Lesson 4.1: Climate-Related Financial Risks

01

Overview

Where This Lesson Fits

This is the first of six lessons in Module 4: Green Finance Products and Services. It establishes the conceptual foundation for understanding how climate change creates financial risk, providing the taxonomy and transmission frameworks that every subsequent lesson builds upon.

The lesson progresses from basic risk classification (physical, transition, liability) through the channels by which climate events propagate into financial losses, to the concept of materiality that determines which risks demand immediate action.

Learning Outcomes

Classify climate risks into physical, transition, and liability categories with precise sub-classifications
Map transmission channels linking climate events to financial losses through credit, market, operational, and liquidity pathways
Distinguish short-, medium-, and long-term risk horizons and their implications for portfolio management
Apply double materiality (financial vs impact) to sectoral analysis across ASEAN economies
Assess Vietnam Mekong Delta climate vulnerability for bank portfolios using structured frameworks

Prerequisites

None. This is the Foundation level entry point for Module 4. No prior knowledge of climate science or risk management is assumed.

02

Slide Deck

Lecture Slides (33 Slides)

Download Slide Deck (PDF)

03

Foundation Level

Physical Risks

Acute Physical Risks

Event-driven hazards that cause immediate damage to assets, infrastructure, and supply chains. These include typhoons and cyclones, riverine and coastal flooding, wildfires, heatwaves, and severe storms. Their financial impact is concentrated but can be catastrophic for exposed portfolios.

Typhoons and cyclones — wind damage, storm surge, rainfall-induced flooding
Flooding — riverine overflow, flash floods, coastal inundation from storm surge
Wildfires — direct asset destruction, air quality impacts on productivity
Heatwaves — labor productivity losses, increased energy demand, crop failure

Chronic Physical Risks

Long-term shifts in climate patterns that gradually erode asset values and economic productivity. These risks are slower-moving but often more pervasive and harder to reverse.

Sea-level rise — coastal real estate devaluation, infrastructure retreat costs
Temperature shift — agricultural yield changes, cooling cost increases, species migration
Precipitation changes — drought frequency, water scarcity, altered hydropower output

ASEAN ExampleTyphoon Rai (Super Typhoon Odette) struck the Philippines in December 2021, causing $1.1 billion in insured losses and an estimated $2.1 billion in total economic damage. Over 400 deaths, 2 million homes damaged, and severe disruption to agricultural output in Visayas and Mindanao.

Transition Risks

Risks arising from the adjustment toward a lower-carbon economy. The speed, scale, and coordination of the transition determine the magnitude of financial losses.

Five Transition Risk Channels

Policy and Legal — Carbon pricing mechanisms (taxes, ETS), regulations mandating emissions reductions, energy efficiency standards, land-use restrictions
Technology — Disruptive clean technologies rendering existing assets obsolete: renewable energy cost declines, battery storage breakthroughs, green hydrogen scaling
Market — Shifts in supply and demand: changing consumer preferences, commodity price volatility, reduced demand for fossil fuel products
Reputation — Stakeholder perception shifts: investor divestment campaigns, consumer boycotts, employee recruitment challenges for high-carbon firms
Behavioral — Changes in individual and institutional behavior: ESG-driven capital allocation, green procurement policies, lifestyle shifts reducing carbon-intensive consumption

ASEAN ExampleThe EU Carbon Border Adjustment Mechanism (CBAM), phasing in from 2026, will impose carbon costs on imports of cement, iron, steel, aluminum, fertilizers, electricity, and hydrogen. ASEAN exporters to the EU — particularly Vietnam's steel sector and Thailand's cement industry — face significant cost increases if they cannot demonstrate low-carbon production processes.

Liability Risks

The emerging third category of climate risk, increasingly recognized as distinct from transition risks. Liability risks arise when parties seek compensation for climate-related losses through legal or regulatory action.

