Water-related financial risks are increasingly recognised as critical threats to economic and financial stability due to climate change, ecosystem degradation, and sectoral dependencies. This chapter discusses how supervisors can apply the OECD three-step framework - risk identification, economic analysis, and financial assessment - to map exposures across credit, market, liquidity, and operational channels. Systemic risks may accumulate, due to interconnections, common exposures, and feedback loops between institutions and sectors. This underscores the need for scenario analysis, inter-agency collaboration, and forward-looking supervision to strengthen resilience in a water-stressed world.
Embedding Water‑related Risks in Financial Stability Frameworks
Abstract
This chapter presents practical tools and approaches to apply the three-step analytical framework provided in the OECD Supervisory Framework For Assessing Biodiversity-Related Risks (OECD, 2023[1]) to help financial supervisors and central banks understand water-related financial risks. These three steps are as follows:
1. Risk identification and prioritisation, to identify and rank risks based on their potential impact and likelihood.
2. Economic risk assessments, to assess the potential economic effects and risks that can stem from these exposures.
3. Financial risks assessments, to explore financial risks stemming from the exposure to sources of physical and transition risks, notably through financed activities.
Water-related risks can impact a large range of economic sectors, including those not traditionally considered water-intensive. This depends on the specific country context, including composition of the economy and exposure and vulnerability to water-related risks. Nevertheless, certain sectors tend to be particularly exposed to water-related risks, given their higher dependency or vulnerability.
Risk identification is the foundational step in understanding the potential materiality of nature-related risks for financial authorities. According to the OECD Supervisory Framework on Biodiversity-related risks, a robust process for identifying nature-related financial risks involves three steps, which are supported by guiding questions detailed in Box 4.1:
Assessing economic dependencies and impacts on nature and ecosystem services;
Identifying the economic sectors most exposed to or responsible for these impacts; and
Determining which ecosystems underpin these services and are at risk of degradation.
Financial institutions and regulators can adopt either top-down or bottom-up approaches for risk identification, depending on their objectives and the level of granularity required. The OECD’s Framework adopts a top-down method, using aggregate sectoral data to pinpoint areas of potential concern. This can support macroprudential oversight by identifying broad concentrations of risk exposure across sectors (OECD, 2023[1]). However, bottom-up approaches can also provide granular insights by linking firm-level data with geospatial information on ecosystem conditions and water stress.
A hybrid approach may therefore be best suited to meet supervisory needs and to provide a more nuanced perspective, as both approaches have trade-offs. Top-down assessments offer broad comparability but can lack precision. Notably, while tools like ENCORE provide global average materiality ratings, financial authorities also require geospatial tools to identify location-specific risks, particularly for water.
Bottom-up assessments are more specific but are often constrained by data availability and consistency. Accurate risk assessment requires detailed data on water availability, climate trends, and sectoral economic activity. Depending on the level of granularity, a bottom-up approach will require collaboration with government agencies, research institutions, and data providers to access high-resolution datasets and develop reliable proxies.
Impacts and dependencies assessments:
What is the exposure of the financial system, in terms of impacts and dependencies, to water through ecosystem services?
Do the impacted ecosystem services differ from those depended on?
Economic sector identification and prioritisation (financial materiality perspective)
Direct economic sectors (immediately involved in the primary economic activity being analysed)
Which are the most relevant direct economic sectors?
Independent of the impacts and dependency assessment, what is the economic relevance of primary economic sectors?
Indirect economic sectors (sectors that support or supply goods and services to the direct sectors)
Which are the most relevant indirect economic sectors?
What is the share of imported commodities compared to domestic production?
What is the aggregate financial relevance of identified economic sectors and the sectoral concentration?
Geographic scope
Where are direct and indirect economic activities located?
For indirect economic activities, where are their upstream value chains located?
Domestic level
How is the domestic policy environment, technological availability, consumer preferences and public sentiment towards transition risks?
Are there relevant legal local disputes or non-judicial cases that concern the protection of water-related ecosystems and could represent a source of litigation risk?
International level
What is the geographic concentration for imported impacts, per country? (Consider both sectors and commodities)
What are the regional/sectoral policies relevant for nature, technological availability, consumer preferences and public sentiment towards nature (transition risks) in other countries?
Are there relevant legal disputes or non-judicial cases in other countries that concern the conservation of nature and could represent a source of risk (litigation risk)?
Freshwater ecosystem identification
What are the most important freshwater-ecosystem services for the economy?
What are the main drivers of degradation of freshwater-ecosystems (focused on impacts and dependencies)?
What is the current state of different freshwater-ecosystems (related to the identified ecosystem services)?
Source: Adapted from (OECD, 2023[1]).
4.1.1. Economic activities both impact and depend on freshwater systems
The economic dependencies on water are vast but often underestimated. Agriculture accounts for approximately 70% of global freshwater withdrawals, making it highly vulnerable to declining water availability (FAO, 2024[2]). The energy sector, particularly hydropower and thermal power generation, is directly dependent on reliable water supply. Manufacturing and industrial sectors require stable access to water for production, cooling, and processing. Disruptions to water supply, whether from climate-induced droughts, regulatory restrictions, or pollution crises, can lead to supply chain failures, rising costs, and financial losses across multiple sectors.
At the same time, the impacts of economic activity on water security are intensifying risks for ecosystems and societies. The loss of wetlands, which provide critical functions such as flood protection, groundwater recharge, and pollution filtration, erodes natural resilience and increases reliance on costly infrastructure solutions (Bhowmik, 2020[3]). Over-abstraction of groundwater not only depletes aquifers but also triggers cascading economic and environmental consequences, including reduced agricultural productivity, subsidence, and ecosystem collapse (Fessahaye et al., 2025[4]; Faunt et al., 2016[5]). The sectors that have the largest impacts on water resources and degradation of freshwater ecosystems, through consumption or pollution, are likely to be those most exposed to stringent controls and will therefore be exposed to economic and financial risks (NGFS, 2024[6]).
Assessing impacts and dependencies on water and freshwater ecosystems is a first step to understanding exposure to physical and transition risks. A growing number of tools have emerged to help financial authorities understand how economic sectors depend on and impact nature. Among the most widely used is the ENCORE (Exploring Natural Capital Opportunities, Risks and Exposure) tool which provides structured assessments of sectoral dependencies and impacts on ecosystem services, including water, based on ISIC classifications (ENCORE Partners, 2024[7]). Further tools are listed in Section 4.1.4.
ENCORE classifies 271 economic activities using ISIC codes. These are assessed against 25 ecosystem services defined by the UN System of Environmental-Economic Accounting Ecosystem Accounting (UN SEEA-EA) framework. Water-related ecosystem services include water supply, water purification services, water flow and regulation services, climate regulation services, and other regulating and maintenance service (UN, 2024[8]). This also includes flood mitigation services and storm mitigation services which are directly relevant to avoiding water-related hazards. ENCORE assigns "materiality scores" for each activity, distinguishing between direct and indirect dependencies or impacts (ENCORE Partners, 2024[7]).
