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Profitability Impact Of Reducing Coal Lending Exposure: A Scenario Analysis of Bank Permata's Sample Loan Portfolio

石炭融資エクスポージャー削減の収益性への影響:Bank Permataのサンプルローン・ポートフォリオのシナリオ分析 (AI 翻訳)

Aditya Nugraha, Yunieta Anny Nainggolan

Journal Integration of Management Studiesプレプリント2025-08-17#トランジション・ファイナンス
DOI: 10.58229/jims.v3i2.399
原典: https://doi.org/10.58229/jims.v3i2.399

🤖 gxceed AI 要約

日本語

インドネシアのBank Permataを対象に、石炭セクターからの融資段階的削減が収益性に与える影響をシナリオ分析で評価。短期的には金利収入減少が見込まれるが、長期的には規制リスク低減やグリーンセクターへの再配分による利益維持が可能と示唆。新興市場銀行向けの再現可能なモデリング枠組みを提供。

English

This study evaluates the profitability impact of phasing out coal lending for Bank Permata, an Indonesian bank, using scenario analysis. Short-term declines in interest income are projected, but long-term benefits include reduced regulatory risk and potential gains from reallocating to green sectors. It provides a replicable framework for emerging market banks to assess transition risks.

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

日本では、金融庁の気候変動対応やグリーン・トランジション・ファイナンスの推進が進む中、本論文のシナリオ分析手法は、国内銀行が石炭関連融資の削減戦略を検討する際の参考となる。特に、収益性と規制リスクのトレードオフを定量的に示す点が実務上有用。

In the global GX context

This paper contributes to the global discourse on transition finance by providing a quantitative framework for banks in emerging markets to assess the financial impact of coal phase-out. It aligns with TCFD and ISSB expectations for scenario analysis and offers insights for banks navigating the energy transition under growing regulatory and investor pressure.

👥 読者別の含意

🔬研究者:Provides a replicable scenario-based modeling framework for quantifying financial effects of coal phase-out in emerging market banking.

🏢実務担当者:Offers a practical approach for banks to evaluate profitability impacts and mitigation strategies when reducing coal lending exposure.

🏛政策担当者:Highlights the need for clear green taxonomy and transition pathways to support banks in reallocating capital without undermining financial stability.

📄 Abstract(原文)

The global shift toward a low-carbon economy has intensified regulatory, market, investor, and societal pressures on banks to align lending portfolios with sustainable finance principles. In Indonesia, where coal remains central to the energy mix, banks face a strategic trade-off between sustaining profitability from coal financing and complying with green taxonomy requirements. This study evaluates the profitability implications of the coal sector phase-out for Bank Permata, a leading Indonesian commercial bank, and examines mitigation strategies. The analysis integrates Signaling Theory, Resource Dependence Theory, Stakeholder Theory, and Sustainable Finance to frame the strategic, risk, and stakeholder considerations in portfolio reallocation. A quantitative scenario analysis was applied to four publicly listed coal companies with existing credit facilities at Bank Permata, which were selected as a sample. Using a profit planning approach, financial projections were developed for income statements, balance sheets, and cash flows based on public disclosures and validated assumptions. Results were compared across a baseline (no phase out) and three phase out scenarios, with the most stringent targeting zero exposure by 2030. Findings indicate that phasing out in the short term will affect declines in interest income, driven by reduced loan balances and yields, but highlight long-term benefits through reduced regulatory non-compliance risk and lower reputational exposure to transition risks. Potential losses can also be mitigated by reallocating to green taxonomy-aligned sectors with competitive yields. The research offers a replicable scenario-based modeling framework for quantifying the financial effects of coal phase-out strategies in emerging market banking. It underscores the importance of strategic portfolio realignment, diversification into sustainable sectors, and strengthened ESG risk assessments to maintain profitability while supporting national and global sustainability goals.

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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。