Three Sub-categories

Litigation — Lawsuits against emitters for climate damages, failure to disclose climate risks, or breach of fiduciary duty in climate-related investment decisions
Adaptation failure — Legal liability for failing to adapt infrastructure, products, or services to known climate risks (e.g., building codes in flood zones)
Greenwashing — Regulatory enforcement and civil litigation against misleading environmental claims in financial products, corporate reporting, or marketing

ASEAN ExampleIn 2021, a Dutch court ordered Royal Dutch Shell to reduce its CO2 emissions by 45% by 2030 relative to 2019 levels, establishing a precedent that major emitters owe a duty of care to affected populations. While the case originated in Europe, it signals growing global litigation risk for fossil fuel companies and their financiers, including ASEAN-based institutions with upstream oil and gas exposure.

Transmission Channels

Transmission channels describe how climate events propagate into financial losses. Understanding these channels is essential for quantifying and managing climate-related portfolio exposure.

Four Financial Risk Channels

Credit risk — Climate events reduce borrower income or collateral values, increasing probability of default (PD) and loss given default (LGD). Example: drought destroys crops, farmer cannot repay agricultural loan, land value declines as collateral.
Market risk — Abrupt repricing of securities when climate risks are suddenly recognized. Example: stranded asset revaluation in fossil fuel equities, sovereign bond repricing for climate-vulnerable nations.
Operational risk — Climate disrupts business operations directly. Example: flooding damages bank branch networks, data centers lose cooling capacity during heatwaves, supply chains break during extreme weather.
Liquidity risk — Climate events trigger simultaneous demand for liquidity across the system. Example: mass insurance claims after a typhoon, deposit withdrawals in affected regions, fire-sale of climate-exposed assets.

ASEAN ExampleDuring the 2011 Thailand floods, the worst in 70 years, over 800 factories in industrial estates north of Bangkok were inundated. Global supply chains for hard drives and automotive parts were disrupted for months. Thai banks faced simultaneous credit risk (non-performing industrial loans), operational risk (branch closures), and liquidity risk (deposit withdrawals in flood-affected provinces). Insured losses exceeded $15 billion.

Time Horizons

Climate risks operate across fundamentally different timescales, creating a mismatch with traditional financial planning horizons. Mark Carney's "tragedy of the horizon" describes how the catastrophic impacts of climate change will be felt beyond the traditional horizons of most actors.

Short-term (0–3 years)

Acute physical events and sudden policy shocks. Relevant to: trading books, insurance underwriting, annual budgets. Examples: typhoon season losses, new carbon tax implementation, regulatory enforcement actions.

Medium-term (3–10 years)

Transition risk acceleration and chronic physical onset. Relevant to: corporate loan books, infrastructure investment, strategic planning. Examples: technology disruption cycles, CBAM full implementation, accumulating sea-level rise impacts.

Long-term (10–30+ years)

Systemic transformation and potential tipping points. Relevant to: sovereign bonds, pension funds, real estate, insurance solvency. Examples: AMOC slowdown, West Antarctic ice sheet collapse, mass climate migration, stranded nation risk.

ASEAN ExampleVietnam's 30-year infrastructure bonds financing Mekong Delta transport and energy projects face compounding risk across all three horizons: immediate typhoon damage (short-term), saltwater intrusion reducing agricultural collateral value (medium-term), and potential uninhabitability of low-lying areas under high-warming scenarios (long-term).

Materiality

Materiality determines which climate risks matter enough to require action. Three competing frameworks define materiality differently, with major implications for risk management scope.

Financial Materiality (Outside-In)

How climate affects the firm's enterprise value. This is the ISSB/IFRS approach: a climate risk is material if it could reasonably be expected to influence investor decisions. Focus: financial performance, cash flows, asset values.

Impact Materiality (Inside-Out)

How the firm's activities affect the climate and broader society. This is the GRI approach: a firm's contribution to climate change is material regardless of financial impact. Focus: emissions, resource use, ecological damage.

Double Materiality (Both Directions)

The EU CSRD approach combines both lenses. A climate risk is material if it affects the firm's value (financial materiality) or if the firm's activities affect climate outcomes (impact materiality). This is the most comprehensive framework and the direction of ASEAN regulatory convergence.

ASEAN ExampleA Vietnamese coal-fired power plant may face limited short-term financial materiality (domestic coal demand remains strong), but high impact materiality (significant CO2 emissions affecting global climate). Under double materiality, both dimensions require disclosure and risk management. As ASEAN regulators increasingly adopt EU-aligned standards, the scope of material climate risks will expand substantially for the region's financial institutions.