Figure 4.1 and Figure 4.2 provide examples of ENCORE’s findings on sectoral water dependencies and impacts, respectively. The data shows that agriculture, textiles, and energy are among the most water-dependent sectors, while agriculture, extractives, and energy have the greatest impacts on water systems. Dependency scores assess the financial risks associated with disruptions to specific ecosystem services, while impact scores evaluate the potential consequences of production processes on natural resources (UNEP-WCMC, 2024[9]).
Note: The size of the flows represents the average rating scores of each sector’s dependencies. While this base allows users to compare materiality ratings for a given dependency across multiple economic sectors and activities, the ratings are not designed to enable comparisons across different ecosystem services.
Sectors follow ISIC classification, where manufacturing includes textiles.
Source: (ENCORE Partners, 2024[7]).
Note: The size of the flows represents the average rating scores of each sector’s pressures. While this base allows users to compare materiality ratings for a given pressures across multiple economic sectors and activities, the ratings are not designed to enable comparisons across different ecosystem services.
Source: (ENCORE Partners, 2024[7]).
Where there is significant overlap between impacts and dependencies from specific sectors, these sectors are exposed to both transition and physical risks stemming from degradation of freshwater ecosystems. In such instances, financial authorities may want to consider both risk sources concurrently due to their potentially interacting and compounding effects. For water, this notably concerns agriculture and energy which significantly impact and depend on water.
While ENCORE provides a view of upstream and downstream value chain links associated with an economic activity, it primarily focuses on direct impacts. As a result, water-related risks, particularly indirect risks that propagate through the value chain, may be underestimated. In addition, ENCORE provides global average materiality ratings, whereas the actual materiality of dependencies and impacts is likely to vary significantly based on the specific context, company and location that is assessed (UNEP-WCMC, 2024[9]). As such, sector assessments must be contextualised with additional data to improve accuracy.
4.1.2. Water-related risks are highly location specific
It is important to recognise that the materiality of water-related impacts and dependencies is highly context-specific. The same volume of water withdrawal may have minimal environmental impact in a water-abundant region but can be severely damaging in a water-scarce or degraded watershed. This underscores the need for a location-specific approach to water-related risk assessment that incorporates both physical availability and basin-level stress.
In this context, geographical location is a primary driver of exposure and vulnerability, particularly for sectors with limited operational flexibility, such as agriculture, mining, and food processing. For example, irrigated crops grown in arid regions may face far greater physical and regulatory risks than similar crops in temperate zones. The same industry may encounter vastly different water-related risks depending on its location’s hydrological conditions, regulatory frameworks, governance capacity, and water infrastructure quality. Indeed, ESG rating providers have started to look more closely into how the localised context of water risks can be integrated into the scoring methodologies (Molnar and Sasarean, 2021[10]).
However, focusing on direct exposure alone does not capture the full picture. Indirect exposure arises when downstream sectors rely on water-intensive inputs sourced from high-risk regions, for instance, textiles made from cotton grown in drought-prone areas. These indirect dependencies create transmission risks across supply chains and borders, often beyond the operational control or awareness of downstream actors. Multinational corporations and their global supply chains are increasingly exposed to water-related risks, but evidence suggests these risks are severely underestimated by the same corporations. According to CDP data, while 623 out of 3 163 companies (20%) reported USD 77 billion at risk due to water-related issues in supply chains, 60% of companies did not report to be presently assessing risks in their supply chains (CDP, 2024[11]).
Assessing geographical vulnerability to water-related risks is significantly more complex for indirect economies, which necessitate an evaluation of water vulnerabilities across the entire upstream value chain. This involves identifying potential risks, such as pollution or scarcity, at each stage of production, distribution, and sourcing. In addition, this means exploring diverse regulatory environments, with varying environmental policies and public sentiment. For example, non-compliance with water regulations can result in financial penalties, operational disruptions, and reputational damage. Moreover, negative public perception can lead to consumer boycotts, protests, or stricter regulations. The textile and apparel industry serves as a prime example, with manufacturing facilities in South Asia facing protests over water pollution and resource depletion (Greenpeace, 2011[12]; Restiani and Khandelwal, 2016[13]).
4.1.3. Freshwater ecosystem degradation amplifies risk exposure
The identification of water-related physical and transition risks is a challenging task. For physical risk, it is important to consider acute and chronic shocks and for transition risks, existing or announced water-related policies at a global regional or national level. This provides a starting point for developing scenarios.
In particular, the identification and prioritisation of ecosystems involves assessing the current and projected states of freshwater ecosystems, their geographical distribution, and their role in providing essential ecosystem services. The OECD Supervisory Framework for assessing nature-related risks advises taking the following three steps (OECD, 2023[1]):
identify the most relevant freshwater ecosystems services using the results of the impacts and dependencies assessment.
identify the main drivers of degradation and general threats to the integrity of the key ecosystem services
perform an assessment of the current and forecasted state of nature.
There is no agreed-upon means or easily identifiable metric for aggregating environmental data to assess ecosystem health or ecosystem degradation, meaning that nature-related scenarios will need to build on a large number of metrics and indicators. Translating the contributions of different ecosystem services into monetary units, which could then feed into economic models, is a task fraught with difficulties and shortcomings for the purpose of assessing nature-related risks.
One emerging approach to developing more integrated and actionable nature-related risk scenarios is to incorporate metrics like Total Water Storage (TWS), which captures changes across all major water stores and provides a more holistic view of ecosystem condition and hydrological resilience (Box 4.2).
Total Water Storage (TWS) is a comprehensive measure of all water stored above and below the land surface in a given area. TWS represents the full “wetness” of a river basin, region, or continent and is a key indicator for understanding water availability, flood/drought risk, and ecosystem health. TWS data gives clarity on where water is accumulating or disappearing. For example, they help distinguish between surface flooding and long-term groundwater depletion, which is essential for water management and disaster preparedness.
TWS includes the sum of the following components:
Surface water: Water in rivers, lakes, reservoirs, and wetlands
Soil moisture: Water held between soil particles in the root zone
Groundwater: Water stored in underground aquifers
Snow and ice: Water stored in snowpacks, glaciers, and ice sheets
Vegetation water: Water held within living plants and trees
Monitoring TWS captures both blue water (surface and groundwater) and green water (soil moisture, water in vegetation), providing a broader perspective on the entire terrestrial water cycle.
Advances in satellite technology, especially data from NASA’s GRACE and GRACE-FO missions, now allow scientists and policymakers to track TWS anomalies and long-term trends, revealing emerging risks driven by climate change, land use, and human intervention.
Financial authorities may encounter difficulties in identifying risks by themselves, as this may not be in their mandate, or they may have different levels of expertise. For this reason, it would be essential to involve environmental agencies, who already undertake such analyses and may have the capacity to complete the ecosystem identification and assessment steps outlined below. Similarly, where mandates permit, financial authorities could consider the creation of specialised departments within their institutions for nature-related assessments and follow-up on recommendations.
