

Data sources:

• Audited company sustainability reports
• CDP disclosures
• National GHG inventories

Score 2: Unverified, Direct Emissions Data

Definition :Emissions data is reported by the investee company but has not been independently verified.

Example: An asset manager holds corporate bonds in a manufacturing firm that publishes a sustainability report with self-reported (but unaudited) GHG emissions. The manager uses these numbers for financed emissions calculations and assigns a score of 2.

Why it matters:

• Still based on company-specific data, but less reliable due to lack of verification.
• Should be prioritized for improvement (e.g., by encouraging investees to seek third-party assurance).

Data sources:

• Company sustainability or annual reports (unaudited)
• Company disclosures to stock exchanges

Score 3: Calculated Using Company-Specific Physical Activity Data

Definition: Emissions are calculated using company-specific physical activity data (e.g., energy use, production volume) and appropriate emission factors.

Example: A financial institution lends to a logistics company that doesn’t report emissions, but provides annual fuel consumption data. The lender calculates emissions using fuel use and standard emission factors (e.g., from the PCAF web-based emission factor database), assigning a score of 3.

Why it matters:

• More accurate than sector averages, but less so than direct emissions reporting.
• Encourages engagement with investees to collect relevant activity data.

Data sources:

• Company energy bills, production logs, utility data
• Emission factors from PCAF, IEA, EPA, etc.

Score 4: Estimated Using Sector-Average Activity Data and Emission Factors

Definition: Emissions are estimated using sector-average activity data (e.g., average energy use per revenue for the sector) and emission factors.

Example: A bank finances a small construction firm that provides only annual revenue figures. The bank applies sector-average energy intensity (e.g., kWh per $ revenue) and emission factors to estimate emissions, resulting in a score of 4.

Why it matters:

• Useful when company-specific data is unavailable.
• Less precise; should be improved over time by collecting better data.

Data sources:

• National statistics, sector benchmarks
• PCAF emission factor database

Score 5: Estimated Using Proxy Data or Broad Assumptions (Lowest Quality)

Definition: Emissions are estimated using proxy data or broad assumptions due to a lack of company or sector-specific data.

Example: An asset manager invests in a private company with no emissions or activity data available. The manager uses a generic proxy (e.g., average emissions per employee for the sector) to estimate financed emissions, assigning a score of 5.

Why it matters:

• Lowest reliability; should be disclosed transparently and targeted for improvement.
• Highlights data gaps and the need for engagement or new data sources.

Data sources:

• Proxy data from industry studies
• Assumptions based on similar companies

How Data Quality Scores Are Used in Practice

• Disclosure: Financial institutions must disclose the data quality scores for each asset class and exposure, as required by the PCAF standard.
• Continuous improvement: Institutions are expected to improve data quality over time by engaging investees, leveraging new data sources, and using tools like the PCAF web-based emission factor database.
• Portfolio decarbonization: High data quality enables more accurate portfolio emissions baselining, scenario analysis, and progress tracking toward net zero financed emissions.

Why the Data Quality Score Matters

• Regulatory compliance: Many frameworks, including the GHG Protocol Scope 3 Category 15 and TCFD, require transparent disclosure of data sources and quality.
• Stakeholder trust: Investors, clients, and regulators increasingly scrutinize the credibility of financed emissions disclosures.
• Risk management: High-quality data enables better climate risk assessment and strategic decision-making.
• Comparability: The five-tier system allows stakeholders to compare emissions data across institutions, asset classes, and reporting periods.

The PCAF standard and its five-tier data quality score are transforming how the financial sector measures and manages financed emissions. By understanding and applying this framework, financial institutions can deliver credible, actionable, and transparent disclosures, building trust with stakeholders and driving real progress toward net zero financed emissions.

Next steps for financial institutions:

• Assess current data quality for all asset classes.
• Disclose data quality scores in line with the PCAF standard.
• Use the PCAF web-based emission factor database and engage with investees to improve data quality over time.

By prioritizing data quality, the financial sector can lead the way in climate action, portfolio decarbonization, and sustainable finance.

As the financial sector intensifies efforts to align with global climate objectives, prioritizing robust, transparent, and comparable financed emissions reporting is critical. The Partnership for Carbon Accounting Financials (PCAF) standard has emerged as the global benchmark for measuring and disclosing greenhouse gas emissions linked to financial activities, known as financed emissions. Central to the PCAF methodology is a rigorous five-tier data quality scoring system, which ensures that emissions data is reliable, actionable, and credible—enabling financial institutions to set science-based targets, comply with regulations, build stakeholder trust, and manage climate risks effectively.

By adopting PCAF, financial institutions gain access to asset class-specific guidance, alignment with global frameworks such as the GHG Protocol Scope 3 Category 15, and a transparent method to attribute emissions proportionally to their shareholding. The five-tier data quality score ranges from verified, direct emissions data (score 1) to estimations based on proxy data or broad assumptions (score 5), helping institutions identify data gaps and prioritize improvements.

StepChange (stepchange.earth) stands out as a pioneering leader in this space, being the fourth organization globally and the first in the Global South accredited to the PCAF standard. This accreditation underscores StepChange’s commitment to delivering high-quality, transparent financed emissions accounting and supporting financial institutions in the Global South to advance their climate action and portfolio decarbonization efforts. Partnering with StepChange enables institutions to leverage expert guidance and cutting-edge tools to enhance data quality, meet regulatory demands, and demonstrate climate leadership in a rapidly evolving sustainable finance landscape.

By integrating the PCAF standard with trusted partners like StepChange, the financial sector can confidently drive meaningful progress toward net zero financed emissions, fostering a more sustainable global economy.

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