04

Intermediate Level

Sectoral Exposure Mapping

Systematic assessment of how physical and transition risks affect different economic sectors. Sectors are ranked by exposure to construct a 10-sector risk profile.

High-Exposure Sectors

Sector	Physical Risk	Transition Risk	Overall
Energy (fossil fuels)	High	Very High	Very High
Agriculture	Very High	Medium	Very High
Real Estate	High	High	High
Transport	Medium	High	High
Manufacturing	Medium	High	High
Tourism	High	Medium	High
Fisheries & Aquaculture	Very High	Low	High
Mining	Medium	High	Medium-High
Financial Services	Low	Medium	Medium
Technology	Low	Low	Low

Compound Risk Analysis

Climate risks rarely occur in isolation. Compound risk analysis examines how multiple climate drivers interact to produce non-linear financial losses that exceed the sum of individual risk assessments.

Interaction Types

Physical + Physical — Drought followed by flooding on hardened soil; heatwave + wildfire cascades
Physical + Transition — Drought reduces agricultural output while a new carbon tax raises input costs, creating a margin squeeze
Transition + Transition — Simultaneous technology disruption (EVs) + policy tightening (emissions standards) accelerating stranded asset creation
Feedback loops — Climate damage reduces fiscal capacity to invest in adaptation, increasing future damage severity

ASEAN ExamplePhilippine agriculture faces compound risk: a La Nina-driven typhoon season (acute physical) coinciding with rising fertilizer costs from carbon pricing (transition), while drought in alternative growing regions drives food import prices higher (market). For agricultural lenders, the combined probability of default far exceeds independent risk estimates.

Risk Heatmap Construction

A 10-sector by 6-risk-type matrix provides a visual summary of portfolio-level climate exposure. Each cell is scored 1–5 based on scenario data and expert judgment.

Methodology

Define sectors (rows): Energy, Agriculture, Real Estate, Transport, Manufacturing, Tourism, Fisheries, Forestry, Mining, Financial Services
Define risk types (columns): Acute Physical, Chronic Physical, Policy Transition, Technology Transition, Market Transition, Litigation
Score each cell 1–5 using NGFS scenario data, country-specific climate projections, and regulatory trajectory analysis
Weight cells by portfolio exposure (loan book concentration) to derive portfolio-level risk scores
Identify red zones (score 4–5) requiring immediate risk management attention

Portfolio-Weighted Risk Score

$$R_{\text{portfolio}} = \sum_{s=1}^{10} \sum_{r=1}^{6} w_s \cdot \text{Score}_{s,r}$$

where $w_s$ is the portfolio weight of sector $s$ and $\text{Score}_{s,r}$ is the 1–5 risk score for sector $s$, risk type $r$.

Worked Example: ASEAN Bank Portfolio

Apply the Climate Value-at-Risk framework to a hypothetical ASEAN commercial bank's loan portfolio. The model adjusts baseline probability of default using a climate sensitivity parameter.

Climate Value-at-Risk by Sector

$$\text{Climate VaR}_{\text{sector}} = \text{PD}_{\text{base}} \times (1 + \Delta T \cdot \beta_{\text{climate}}) \times \text{LGD} \times \text{EAD}$$

Parameter Definitions

$\text{PD}_{\text{base}}$ — Baseline probability of default (historical, non-climate-adjusted)
$\Delta T$ — Temperature change scenario (e.g., +1.5°C, +2.0°C, +3.0°C)
$\beta_{\text{climate}}$ — Climate sensitivity coefficient (sector-specific, estimated from NGFS damage functions)
$\text{LGD}$ — Loss given default (recovery rate adjustment for climate-damaged collateral)
$\text{EAD}$ — Exposure at default (outstanding loan balance at the sector level)

Example Calculation

For the Agriculture sector under a +2.0°C scenario:

Agriculture Climate VaR

$$\text{Climate VaR}_{\text{agri}} = 0.05 \times (1 + 2.0 \times 0.35) \times 0.60 \times \$300\text{M} = \$15.3\text{M}$$

Compare to non-climate baseline: $0.05 \times 0.60 \times \$300\text{M} = \$9.0\text{M}$. The climate adjustment adds $6.3M (70% increase) in expected losses.