4.1.4. Data gaps obscure the full extent of water-related risks
Unlike carbon-related financial risks, which can be relatively standardised through emissions reporting, water-related risks are highly localised, sector-specific, and dependent on local hydrological conditions. Thus, granular and comparable data is crucial for understanding how the sources of water-related risks translate into economic and financial risks.
By leveraging combinations of data sources, alongside traditional financial analysis, financial authorities can start to build a more comprehensive view of a sector’s water-risk exposure. While no single dataset is perfect, together tools like ENCORE, CDP, EXIOBASE and the Water-related risk Filter offer complementary insights into different dimensions of water-related risks (from dependence on water resources to local basin conditions). These resources are helping to fill the information gap identified in supervisory exercises. They form a critical foundation for developing scenario analyses and risk metrics tailored to water-related financial risks.
The list below outlines some examples of data sources and tools, their capabilities, and their current limitations. A more comprehensive list is included in Annex A, section 6.2.3.
Sector-Level tools
Given the frequent lack of comprehensive data, identifying water-related risks at the sector or geographical level can be a more suitable approach. Financial supervisors can utilise databases and tools like ENCORE, Science Based Targets for Nature (SBTN), and EXIOBAS to assess sector water dependency.
ENCORE database, developed by Global Canopy, UNEP FI, and UNEP-WCMC, helps financial institutions assess the dependencies and impacts of economic activities on natural capital, including water. It identifies high-risk sectors by mapping 271 economic activities against 25 ecosystem services, including groundwater, surface water, and flood regulation services (ENCORE Partners, 2024[7]). However, ENCORE provides global-level sectoral insights, which do not capture location-specific water-related risks. This should be used as a starting point to understand generalised relationships between sectors and water-related ecosystems. The organisations behind ENCORE are working to continually update their approaches and have started incorporating value chains.
EXIOBASE is a multi-regional environmentally extended input-output database, tracking water use, pollution, and ecosystem impacts across 44 countries (Stadler et al., 2018[16]). It allows financial institutions to trace direct and indirect water-related risks across supply chains, offering insights into water footprints across sectors. Its limitation is static coefficients, which may oversimplify sectoral shifts due to regulatory or climate changes.
Water Watch - CDP Water Impact Index explores sectoral level dependencies, by ranking roughly 200 industrial activities within 13 industry sectors, according to their potential impact on water resources – both in terms of water quantity and water quality. This is the only analysis of this granularity that exists for assessing the relative impact of different industrial activities from companies’ direct operations, supply chain and product use on the world’s water resources (Box 4.3).
Science Based Targets for Nature – Sector Materiality Ratings identifies which environmental pressures, including water use and pollution, are material for specific sectors and sub-sectors. Supports prioritisation for setting science-based targets aligned with the SBTN framework.
TNFD Sector and Biome Guidance provides guidance on how sectors interact with different biomes, helping users assess dependencies, impacts, and nature-related risks using the TNFD LEAP framework. Useful for identifying water-related risks across ecosystems and value chains.
CDP publishes an annual index that evaluates water-related impacts and dependencies across the value chains of more than 200 industrial activities, illustrating how various sectors affect both water availability and quality. The findings highlight sector-specific challenges, such as:
Fashion and apparel: This industry, along with associated sectors like cotton cultivation, is a significant consumer of water throughout both its direct operations and supply chains. Increasing attention is also being paid to the sector’s influence on water quality, not just during production but across the entire product lifecycle, including usage and disposal.
Technology: Water is an essential input for the tech industry, particularly in the manufacturing of semiconductors, which requires vast volumes of ultra-pure water to prevent contamination. Additionally, data centres depend on water for cooling, and their consumption is expected to grow substantially with the rise of artificial intelligence. These dependencies make the sector particularly sensitive to local water stress, which could disrupt operations and production.
Agribusiness: Agriculture contributes significantly to water stress through intensive water use and nutrient runoff. In key emerging economies like India and China, growing pressure on groundwater and freshwater systems is prompting calls for subsidy reform, particularly around water extraction and fertiliser use. Germany has recently introduced legislation to curb fertiliser runoff, though such policy action remains rare among major economies, leaving the sector exposed to potential regulatory shifts.
Metals, mining, and extractives: These activities can have substantial negative effects through wastewater discharge and pollution. Their broader supply chains can also be water-intensive, amplifying their overall impact on water systems.
Note: 0 = no materiality and 3 = highest materiality. Data comes from : Water Watch Impact Index 2023, June 2023, CDP.
Source:; (Insight Investment, 2024[17]).
Physical risk data
Physical data allows firms to estimate current exposure to water-related risks such as water stress, floods, and water pollution. Physical indicators can be direct measures of water-related risks, or they can be an aggregated indicator based on physical measures.
Global Water Monitor Consortium data combine satellite and ground data to track the planet’s water. Their open-access platform offers daily data on precipitation, temperature, soil moisture, river flows, and lake levels, enabling users to monitor hydrological extremes and trends globally (Box 4.2).1
The WWF Water Risk Filter is a spatial tool that evaluates water-related physical, regulatory, and reputational risks across river basins worldwide. It integrates various data sources to provide a holistic view of water-related risks and is used by financial institutions and corporations for water stress and flood risk mapping (WWF, 2023[18]). While it offers granular geographic insights, it does not incorporate company-level financial risk metrics. The underlying data is also updated semi-frequently and may not reflect current conditions. For instance, water stress relies on World Resources Institute’s Aqueduct risk indicators which was last updated in 2019 (Hofste et al., 2019[19]).
Geospatial data and remote sensing for water-related risk monitoring are providing new data sources. For example, satellite data and AI-powered analytics (e.g., from National Aeronautics and Space Administration (NASA), the European Space Agency (ESA), and Google Earth Engine are being integrated into financial risk models to map water stress and pollution exposure at asset and regional levels (NASA, 2025). More examples are listed in Annex A, section 6.2.3.
Company-Level Water-related risk Disclosures
To evaluate water governance and exposure to water-related risks at the asset level, financial institutions often rely on ESG analysis.
The CDP Water Security Questionnaire collects self-reported corporate data on water management, scarcity risks, and financial exposure. Over 3 100 companies disclosed water-related risks through CDP in 2023, though data completeness varies (CDP, 2024[20]). Some major challenges are the coverage of reporting companies. In addition, only that 40% of companies assess water-related risks in their supply chains, leading to undervalued systemic risks.
Moody’s, MSCI, and S&P, Sustainalytics integrate water-related risk assessments into ESG ratings by evaluating Water usage intensity of companies, operations in water-stressed regions, regulatory exposure to water-related restrictions. However, methodologies are not fully standardised, making cross-provider comparisons difficult (Davies and Martini, 2023[21]).
Regulatory standards
Many institutions remain unaware of the significant water-related risks they face, as highlighted by data from the Carbon Disclosure Project (CDP, 2023[22]). This lack of awareness leads to underestimation of water-related risk indicators at the business level, particularly concerning indirect risks within supply chains. Indeed, basic heatmaps and conventional risk assessments often fail to capture the intricate dependencies and impacts that extend throughout entire value chains. Additionally, transparency is lacking in how companies and financial institutions quantify and disclose their exposure to water-related risks. This gap makes it difficult to compare and benchmark risk management practices across different sectors and regions. Moreover, current qualitative ratings of water-related risks often do not account for the economic exposure of individual companies, which means assessments may not accurately reflect the true financial risks associated with water-related issues.
