This article first appeared in Forum, The Edge Malaysia Weekly on December 18, 2023 - December 24, 2023

What are “financed emissions”? In layman’s terms, “financed emissions” serve as a scorecard to monitor the green efforts of financial institutions. According to the Partnership for Carbon Accounting Financials (PCAF), greenhouse gas (GHG) emissions are categorised into three scopes.

Scope 1 is related to direct GHG emissions generated from sources owned or controlled by the reporting company. Scope 2 is the indirect GHG emissions generated from sources (for example, electricity, steam and cooling) purchased or acquired by the reporting company. Scope 3 is all other indirect GHG emissions not accounted for in Scope 2 reporting. The coverage of Scope 3 is broad. It involves all the indirect GHG emissions from upstream activities (for example, from material gathering to production to finished products or goods for sale) as well as downstream activities (such as distribution, storage, usage and end-of-life treatment), except those produced by the energy sources purchased or acquired by the reporting company. The term “financed emissions” specifically refers to the GHG emissions under Scope 3.

Banks are required to report “financed emissions” by seven asset classes. They are listed equity and corporate bonds, business loans and private equity, project finance, commercial real estate, mortgages, motor vehicle loans and sovereign debt. Each asset class has its own method of calculation. Using the business loans to listed companies’ calculation method as an example, a reporting bank is required to establish an “attribution factor”, which is a ratio derived from loans (numerator) extended over the enterprise value plus cash. Next, the “company emissions” need to be determined. It is either provided by the bank’s borrowers and/or investee companies, or estimated using physical or economic activity-based emissions of the borrowers or investee companies. In addition, the data quality of “company emissions” must also be specified in the report. Then, the “financed emissions” of the asset class is estimated by multiplying the “attribution factor” with the “company emissions” (see reference equation). Once the “financed emissions” number is determined, the “emissions intensity” is derived by dividing “financed emissions” with total outstanding loans (in million ringgit denomination). The whole process is repeated on each asset class with the predefined calculation method (see PCAF for details). The “emissions intensity” numbers are then used to compare and benchmark banks.

If you are confused or overwhelmed by now, you are not alone. Allow me to shed some light. The “emissions intensity” ratio is the easy part, provided banks managed to produce the “financed emissions” numbers. While banks are able to tweak their systems to churn out the numbers for “attribution factor” of the designated asset classes, the data on “company emissions” is the pain point. It is not readily available.

Acknowledging this key limitation, PCAF allows banks to purchase data from third-party data providers (such as ISS ESG and MSCI). However, using third-party data presents another set of challenges. First, a bank needs to stick with the same data provider to ensure internal consistency and comparability of its own reported numbers. Second, the level of comparability among banks is low due to the use of different data from varying data providers who rely on different data sources and estimation methodologies. Although the “emissions intensity” ratio is meant to improve comparability among banks, varying GHG emissions sources would undermine the ratio’s reliability. For instance, this dilemma would be apparent when two banks of similar loans and investment profiles generate different emissions intensity” ratios. At the national level, the reported “financed emissions” numbers may not be comparable due to different sources of GHG emissions, posing a challenge for Bank Negara Malaysia to measure banks’ green efforts.

The most reliable data source on Malaysia’s CO2 emissions is the Fourth Biennial Update Report (BUR) submitted by the Ministry of Natural Resources, Environment and Climate Change to the United Nations. However, the latest data on CO2 emissions are reported for 2019, which is three years behind. Another challenge observed from this BUR report is the sectoral classifications. The BUR sector and subsector classifications are different from the classifications specified in the PCAF — this raises the data mapping issue.

At the firm level, Malayan Banking Bhd (Maybank) is the first bank claiming to have furnished a complete report on “financed emissions”. As of 2022, Maybank reported to have financed 25.7 million tonnes of CO2 emissions (mtCO2e), of which 97% are generated in Malaysia. In the same reporting year, CIMB reported 13.8 mtCO2e. It is apparent that CIMB’s reported number is substantially lower, at about 46% of Maybank’s reported number. In case you have suspected, it has nothing to do with under or creative reporting. CIMB has reported only Scope 1 and 2 CO2 emissions attributed to its borrowers and investee companies. Maybank’s reported number includes Scope 3 as well.

On the data quality scale of one to five, one being the highest and five being the lowest (refer to PCAF for details), CIMB’s average data quality score (ADQS) is four and Maybank’s ADQS is 4.63. The other contributing factor to this gap in “financed emissions” numbers is the “attribution factor”, which is that the size of loans and investment composition between these two banks are also different.

Although efforts to report “financed emissions” are indeed commendable, the numbers from Maybank and CIMB are not exactly comparable. The scope of reporting alone undermined their comparability. For instance, CIMB reported an overall intensity of 0.060 mtCO2e in 2022 as compared with 0.063 mtCO2e in 2021. On the other hand, Maybank reported an overall intensity of 0.044 mtCO2e in 2022 as compared with 0.046 mtCO2e in 2021. At a glance, both banks reported an approximate improvement of 5%. Technically, both banks also reported variations in their data quality scores between these two years, indicating a change in data sources.

In terms of “emissions intensity”, the lower the reported number, the better is the reduction of “financed emissions”. On this basis, has Maybank performed better than CIMB? The answer is that their reported numbers are not comparable. The reasons are differences in reporting scopes and CO2 emissions data sources. These discrepancies clearly indicate that “financed emissions” is not a firm-level undertaking but an industry-level undertaking, and national-level assistance is needed (see chart below).

A reasonable solution to address this challenge involves collaboration among many stakeholders (including Bank Negara, the Securities Commission Malaysia, the Ministry of Natural Resources, Environment and Climate Change and banks) to produce a sound framework and baseline for Malaysia’s financial institutions as a whole. To kick-start, it is key to appoint a coordinator to get all stakeholders together and determine the terms and scope of engagement.

The appointed coordinator will serve as the hub to coordinate all the stakeholders, facilitate the development of the framework, gather and harmonise data, conduct empirical research, furnish the “financed emissions” baseline for national and sectoral levels, and conduct workshops and knowledge sharing seminars. Universities equipped with the right facilities (knowledge banks, research tools and so on), and domain expertise (including banking, economics, investment and statistics) are ideal candidates for the role. What is needed next are sponsors, steering committees and stakeholders’ endorsement to get the ball rolling.

Dr Lim Kok Tiong is a seasoned risk manager, adviser and researcher

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