05

PhD Extension

Risk Taxonomy Evolution

The taxonomy of climate-related financial risks has evolved through successive institutional frameworks, each expanding scope and granularity.

Institutional Timeline

Year	Framework	Contribution
2015	Carney / FSB	"Tragedy of the Horizon" speech; established physical, transition, liability trichotomy; created TCFD
2017	TCFD	Standardized four-pillar disclosure framework; mainstream legitimation of climate risk
2019	NGFS	Central bank scenario framework; quantitative pathways linking climate to macro-financial variables
2023	TNFD	Extended taxonomy to nature-related risks; LEAP approach; biodiversity-finance nexus
2024	ISSB	IFRS S2 global baseline standard; integration with financial accounting; mandatory in 20+ jurisdictions

Research QuestionHow has the expanding scope of climate risk taxonomy (from Carney's three categories to TNFD's nature-inclusive framework) affected the measurability and comparability of risk assessments across jurisdictions?

Endogenous vs Exogenous Risk

Battiston et al. (2017) demonstrated that climate risk is not purely exogenous. Financial network structure creates endogenous amplification: initial climate shocks propagate through interbank exposures, portfolio overlaps, and fire-sale dynamics, creating losses far exceeding the direct physical or transition impact.

Network Propagation Model (Battiston et al. 2017)

$$R_i(t+1) = R_i(t) + \sum_{j} w_{ij} \cdot \Delta V_j(t)$$

where $R_i(t)$ is the risk exposure of institution $i$ at time $t$, $w_{ij}$ is the network weight (exposure of $i$ to $j$), and $\Delta V_j(t)$ is the change in value of institution $j$'s portfolio due to climate impacts.

Key Insights

Direct climate losses may be manageable, but network amplification can create systemic crises
Portfolio concentration in climate-exposed sectors creates correlated defaults
Fire-sale externalities emerge when multiple institutions simultaneously deleverage from the same assets
The financial system's network structure is itself a source of climate risk

Research QuestionUnder what conditions does network amplification of climate shocks exceed the original exogenous loss, and how does ASEAN interbank network topology compare to EU networks in terms of contagion vulnerability?

Network Propagation Models

Three mechanisms through which climate risk propagates in financial networks:

1. Contagion

Direct counterparty exposure: when institution $j$ defaults due to climate losses, institution $i$ loses its claims on $j$. The cascade continues through chains of interbank lending, derivatives counterparty risk, and trade credit networks.

2. Fire Sales

Indirect propagation through asset markets: institutions forced to sell climate-exposed assets depress prices, imposing mark-to-market losses on all holders of similar assets. This creates a common exposure channel even without direct bilateral links.

3. Amplification

Positive feedback loops between contagion and fire sales. Counterparty losses trigger margin calls, forcing further asset sales, which depress prices, causing more counterparty losses. The result is non-linear loss escalation that can transform a sector-specific climate shock into a system-wide financial crisis.

Research QuestionCan early-warning indicators based on network centrality measures (e.g., DebtRank, eigenvector centrality) identify systemically important climate-exposed institutions before cascade failures materialize?

Climate Litigation as Systematic Risk

Setzer and Higham (2023) document 2,341 climate litigation cases across 50+ jurisdictions, establishing litigation as a systematic rather than idiosyncratic risk. The Grantham Research Institute database shows exponential growth since 2015.

Litigation Categories

Climate-aligned — Cases seeking stronger climate action: emission reduction orders, policy challenges, corporate accountability
Climate-obstructive — Cases challenging climate regulations: ETS validity, renewable energy mandates, stranded asset compensation
Disclosure-based — Shareholder suits for inadequate climate risk disclosure: securities fraud, breach of fiduciary duty
Greenwashing — Consumer and regulatory actions against misleading environmental claims in financial products

Financial System Implications

Litigation risk creates a contingent liability that is difficult to quantify but potentially enormous. The Shell ruling (2021) demonstrated that courts can mandate emissions reductions with binding financial consequences. For financial institutions, litigation risk manifests through: (1) direct liability for portfolio companies, (2) failure to disclose climate risks to investors, (3) greenwashing in sustainable finance products.