Data on water-related risks in developing countries are notably scarce, limiting understanding of the severity and extent of challenges in regions most vulnerable to water scarcity and pollution.
Publicly available data on water-related risks and insurance coverage are insufficient, complicating efforts to assess and manage financial exposure associated with these risks. Additionally, there is a significant gap in data concerning the future of freshwater ecosystem services, hindering our ability to anticipate how these vital services may be impacted by water-related risks.
Assessments of water-related risks frequently overlook potential future developments that could reduce dependencies on natural resources like freshwater. This limitation underscores the need for adaptable assessments that can incorporate technological advancements and evolving industrial practices.
Regulatory initiatives are expanding the scope and quality of corporate water-related risk reporting, moving from voluntary disclosures to mandatory, standardised frameworks.
Frameworks like the EU’s Corporate Sustainability Reporting Directive2 (CSRD) and the International Sustainability Standards Board (ISSB) standards3 require companies to disclose material sustainability risks and impacts, providing critical data for financial institutions and regulators. ISSB and CSRD incorporate water-related risks in different ways. The ISSB (IFRS S24 – Climate Disclosures) primarily addresses water through climate-related physical risks (e.g., droughts, floods, and water scarcity) and transition risks (e.g., regulatory constraints on water use and pollution). IFRS S1 on General Requirements also includes broader nature-related financial risks. However, water is not a standalone reporting category under ISSB, and disclosures are only required to the extent that they are financially material. While the IFRS Foundation focuses solely on reporting on financially material risks, it is seeking to enable interoperability with the Global Sustainability Standards Board’s voluntary standards for reporting on impact materiality under the Global Reporting Initiative5 (GRI).
In contrast, CSRD provides dedicated reporting requirements for water through ESRS E36 (Water and Marine Resources) and ESRS E27 (Pollution). From 2024 onwards, large EU companies must disclose water dependencies, impacts, and financial risks as part of their Environmental, Social, and Governance (ESG) reporting, with the implementation of the Corporate Sustainability Reporting Directive (CSRD) (European Commission, 2022). Under ESRS E3, companies must report on water withdrawals, consumption, discharge, efficiency, and dependencies on water-stressed regions. Additionally, ESRS E2 explicitly covers water pollution, requiring firms to disclose how their operations contribute to water contamination, hazardous substance discharge, and ecosystem degradation. Unlike ISSB, CSRD mandates a double materiality approach, meaning companies must assess not only how water-related risks affect their financial position but also how their activities impact water resources and ecosystems.
While ISSB focuses on integrating water-related risks into financial risk management, CSRD sets a much broader and more detailed water-related disclosure framework, aligning with EU environmental policies and the Water Framework Directive. The Corporate Sustainability Reporting Directive (CSRD) is deeply integrated with existing EU environmental regulations, ensuring that corporate water disclosures are aligned with broader policy goals. Specifically, CSRD aligns with the EU Water Framework Directive (WFD), the Industrial Emissions Directive (IED), and the Zero Pollution Action Plan, reinforcing corporate responsibility for water management, pollution control, and biodiversity protection.
Under TNFD's Nature-Related Risk Assessment Framework, sector-specific water-related risk disclosure guidance8 are being introduced that will help investors assess corporate exposure based on location-specific water-related risk indicators. As regulatory pressure increases, it is likely that ISSB’s future updates, particularly through its collaboration with TNFD will expand water-related disclosure requirements to align more closely with CSRD’s detailed approach (TNFD, 2025[23]). These developments will increase the volume, consistency, and granularity of corporate water data, enabling more accurate financial risk assessments. Nevertheless, it is important to note that TNFD is more applicable for issuers with direct operations and banks with equity portfolios where disclosure and metrics are more available. Central banks’ own balance sheets are often a mix of different assets, but the core is often sovereign exposures where data is even more scarce and existing TNFD guidance is less applicable (FfB, 2025[24]).
4.1.5. Supervisors are starting to map water-related dependencies
Several supervisory authorities and central banks have conducted pilot assessments to better understand their financial systems' dependencies on nature, and therefore their exposure to nature-related risks. These case studies, of which some are summarised in Table 4.1, show that integrating ecosystem risk exposure into financial analysis is feasible and can reveal meaningful exposure patterns that may not be evident using conventional risk frameworks. These studies in particular highlight that ground and surface water are commonly identified as having the highest material dependency (UNEP FI and WWF, 2024[25]).
Note: Some of these studies also include findings on the transition risks related to nature loss.
Source: (UNEP FI and WWF, 2024[25]).
For instance, the Dutch National Bank (De Nederlandsche Bank, “DNB”) applied a TNFD-aligned approach to explore portfolio exposure to nature-related risks. These efforts drew on ENCORE, the WWF Water-related risk Filter, and custom internal datasets to analyse sector-level and asset-level exposure. Groundwater and surface water were the most significant dependencies (Box 4.4). These examples demonstrate that while tools and frameworks are evolving, water-related risk identification remains highly dependent on contextual data, cross-sector collaboration, and regulatory support. Integrating sectoral exposure, geographic vulnerability, and forward-looking disclosure is key to building supervisory readiness.
The Dutch Central Bank (DNB) conducted a pilot study to explore nature-related financial risks in its own-account investments, applying the Taskforce on Nature-related Financial Disclosures (TNFD) framework. The pilot had three primary aims: to assess nature-related risks in investment portfolios, to gain practical experience with the TNFD framework and associated tools, and to contribute to international capacity building in nature-related risk assessment.
The analysis focused on two developed market equity portfolios: one actively managed, aligned with the Paris Agreement (the Paris Aligned Mandate), and one passively managed (the Broad Market Portfolio). Using TNFD-aligned tools such as ENCORE and the WWF Biodiversity Risk Filter, DNB identified ecosystem dependencies and potential impact drivers across the portfolios. While the tools offered valuable initial insights, the analysis was constrained by data gaps—particularly the lack of precise, location-specific information at the asset level—and required significant manual effort.).
Source: (DNB, 2024[26]).
To deepen the assessment, DNB conducted a case study on the electric utilities sector, one of the most nature-dependent sectors in the portfolio. This deep dive highlighted significant dependencies on freshwater ecosystems and land use, as well as exposure to nature-related transition risks such as policy shifts, regulatory changes, and reputational pressures. It also illustrated how material risks could arise from supply chain exposure to high-biodiversity areas, underlining the importance of spatially explicit data and sector-specific engagement strategies. The findings underscored the usefulness of starting with a focused sectoral or portfolio slice to manage analytical complexity and build internal expertise.
The pilot ultimately reinforced the need for enhanced data granularity, stronger guidance for financial institutions, and increased collaboration with external asset managers. It also called attention to the importance of building internal capacity and fostering a shared understanding of nature-related risks—particularly as institutions prepare for the broader adoption of TNFD-aligned disclosure practices.
