インド銀行融資のカーボンフットプリント
Carbon Footprint of Indian Bank Loans (原題)
Madhuresh Kumar, Supriyo Mondal, Apeksha Sharma
🤖 gxceed AI 要約
日本語
インドの銀行融資ポートフォリオの炭素集約度をEEIOフレームワークでスコープ別に推計した研究。Scope1では電力セクターと公的銀行の炭素集約度が突出するが、最終エネルギー基準ではその差が縮小し、Scope3では建設・宿泊・通信などが隠れたホットスポットとして浮上する。2012-13年から2022-23年にかけ炭素集約度は低下し、Scope3で最大34.4%減。スコープ選択がリスク評価と脱炭素優先順位を左右することを示す。
English
This paper estimates the carbon intensity of Indian bank loans using an EEIO framework with scope-disaggregated, bottom-up sector intensities. Under Scope 1, power-sector exposure makes public-sector banks the highest-intensity lenders; under final-energy accounting this premium largely vanishes, while Scope 3 reveals construction, hospitality and telecom as hidden hotspots. Loan carbon intensity fell 2012-13 to 2022-23, most sharply under Scope 3 (-34.4%). Scope choice materially determines which banks appear high-risk.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本の金融機関がScope3投融資排出（PCAF準拠）を開示する際、データ制約下でのEEIOベース推計は実務的な代替手法として参考になる。SSBJ・有報での投融資先排出開示の議論にも示唆を与える。
In the global GX context
Directly relevant to PCAF-aligned financed-emissions disclosure and climate-risk supervision under TCFD/ISSB. Demonstrates that scope selection is a material methodological choice for banks' transition-risk assessments, offering a scalable baseline for data-scarce emerging markets.
👥 読者別の含意
🔬研究者:スコープ選択が銀行の炭素集約度ランキングをどう反転させるかを実証した、投融資排出推計の方法論的ベンチマーク。
🏢実務担当者:データ不足環境でPCAF対応の投融資先排出ベースラインをEEIOで構築する際の実務的参考になる。
🏛政策担当者:気候リスク監督においてスコープ定義の標準化が不可欠であることを示す、規制設計への示唆。
📄 Abstract（原文）
Indian banks remain among the least scrutinised sources of financed emissions despite their lending portfolios carrying a substantial carbon burden. This paper provides scope-disaggregated estimates of the carbon intensity of Indian bank loans using the Environmentally Extended Input-Output (EEIO) framework. Unlike prior studies, we construct sector-specific emission intensities from the ground up to produce estimates that are transparent, reproducible, and resistant to greenwashing. The choice of emissions scope turns out to matter enormously. Under Scope 1, the electricity sector dominates measured emissions, and Public-Sector Banks (PSBs), with their heavy exposure to power generation, record the highest carbon intensity of loans (CIL). Under final energy emissions (Scope 1 + Scope 2 minus electricity sector), that PSB premium largely disappears as emissions are redistributed to end-use sectors. Under Scope 3 (supply chain emissions), seemingly low-carbon sectors such as construction, hospitality, telecommunications emerge as hidden hotspots. Across all three approaches, CIL declined meaningfully between 2012-13 and 2022-23, with the sharpest fall under Scope 3 (34.4 per cent, from 175.7 to 115.2 tCO₂ per crore). These findings carry direct implications for climate risk supervision. Scope selection is not a technical footnote - it determines which banks appear high-risk and how decarbonisation strategies are prioritised. For financial institutions operating in data-scarce environments, the EEIO approach offers a scalable, verifiable baseline for financed emissions disclosure, one that India's evolving climate finance framework urgently needs.
🔗 Provenance — このレコードを発見したソース
- openaire https://doi.org/10.2139/ssrn.7416178first seen 2026-11-05 04:24:54 · last seen 2026-11-06 04:23:26
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