Research QuestionHow should financial institutions model the probability distribution of climate litigation outcomes, and what is the appropriate capital buffer for this emerging systematic risk in ASEAN jurisdictions?

06

Quantitative Lab

Climate Risk Heatmap Construction

Dataset NGFS IIASA Scenario Explorer + World Bank Climate Change Knowledge Portal Tools Python pandas seaborn Output 10-sector x 6-risk-type heatmap (annotated, exportable PDF)

Python Pseudocode

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

# Define sectors and risk types
sectors = ['Energy', 'Agriculture', 'Real Estate', 'Transport',
           'Manufacturing', 'Tourism', 'Fisheries', 'Forestry',
           'Mining', 'Financial Services']
risk_types = ['Acute Physical', 'Chronic Physical',
              'Policy Transition', 'Tech Transition',
              'Market Transition', 'Litigation']

# Load NGFS scenario data and score each cell 1-5
scores = build_risk_matrix(ngfs_data, wb_climate_data)
df = pd.DataFrame(scores, index=sectors, columns=risk_types)

# Visualize as annotated heatmap
fig, ax = plt.subplots(figsize=(12, 8))
sns.heatmap(df, annot=True, cmap='YlOrRd',
            vmin=1, vmax=5, linewidths=0.5, ax=ax)
ax.set_title('Climate Risk Heatmap: ASEAN Banking Sector')
plt.savefig('climate_risk_heatmap.pdf', bbox_inches='tight')
            

Lab Steps

Download NGFS Phase IV scenario data for three ASEAN countries (Vietnam, Thailand, Philippines) from the IIASA Scenario Explorer
Extract World Bank climate indicators (temperature projections, precipitation changes, sea-level rise) from the Climate Change Knowledge Portal
Construct a 10x6 scoring matrix by combining scenario projections with sectoral vulnerability assessments. Score each cell 1–5.
Apply portfolio weights based on a hypothetical ASEAN bank loan book to compute the portfolio-weighted risk score: $R_{\text{portfolio}} = \sum_s \sum_r w_s \cdot \text{Score}_{s,r}$
Visualize as annotated heatmap using seaborn. Identify the top 3 sector-risk combinations requiring priority risk management. Export as PDF.

Data Sources

NGFS Scenario Explorer World Bank Climate Portal NGFS Scenarios Portal

07

Case Study: Vietnam — Mekong Delta

Mekong Delta Climate Vulnerability & Bank Portfolio Assessment

Geographic Context

The Mekong Delta encompasses 12 provinces in southern Vietnam, home to approximately 17 million people. It produces 50% of national rice output and 90% of aquaculture exports, making it Vietnam's agricultural heartland and one of the most climate-exposed economic zones in Southeast Asia.

Climate Threats

Saltwater intrusion — Currently reaching 60–90km inland during dry seasons; projected to extend 40–50km further by 2050
Sea-level rise — Under a 1-meter rise scenario (plausible by 2100), approximately 40% of the Delta is at risk of inundation
Increased flooding — Upstream hydropower development combined with more intense monsoon rainfall increases peak flood frequency
Temperature increase — Projected +1.5–2.5°C by 2050, reducing rice yields by 10–20% in affected areas

Bank Portfolio Exercise

Assess the climate risk exposure of a hypothetical Vietnamese commercial bank with the following loan portfolio concentration in the Mekong Delta region:

30%

Agriculture

20%

Real Estate

15%

Manufacturing

15%

Retail

10%

Energy

10%

Services

Three-Horizon Assessment Framework

For each sector above, students assess climate risk across three time horizons:

Horizon	Timeframe	Key Risks	Assessment Focus
Short	0–3 years	Typhoon damage, seasonal flooding, acute saltwater intrusion events	PD increase for agricultural loans, collateral damage, insurance gaps
Medium	3–10 years	Progressive saltwater intrusion, transition to saline-tolerant crops, infrastructure adaptation needs	Sectoral reallocation, real estate repricing, technology investment requirements
Long	10–30 years	Permanent inundation risk, mass relocation, fundamental economic transformation	Stranded real estate, sovereign risk implications, portfolio exit strategy