Source: (DNB, 2024[26]).
Risk sources are subject to uncertainty due to the range of possible events related to nature-related losses as well as the differences in regulations implemented by governments, creating the additional problem of needing to forecast the state of nature in the future. Analysis on different risk sources is essential to understand how nature loss, and freshwater ecosystem degradation transmits to the economic system, entailing the need for scenarios which allow building a forward-looking assessment of the consequences of nature loss.
To support the conceptualisation of economic impacts stemming from physical and transition water-related risks, the OECD Supervisory Framework on assessing Biodiversity Risks invites financial authorities to explore how economic risk originates, their economic impacts, possible channels of propagation to other parts of the economic system. Box 4.5 provides some questions to guide this process. The purpose is to provide clarity on which type of risks could be considered by financial authorities to design relevant scenarios for their own assessment of financial materiality (OECD, 2023[1]). Section 4.2.4 then outlines key economic modelling approaches to quantify these risks.
Economic risk origination:
Origin of the risks, their magnitude, and their transmission channels.
What are the relevant risk sources and what is their magnitude? (Magnitude may consider the economic sectors affected and the impact on the entire economic system)
Are risks transmitting to the economy through physical or transition channels? Are there relevant interlinkages to consider?
Are there relevant climate risks to be taken into account that could amplify the magnitude of the risk?
Location of the risk and the relevant time horizon for risk materialisation.
Is the foreign exposure of market participants significant?
Are domestic or foreign nature-related risks most relevant to consider?
What are the relevant time horizons over which these risks may occur and propagate?
Are there any additional risks that could materialise over time and exacerbate environmental risks?
Economic risk materialisation
What are the direct and indirect economic impacts of water-related risks, including micro and macro-economic impacts originating from physical and transition risks;
How can risks transmit between sectors from those which directly depend on and impacting water and freshwater ecosystems.
Economic risk propagation:
What is the level of risk materialisation for direct and indirect impacts?
What are the most relevant micro and macro-economic impacts identified for the assessment?
What is the time horizon over which identified impacts can occur?
Can additional sources of uncertainty be taken into account in the assessment?
Are there traditional risks which may amplify or mitigate the economic risks stemming from nature degradation?
Source: adapted from (OECD, 2023[1]).
4.2.1. Identifying how economic water-related risks originate
Water-related risks originate from a range of physical and transition pressures on ecosystems, especially freshwater systems. Developing forward-looking assessments requires financial authorities to consider:
The source and magnitude of risk (e.g. drought frequency, regulatory change),
The time horizon (short, medium, or long term),
The geographic context (local, national, or global), and
The ecosystem services at risk (e.g. water purification, flood regulation, groundwater recharge, soil moisture regulation, or biodiversity support).
Nearly every sector of the economy depends on water directly or indirectly. Crucially, water has no close substitute in most industrial, agricultural, or municipal uses. This makes firms particularly vulnerable to physical water risks, as operations cannot easily be maintained or relocated when access is disrupted. Prolonged "day zero" water scarcity or severe floods can halt operations outright in water-intensive industries. The exposure to water-related risk is highly location-specific: firms and assets in basins facing chronic water stress or in floodplains are far more vulnerable. This highlights how local water availability can generate financial risks even for a global company. The location and time horizon of water-related risks are key – some risks are acute (e.g. flash floods, sudden droughts) while others are chronic (e.g. multi-year rainfall decline, aquifer depletion). Financial authorities need to identify where these risks originate and over what time frame they might materialise when assessing potential impacts on portfolios.
The magnitude of water-related hazards varies widely. Extreme events like catastrophic floods can cause immediate large losses, whereas gradual water scarcity might erode economic output more subtly over time. There is evidence that what were historically considered rare extremes are becoming more frequent and severe. For instance, “500-year” flood events have struck major economies multiple times in recent decades, and many regions are experiencing the driest conditions in living memory (Ingraham, 2017[27]). While probabilistic data on future water extremes remains uncertain, indicators point to rising risk. By 2050, up to 3.2 billion people are projected to live in severely water-scarce regions under business-as-usual trends (Global Commission on the Economics of Water, 2024[28]), and roughly 46% of global GDP could be produced in areas facing high water stress (up from about 10% today) (WWF, 2023[29]). These figures underscore that the sources of water-related risk – climate change, unsustainable water use, ecosystem degradation – are on course to intensify, expanding the exposure of economic activities to water shocks. Identifying the origin and drivers of water-related risk is therefore a first step in risk assessment, informing where mitigation or adaptation measures are most urgently needed.
Figure 4.5 provides a schematic of how these risks originate from environmental degradation and feed into economic systems.
Source: (OECD, 2023[1]).
4.2.2. Water-related risks drive economic losses at micro and macro scales
Microeconomic impacts
At the micro level, water-related disruptions can hinder business operations, damage assets, and drive up cost. For example, droughts reduce crop yields for farmers and can force water-intensive industries to curtail production, leading to revenue losses. Floods can destroy infrastructure and inventory, imposing reconstruction costs and downtime. Water quality issues (e.g. industrial water pollution or algal blooms) can raise treatment costs for firms or constrain industrial processes.
A striking case occurred during the 2011 Thai floods – the disaster caused an estimated USD 46 billion in damage and losses, heavily affecting manufacturing hubs. This led to a 1.1 percentage point reduction in Thailand’s GDP growth that year compared to pre-flood projections, and disrupted global supply chains for automotive and electronics companies (World Bank, 2012[30]). In fact, indirect losses abroad were disproportionate: Swedish firms alone saw an estimated EUR 3 billion drop in sales due to parts shortages following the Thai floods, a 30-fold amplification of the direct impact via global value chains (Forslid and Sanctuary, 2023[31]). Such examples illustrate how localised water shocks (whether floods or droughts) can translate into significant firm-level and industry-level losses, not only locally but for trading partners and multinational businesses as well. The 2011 Thai floods also resulted in record insured losses, estimated at USD 12 billion, making it one of the costliest flood disasters for insurance and reinsurance markets worldwide (Swiss RE, 2021[32]). Reinsurers shouldered significant claims due to business interruption and supply chain disruptions, leading to changes in risk assessment and insurance coverage practices throughout the region (Swiss RE, 2021[32]).
Beyond episodic disasters, chronic water stress can also erode sector performance. Research indicates that water scarcity has started to impact credit risk in water-dependent sectors. For instance, a recent pilot stress test by an international bank examined a scenario of a three-month water supply curtailment in a highly water-stressed Asian region. The outcome was a significant deterioration in average credit ratings for the affected heavy industrial firms, with over one-third of companies moving from investment grade to speculative grade status (CISL and HSBC, 2022[33]) This underscores that prolonged or severe water deficits can materially weaken firms’ financial health (through lower output, higher costs, or both), increasing their credit risk. Even in less extreme cases, companies facing higher water costs or intermittent shortages may see reduced profit margins and competitiveness. At a household level, water crises can reduce incomes and welfare – for example, farmers may suffer crop failures and communities might face higher expenditure for water procurement or health costs due to waterborne disease outbreaks.
