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Guidance for CFOs and audit committees in the insurance sector on reporting and assuring scope 3 greenhouse gas emissions related to sovereign debt of all maturities issued in domestic or foreign currencies. Find out about methods of estimating emissions and common challenges.

ICAEW's Financial Services Faculty has worked with members from within the sector and experts from the Partnership for Carbon Accounting Financials (PCAF) to outline estimation methodologies for those reporting and assuring on greenhouse-gas emissions relating to non-life insurance products.

Here we focus on sovereign debt, and separately have covered commercial lines (aviation) and personal lines (motor) to highlight the suitability of applying PCAF methodology to the investments held by Non-Life insurers.

Scope 3 emissions are all indirect GHG emissions, not included in Scope 2, that occur in the value chain of the reporting company. Scope 3 can be broken down into upstream emissions that occur in the supply chain (for example, from production or extraction of purchased materials) and downstream emissions that occur as a consequence of using the organisation’s products or services.

As part of Scope 3 Category 15, non-life insurers need to report both their financed emissions from their investments and their insured emissions from across the insurance value chain. To avoid double counting the insured emissions are calculated separately to the financed emissions but still reported within Category 15 (investments).

The PCAF highlights that insurance associated emissions and financed emissions are not directly comparable and so should not be aggregated (see Box 6-1 on p53 of The Global GHS Accounting and Reporting Standard, Part C).

Estimation methodologies

Overall process flow

This figure outlines the overall process flow for the calculation of financed emissions from sovereign debt (across all PCAF options).

Data quality scores

Within its Global GHG Accounting and Reporting Standard Part A, the PCAF further splits possible data quality scores into three different 'options' depending on data availability which are outlined in the table below. Further details on the attribution factors are available on p116 of Part A and shown below.

Formula supporting financial services organisations in calculating emissions related to sovereign debt.
General description of the data quality score table for sovereign debt (score 1 = highest data quality; score 5 = lowest data quality)
General description of the data quality score table for sovereign debt (score 1 = highest data quality; score 5 = lowest data quality)

Data quality

Options to estimate the financed emissions

When to use each option

Score 1

Option 1: Reported emissions

1a

Verified GHG emissions of the country are available. These GHG emissions are reported by the country itself and can be extracted from the UNFCC.

Score 2

Option 1: Reported emissions

1b

Unverified emissions of the country are available.

Score 3

Option 2: Physical activity-based emissions

2a

Reported GHG emission of the country are not known. Emissions are calculated using primary physical activity data of the country's energy consumption (domestic generated and imported) and emission factors specific to that primary data.

Score 4

Option 3: Economic activity-based emissions

3a

Reported GHG emissions of the country are not known. Emissions are calculated using sectoral revenue data of the country's production and emission factors specific to that revenue data.

Score 5

3b

Country GHG emissions are estimated by taking a proxy. GHG emissions are (a) similar (climate zones), wealth, GDP country are taken to estimate the country GHG emissions.

PCAF includes a table outlining detailed data quality score tables per asset class on p142 of Part A.

Option 1: reported emissions

Figure 2 outlines the process flow for calculating financed emissions from emissions from sovereign debt.

More support

Read more case studies and a list of common challenges facing financial services organisations when reporting and assuring scope 3 emissions.

Case studiesChallenges
  • Data quality score 1 is available if data is verified and reported data.
  • Data quality score 2 is given if the data is reported but unverified emissions data.

Option 2: physical activity-based emissions

Notes: *data quality of score of 3 is given.

Primary physical activity data refers to country's energy consumption by energy source and the emission factor would be energy source specific.

Option 3: economic activity-based emissions

Notes:

  • Data quality score of 4 is given if the emissions are calculated is a weighted average of the country’s production sector’s GHG emissions weighted by revenue.
  • Data quality score of 5 is given if GHG emissions are unavailable and instead GHG emissions of a proxy country are used weighted by the ratio of PPP-adjusted GDP (gross domestic product at purchasing power parity) of the proxy country to the PPP-adjusted GDP of the country in question.

Common challenges

The PCAF Financed Emissions Standard provides detailed methodology for the following seven asset classes:

  • listed equity and corporate bonds;
  • business loans and unlisted equity;
  • project finance;
  • commercial real estate;
  • mortgages;
  • motor vehicle loans; and
  • sovereign debt.
Guidance created with permission from PCAF

This guidance is based, with permission, upon the work of the Partnership for Carbon Accounting Financials (PCAF) including the data quality score tables from The Global GHG Accounting and Reporting Standard for the Financial Industry.