Assessment Rubric

Criterion	Weight	Excellent (5)	Adequate (3)	Insufficient (1)
Risk identification	25%	All three risk types identified per sector with specific examples	Two risk types per sector, general examples	Single risk type, no sector differentiation
Transmission mapping	25%	Clear causal chains from climate event to financial loss for each channel	Partial transmission chains, some channels missing	No transmission analysis
Time horizon analysis	20%	Distinct risk profiles across all three horizons with quantitative estimates	Two horizons addressed, qualitative analysis	Single time horizon
Materiality assessment	15%	Double materiality applied with sector-specific financial and impact analysis	Single materiality lens	No materiality discussion
Portfolio recommendations	15%	Specific, actionable recommendations with risk mitigation strategies per sector	General recommendations	No recommendations

08

Key Concepts

Glossary (15 Terms)

Acute physical risk: Event-driven climate hazards causing immediate damage: typhoons, floods, wildfires, heatwaves. Characterized by sudden onset and concentrated impact.
Chronic physical risk: Long-term shifts in climate patterns that gradually erode economic value: sea-level rise, sustained temperature increases, changing precipitation patterns.
Compound risk: The interaction of multiple climate risk drivers producing non-linear financial losses exceeding the sum of individual risks assessed independently.
Credit risk: The risk of financial loss from a borrower's failure to repay. Climate-adjusted credit risk incorporates increased PD and LGD from climate-related income or collateral impairment.
Double materiality: The EU CSRD framework requiring assessment of both how climate affects firm value (financial materiality) and how the firm affects climate outcomes (impact materiality).
Financial materiality: The ISSB/IFRS approach: a climate risk is material if it could reasonably influence investor decisions about enterprise value. Outside-in perspective.
Impact materiality: The GRI approach: a firm's climate impacts are material regardless of whether they affect the firm's own financial performance. Inside-out perspective.
Liability risk: Legal and regulatory risk from climate-related litigation, adaptation failure claims, or greenwashing enforcement actions against firms or their financiers.
Liquidity risk: Risk that climate events trigger simultaneous liquidity demands: mass insurance claims, deposit withdrawals, fire-sale of climate-exposed assets across the system.
Market risk: Risk of financial loss from sudden repricing of securities when climate risks are recognized: stranded asset devaluation, sovereign bond repricing, commodity price shocks.
Operational risk: Risk of loss from climate-related disruption to business operations: physical damage to infrastructure, supply chain failures, workforce displacement.
Physical risk: The umbrella category for all climate-related risks arising from the physical impacts of climate change, encompassing both acute events and chronic shifts.
Stranded assets: Assets that have suffered unanticipated or premature write-downs, devaluations, or conversion to liabilities due to climate-related policy, technology, or market changes.
Transition risk: Financial risks arising from the process of adjusting toward a low-carbon economy, including policy, technology, market, reputation, and behavioral channels.
Transmission channel: The mechanism by which a climate event propagates into financial loss: credit risk, market risk, operational risk, or liquidity risk pathways.

09

References

Key References

2015 Carney, M. "Breaking the Tragedy of the Horizon: Climate Change and Financial Stability." Speech at Lloyd's of London, Bank of England.
2017 Battiston, S., Mandel, A., Monasterolo, I., Schuetze, F., & Visentin, G. "A Climate Stress-Test of the Financial System." Nature Climate Change, 7(4), 283–288.
2024 NGFS. "Climate Scenarios for Central Banks and Supervisors: Phase IV." Network for Greening the Financial System.
2021 ADB. "Asian Development Outlook: Financing a Green and Inclusive Recovery." Asian Development Bank.
2023 Setzer, J. & Higham, C. "Global Trends in Climate Change Litigation: 2023 Snapshot." Grantham Research Institute, London School of Economics.

Supplementary References

2017 TCFD. "Final Report: Recommendations of the Task Force on Climate-Related Financial Disclosures." Financial Stability Board.
2024 ISSB. "IFRS S2: Climate-related Disclosures." International Sustainability Standards Board.
2016 Dietz, S., Bowen, A., Dixon, C., & Gradwell, P. "'Climate Value at Risk' of Global Financial Assets." Nature Climate Change, 6, 676–679.

10

Downloads

Materials

Download Slide Deck (PDF)

Data Resources

NGFS Scenario Explorer World Bank Climate Portal NGFS Scenarios Portal