Macroeconomic level
At the macroeconomic level, water-related shocks can translate into GDP losses, higher inflation, and strains on public finances. Cross-country analysis by the World Bank finds that moderate-to-severe droughts reduce annual GDP growth by about 0.4 to 0.8 percentage points on average, with the largest effects in low-income, agriculture-dependent economies (Zaveri, Damania and Engle, 2023[35]). These growth impacts can cumulate if droughts persist or recur, leading to sizeable income losses over time. In extreme cases, droughts can push economies into recession or trigger balance-of-payments problems if food imports surge. OECD research finds that the economic costs of drought are on the rise, with drought-related losses and damages increasing globally at an annual rate of 3-7.5%. As water scarcity constrains whole sectors and disrupts trade, an average drought event in 2025 could be up to six times more costly than in 2000, while by 2035, costs are expected to be at least 35% higher than today. Agriculture is the most affected sector: in particularly dry years, crop yields can decline by up to 22%, while a doubling of drought duration could reduce the production of key crops like soy and corn by up to 10% (OECD, 2025[36]).
Water scarcity, exacerbated by climate change, is projected to act as a chronic drag on growth in many regions: for instance, without better water management, parts of the Middle East, Sahel, and Central Asia could see their GDP growth rates decline by as much as 6% by 2050 due to water-related impacts on agriculture, health, and incomes (CDP, 2022[37]). New modelling suggests that these risks are not confined to developing countries, under a business-as-usual scenario, it was estimated that high-income countries might experience a median GDP decline of around 8%, and lower-income countries a decline of 10–15%, relative to a baseline that assumes no worsening water constraints (Global Commission on the Economics of Water, 2024[28]).
Water shocks can also spur inflation and fiscal pressures. Droughts and floods often lead to food price spikes (through crop failure or supply disruption), which in turn can drive headline inflation upward (CDP, 2022[37]). For example, drought-related food inflation has been linked to social unrest in some contexts (Koren, Bagozzi and Benson, 2021[38]) and can prompt costly government interventions (such as emergency food imports or farming subsidies). On the fiscal side, governments may face sudden spending needs for disaster relief and infrastructure repair after floods, straining budgets and potentially increasing public debt. Lower economic activity due to water stress also means lower tax revenues. In extreme cases, water crises can contribute to sovereign credit rating downgrades if investors see heightened risks to political or economic stability or public finances (Reuters, 2025[39]).
Integrating water-related risks into macroeconomic frameworks remains constrained by methodological and institutional challenges. Many standard macroeconomic models used by central banks do not incorporate hydrological feedback loops (discussed in Chapter 2.1.6), regional water asymmetries, or cross-sectoral dependencies. As a result, they fall short in simulating how water shocks transmit through key economic variables such as inflation, employment, trade, and output. Data limitations, especially in terms of spatial granularity and temporal resolution, further hinder efforts to translate local water crises into national-level economic indicators (NGFS, 2023[40]). Moreover, institutional mandates and modelling traditions may discourage experimental or systems-based approaches, making cross-agency coordination and methodological innovation essential. Addressing these gaps will be key to ensuring that water-related risks are adequately reflected in macroeconomic surveillance and policy decisions.
4.2.3. Risks propagate through trade, supply chains, and feedback loops
Water-related risks do not confine their effects to the point of impact; they propagate through various transmission channels across the economy and financial system. Understanding these channels is crucial for capturing the full extent of risk and potential systemic implications:
Supply chain and trade linkages
Modern economies are interconnected, so a water shock in one location can create far-reaching spillovers. As noted, the 2011 Thailand floods disrupted global manufacturing supply chains, illustrating how a local catastrophe translated into production interruptions and financial losses for downstream industries worldwide. Droughts can similarly trigger knock-on effects. For instance, a severe drought in a major grain exporting country will reduce its agricultural output, leading to higher world grain prices and import bills for food-importing nations. This can deteriorate trade balances and increase business costs in those importer countries (e.g. food processors, livestock farms relying on feed). Multi-regional input-output analyses show that water scarcity in key producing regions can effectively be “imported” via trade, as shortages curtail exports of water-intensive goods (Global Commission on the Economics of Water, 2024[28]). These indirect impacts mean that even economies not facing high water-related risk domestically can feel the economic pinch via globalisation of water shocks.
Source: Adapted from (Laczynski et al., 2015[41]).
Inter-sectoral impacts and feedback loops
Within a country, water shocks can transmit between sectors through input-output relationships and price effects. For example, reduced water supply to agriculture cuts raw material availability for the food and beverage industry, potentially raising input costs and consumer prices.
In energy markets, competition for limited water during droughts may force power plants to reduce output, increasing electricity prices and affecting all power-dependent sectors. These interactions can create feedback loops: higher prices for essentials like food and energy can depress other consumption and investment, compounding the initial shock. Moreover, if firms in one sector suffer losses, their reduced demand for inputs or labour will impact other sectors (a form of Keynesian multiplier effect). Economic models conceptualise this as micro-to-macro amplification, the initial direct impact (e.g. farmers losing income) leading to second-round effects (e.g. rural consumer spending falls, affecting retail businesses). In addition, households and businesses may deplete savings or borrow to cope with water shocks, affecting future spending and investment patterns. In extreme cases, migration away from water-stricken areas can occur, affecting labour markets and housing markets elsewhere (World Bank, 2016[42]).
Source: Adapted from (NGFS, 2023[34]).
4.2.4. Modelling tools help quantify economic exposure to water-related risks
A variety of modelling approaches have been developed to assess and quantify the economic risks from water-related hazards. Each comes with strengths and limitations, and in practice they can be complementary. A concise overview is provided below (with further technical details and case examples available in Annex B, section 6.2.3).
Integrated Assessment Models (IAMs): IAMs are large-scale models that combine climate science, hydrology, and economic growth modules to project long-term impacts of climate change on the economy. Some IAMs incorporate water explicitly, linking climate-driven changes in water availability to economic production and welfare. They are often used to evaluate global or regional scenarios over decades. For example, the World Bank’s “High and Dry” study integrated a global hydrological model with a computable general equilibrium model to estimate GDP effects of water scarcity under climate change. IAMs can capture broad trends (such as a 6% GDP hit in water-stressed regions by 2050 under a pessimistic scenario) and are useful for policy planning. However, they typically operate at coarse spatial resolution and may not fully capture short-term shocks or local-scale dynamics (World Bank, 2016[42]). IAMs lack the complex representation of ecosystem-services (overrepresenting provisioning, underrepresenting regulating, supporting, and cultural). Certain macroeconomic underlying assumptions (i.e. substitution of natural capital or technological advancements) can lead to underestimation of nature loss and environmental policies’ impact on macroeconomy (Salin, Kedward and Dunz, 2024[43]).
