netzero recent update - Alessio (#72)

blogs/NetZero/netzero.md

@@ -42,7 +42,11 @@ The aim of this science note is to argue that the current approach to the Net Ze
 
 Current strategies and methodologies in the banking industry involve several key steps to integrate Net Zero principles:
 
-- **Identifying Industry Perimeter:** A bank should identify which industries want to consider its Net-Zero analysis. A bank can have a baseline for each industry analysed. Industry perimeters (e.g., Oil & Gas, Power, Steel, etc.) are identified based on NACE codes {cite}`europa2010list` related to customers as present in Master Data information. This is one of the most significant pain points. The Net Zero methodology should be linked to the purpose of the financing, not the NACE code of the company. For example, general financing with no clear purpose should no longer be allowed. If a steel company has a loan for installing photovoltaic panels to generate renewable energy for its activities, this loan should not be included in the Net Zero baseline for the Steel industry. This represents a major data quality issue in banks. It's crucial to start an initiative to map the real purpose of historical loans (i.e., stock) to avoid withdrawing credit lines from companies that are paradoxically implementing ESG strategies, as in the steel company example. According to the standard and as-is Net Zero approach, general financing towards steel (typically mapped with steel NACEs) should be avoided due to the carbon intensity emissions of the steel industry. However, financing for renewable energy, mapped with specific NACEs related to the specific purpose of financing and not to the industry, will highlight an ESG benefit derived from this financing.
+- **Identifying Industry Perimeter:** A bank should identify which industries want to consider its Net-Zero analysis. A bank can have a baseline for each industry analysed. Industry perimeters (e.g., Oil & Gas, Power, Steel, etc.) are identified based on NACE codes {cite}`europa2010list` related to customers as present in Master Data information. This is one of the most significant pain points. The Net Zero methodology should be linked to the purpose of the financing, not the NACE code of the company. For example, general financing with no clear purpose should no longer be allowed. If a steel company has a loan for installing photovoltaic panels to generate renewable energy for its activities, this loan should not be included in the Net Zero baseline for the Steel industry. This represents a major data quality issue in banks. It's crucial to start an initiative to map the real purpose of historical loans (i.e., stock) to avoid withdrawing credit lines from companies that are paradoxically implementing ESG strategies, as in the steel company example. According to the standard and as-is Net Zero approach, general financing towards steel (typically mapped with steel NACEs) should be avoided due to the carbon intensity emissions of the steel industry. However, financing for renewable energy, mapped with specific NACEs related to the specific purpose of financing and not to the industry, will highlight an ESG benefit derived from this financing. In conclusion, it is crucial to analyse these additional problems related to NACEs.
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+Consider that banks' Master Data databases typically assign a single NACE to holding companies or heterogeneous groups. For Holding Companies, a generic NACE is inserted. From a climate and net-zero perspective, this generic holding NACE is not useful. Take, for example, a large Oil & Gas group, comprising a holding and various operating companies. The holding company often manages financial activities for the operating companies, leveraging its bargaining power with banks for better interest rates. The funds from banks are, as expected, used not for holding activities but for the operating companies' activities, which relate to the oil & gas industry. For a consistent Net-Zero methodology, it is crucial to consider the real NACE underlying this group, which is the Oil & Gas NACE, not the Holding one.
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+In the case of heterogeneous Groups, like Amazon, which spans e-commerce, IT and cloud services, gaming, etc., banks usually map in their Master Data the so-called main NACE, often based on a turnover analysis. This main NACE is linked to the department/product/function generating the most turnover. While this is a quick solution for Master Data issues, from a climate and net zero methodology standpoint, if a heterogeneous group has diverse ESG profiles (e.g., e-commerce and servers have different climate anf environmental profiles due to servers' higher water usage compared to e-commerce activities, and e-commerce activities producing more CO2 Scope 1 due to trucks delivering goods), it becomes important to re-classify this group according to its legal entities. This re-classification helps in understanding how many ESG profiles exist and which entity truly needs a net-zero commitment and action plan.
 
 - **Credit features: lifecycle or status:** Credit features, particularly the lifecycle or status of a credit, significantly impact the baselines for financed emissions. Emissions are linked to financed companies, and the characteristics of granted credit play a crucial role in the construction of these baselines. For example, a 30-year credit with 5 years remaining requires the bank to assess its strategic value in the portfolio, impacting whether it's renewed or not. Once such a credit expires, its associated financed emissions are removed from the Net Zero metrics, improving the bank's carbon footprint. This is especially true when credits are at zero residual maturity. Additionally, the credit status, reflecting the borrower's creditworthiness, is a key factor. Credits in good standing that turn non-performing (due to repayment issues) can paradoxically improve Net Zero values. Non-performing credits, often linked to operationally troubled companies, imply reduced emissions. When offloaded by the bank, these credits no longer affect its net-zero metrics. However, including non-performing exposures (NPEs) in baselines without adjustment can lead to inflated baselines and significant apparent reductions in carbon footprints in subsequent years, a form of greenwashing. Therefore, it's best practice to exclude loans with less than a year of residual maturity and to be cautious about including NPEs in baselines to avoid artificially inflated metrics and misleading progress towards Net Zero targets.