Hydro-Economic Models (HEMs): HEMs integrate detailed hydrological models with economic optimization or equilibrium models, usually at basin, national or sub-national scales. These models simulate water supply and demand (for agriculture, industry, households, environment) and optimise water allocation or infrastructure investments based on economic criteria (maximising welfare or GDP). HEMs are well-suited to assess the economic cost of water allocation decisions, water pricing policies, or infrastructure under different scenarios of water availability (Brouwer and Hofkes, 2008[44]; Harou et al., 2009[45]). For instance, a hydro-economic model might evaluate how building a new reservoir or implementing water trading could mitigate the economic losses of a drought in a river basin. By explicitly representing water resource systems (rivers, aquifers, reservoirs) and economic values, HEMs can provide granular insight into adaptation strategies. These models help identify which management options, such as reallocating water, investing in new infrastructure, or implementing conservation policies, yield the greatest economic and environmental benefits under different climate scenarios. It is important to note that HEM have intensive data requirement (e.g. detailed water usage, hydrology, and sectoral data) and they are often scenario-specific rather than predictive in a probabilistic sense. Rather than predicting exact outcomes, HEMs are well-suited to exploring a range of possible futures and facilitating policy dialogue.
Econometric and Statistical Models: These approaches use observed data to statistically estimate the relationship between water-related variables and economic outcomes. Examples include panel regressions of GDP growth on rainfall/drought indices, firm-level studies correlating revenue or stock performance with water stress exposure, or sectoral analyses of output changes after past water shocks (Zaveri, Damania and Engle, 2023[35]). Econometric models provide empirical evidence of impact magnitudes and can control for other factors. Recent cross-country evidence quantifies how droughts systematically reduce growth and increase poverty, especially in arid and developing regions. These models are valuable for validating assumptions in IAMs or HEMs and for stress-testing: e.g., a regression-derived coefficient can be used to estimate GDP impact if rainfall drops X%. Their limitation is reliance on historical patterns, which may not hold as climate change intensifies or if adaptive measures significantly improve (stationarity issues). They also often capture average effects, potentially missing tail-risk scenarios (Zaveri, Damania and Engle, 2023[35]).
Multi-Regional Input-Output (MRIO) and Network Models: MRIO models map the interdependencies between sectors and regions through trade of goods and services. By augmenting MRIO tables with water use and vulnerability data, analysts can simulate how a water supply shock in one region propagates globally via supply chains (Tanoue et al., 2020[46]). For example, an MRIO analysis can estimate the indirect economic losses in country B due to a drought in country A that reduces A’s export of a key input to B. These models excel at tracing spillover effects and identifying critical nodes (sectors or regions) whose disruption would have outsized global impacts. They have been used to estimate metrics like the total global economic loss attributable to a local flood (including second-order effects). A related approach is network modelling, which can incorporate financial networks (creditor-debtor links) or supply-chain networks to see how water-related risks might cascade in complex systems. The challenge with MRIO and network models is the need for detailed, up-to-date data on interconnections and the assumption that technical coefficients remain constant during shocks. Nonetheless, they fill an important gap by going beyond direct impacts to capture systemic propagation, which is highly relevant for financial stability analysis.
Each of these modelling approaches can inform economic risk assessment from different angles. In practice, policymakers and supervisors often draw on multiple tools, for instance, using IAMs for long-run scenario framing, HEMs for project- or region-specific analysis, and econometric models for near-term stress testing benchmarks. A summary comparison of approaches (scope, strengths, limitations) is provided in Annex B, section 6.2.3. Ultimately, the choice of model depends on the decision context: whether the goal is to estimate aggregate GDP impacts, evaluate adaptation investments, set insurance pricing, or conduct a bank stress test on loan portfolios. It is important to note that all models have uncertainties, particularly concerning future climate-water dynamics and adaptive responses, so results should be used as informative ranges rather than precise predictions. Building models that integrate both physical and economic complexities of water (and doing so in a transparent, collaborative manner) remains an evolving frontier.
In the final phase, the financial risk assessment, financial authorities are invited to explore financial risks stemming from the exposure to sources of physical and transition risks, notably through financed activities. Different financial risk channels can be explored, including credit, market, liquidity and underwriting risks. Potential impacts on financial stability and individual financial institutions are assessed.
4.3.1. Increases in borrower default and credit risk
Credit risk relates to the potential for a borrower (issuer risk) or a counterparty (counterparty risk) to default on their obligations (Christoffersen, 2003[47]). Water-related risks can impair a borrower's ability to generate income and maintain wealth, both critical factors in determining creditworthiness. Businesses heavily dependent on water resources are especially at risk. For instance, droughts can drastically reduce crop yields, leading to lower revenues and an increased likelihood of loan defaults (NGFS, 2024[6]). Intensive water use and water pollution can significantly degrade soil quality, reducing the value of agricultural land used as collateral and making it more challenging for farmers to secure loans or repay existing ones (TNFD, 2023[48]). Moreover, water-related risks can deplete a borrower’s overall wealth, complicating loan repayment even if income is still being generated. For example, rising production costs due to water scarcity, such as higher groundwater fees, can strain a mining company's finances, lowering its creditworthiness and increasing the risk of default (TNFD, 2023[48]).
Eight sectors collectively holding USD 1.4 trillion in debt face high water management risks (see Figure 4.8). Water management risks are risks from poor management of water consumption, efficiency, access, quality, and pollution, primarily focusing on governance and management issues that can lead to economic and financial risks for a firm. This illustrates that extractives are particularly exposed to water management risks (Moody’s, 2023[49]).
Notes: United States Dollars (USD).
Source: Author’s construction, data retrieved from (Moody’s, 2023[49]).
The ripple effects of heightened credit risk can extend beyond individual borrowers and lenders, potentially destabilising the entire financial system. Financial institutions with significant exposure to water-stressed sectors are more vulnerable to an increase in non-performing loans, leading to a decline in asset quality. This deterioration can trigger credit rating downgrades and an increase in risk-weighted assets (RWAs) (CISL, 2022[50]). Lower credit ratings can raise borrowing costs for financial institutions, further constraining their ability to lend. Under extreme scenarios, widespread defaults across water-stressed sectors could impact on the financial system, with far-reaching impacts on the broader economy.
In the US, a study of a two-year drought shock found that non-performing loan ratios would significantly increase for agricultural, residential mortgages, commercial loans, and commercial mortgages indicating potential spillover effects and that impacts of drought shocks go beyond agriculture (Özsoy, Rasteh and Yönder, 2025[51]).
4.3.2. Unpriced water-related risks can trigger sharp asset repricing
Market risk, characterised by sudden and substantial declines in asset values, is exacerbated by water-related factors. When risks are not accurately priced into financial assets, they can trigger market volatility and instability (BIS, 2021[52]).
The IMF's 2020 Global Financial Stability report studied aggregate stock market data for 68 economies to assess whether markets were adequately pricing climate risk. The report found that physical risks from climate change do not appear to be reflected in global equity valuations. This work suggested that there was no clear evidence that investors were pricing climate change risks (IMF, 2020[53]). In subsequent reports, the IMF noted increased global awareness and market attention to climate-related financial risks. However, market pricing of physical climate risks remains uneven and partial (IMF, 2023[54]).
Another study investigated the real effects of water-related risks on hydroelectricity generation in the USA and Europe; it found that these risks were not priced in financial markets (Colesanti Senni, Goel and von Jagow, 2024[55]). However, the materiality of water-related risks is highly contextual. The impact of large climatic disasters on equity prices had been found to be relatively modest where there was higher rates of insurance penetration and greater sovereign financial strength, which mitigate the impact of a large disaster on equity returns (IMF, 2020[53]).There is mixed evidence for the pricing of climate change physical risk in other asset classes. In the United States, counties projected to be adversely affected by rising sea levels faced higher costs for underwriting fees and initial yields when issuing long-term municipal bonds, in comparison with other long-term municipal bonds from counties unlikely to be affected by climate change and short-term municipal bonds. This implies that the market does in some cases price climate change risks for long-term securities (Painter, 2020[56]).
One key example of the materialisation of market risks was the 2007–2008 world food price crisis, which was partly driven by drought-induced crop failures in major grain-producing regions, leading to significant spikes in food prices globally (Global Commission on the Economics of Water, 2023[57]). In another example, in 2018, Cape Town faced a severe water shortage, bringing the city close to "Day Zero", the point at which municipal water supplies would have to be shut off or severely curtailed. This crisis had profound effects on the local economy, particularly in agriculture and tourism, leading to job losses and decreased economic output. The water crisis adversely affected Cape Town's real estate market. Luxury property prices declined by an estimated 30% between mid-2017 and 2020, reflecting decreased demand and investor confidence during the drought (Foroudi, 2020[58]).
Furthermore, water-related transition risks can lead to the devaluation of assets associated with water-intensive or polluting industries. This devaluation can result in stranded assets, which are investments that have become obsolete or non-performing due to external changes, leading to financial losses for investors and institutions holding these assets. This can also amplify credit risk and financial instability (NGFS, 2024[6]). CDP data already shows that there are already USD 15 billion of assets stranded or at risks of being stranded in the energy and mining sectors due to water-related risks (CDP, 2022[37]).
4.3.3. Liquidity dries up when water shocks hit confidence and capital
Liquidity risk occurs when a financial institution is unable to secure stable funds, such as cash flows or borrowed funds, to meet its financial obligations (NGFS, 2024[6]). Banks are particularly vulnerable to liquidity risk when there is a rapid change in market conditions. This can be provoked by regulatory changes affecting specific assets or sudden shocks such as natural disasters (e.g., floods). (BIS, 2021[52]).
Branches in regions affected by flooding events can be exposed to massive money withdrawals, especially in developing economies (Abedifar, Kashizadeh and Ongena, 2024[59]). Banks’ counterparties could withdraw deposits and lines of credit in order to finance damage repairs or pay for medical care associated with severe water-related events (BIS, 2021[52]). Meanwhile, households in need of additional funds would probably demand emergency loans (Klomp, 2014[60]), pushing banks to sell their assets to cover these outflows (Bafin, 2020[61]).
Water-related events can disrupt supply chains, increase businesses’ costs, and lower consumption, all together leading to a decrease in economic activity and lower profits (Yu et al., 2022[62]). As a result, assets from sectors that are vulnerable to water-related risks can become less valuable, affecting the value of the bank’s loan portfolio and leading to increased defaults and losses, and a decrease in liquidity (Mirza et al., 2023[63]; Su et al., 2022[64]).
Transition risks can also trigger liquidity risks. For instance, if a company’s licence is removed due to its impact on water or non-compliance with water regulations, it can impact its credit rating and generate refinancing costs (CISL, 2021[65]; Morgan et al., 2019[66]). Prudential regulations may also get more stringent, limiting funding to water-intensive companies (Lang et al., 2023[67]).
In the insurance sector, mispricing of nature-related risks can threaten financial stability by leading to higher payouts, which may subsequently result in liquidity and solvency issues. This is particularly relevant for property and casualty (P&C) insurance, where inadequate risk management and control in the short term could also lead to restrictions or withdrawals of coverage (SIF, 2021[68]).
However, despite increasing awareness of the crucial role water resources play in global financial stability, no globally systemically important bank in the study had explicitly identified these factors as potential liquidity risks (WWF and CDP, 2024[69]).
4.3.4. Underwriting, operational, and reputational risks intensify with water-related events
Underwriting risk
Where insurance is provided via the private market, as underwriters of natural catastrophe risks, (re)insurance sector is at the frontline of climate change and environmental degradation. The long maturities of (re)insurance company portfolios, which span over several decades in advanced economies, will bear the longer-term water-related risks.
Insured losses have been elevated over the last five years due to recurring high-loss secondary peril, with multi-billion insured loss outcomes. “Secondary perils” is an umbrella term for natural catastrophes that typically generate losses of low to medium magnitudes, such as thunderstorms, hail and tornadoes, drought, wildfire, snow, flash floods and landslides. “Primary perils” refers to large-scale catastrophes, notably tropical cyclones, earthquakes and European winter storms. The increase in secondary perils is a new trend. For instance, in 2021 there were notably two separate secondary perils events that caused losses in excess of USD 10 billion each: the winter storm Uri in the US and devastating floods in central-western Europe.
Floods have been highlighted as a cause of regular and sometimes devastating damage. In 2021 alone, flooding accounted for USD 82 billion in losses, nearly a third of all economic losses from natural catastrophes in that year. Of the USD 82 billion, only USD 20 billion were insured (SwissRE, 2022[70]). The July 2021 flooding in Central Europe was the costliest natural catastrophe in modern European history and the costliest flood event globally to date, with estimated overall losses of USD 54 billion (MunichRe, 2020[71]).
Typically, secondary peril events have been less well monitored and modelled, which is problematic given the rise of their associated losses. This points to an important need for secondary perils to be better understood for the purpose of a more complete and accurate risk assessment. (SwissRE, 2021[72]; SwissRE, 2022[70]). Insurance companies have needed to develop tools and products to evaluate the risks and costs associated with potential water-related hazards. For example, Swiss Re has developed specialised tools like CatNet and FLOAT for evaluating water-related risks, as well as insurance products such as FLOW to address these specific challenges (Swiss Re, 2023[73]).
In addition, underwriting risks extend beyond property insurance and can significantly impact multiple sectors. Water-related risks can disrupt business operations, leading to higher business interruption claims. In the agricultural sector, water stress results in substantial revenue losses and affects crop insurance by reducing yields. Moreover, water-related risks can contribute to the spread of diseases, elevating morbidity and mortality rates and driving up life and health insurance claims (EIOPA, 2023[74]).
Moreover, understanding of nature-related risks is still in early stages. A global survey conducted by the Sustainable Insurance Forum (SIF), a global network of insurance supervisors and regulators addressing sustainability and climate change issues, revealed that the understanding of nature-related risks is significantly lower than that of climate change and natural hazard risks. While most natural hazards are water-related, this still leaves disruptions of freshwater ecosystems due to economic activity unexplored (UNEP, 2023[75]). In addition, other forms environmental degradation, can increase the vulnerability of insured properties. For example, soil erosion can intensify flood-related damage to buildings (NGFS, 2024[6]). The survey found that approximately 60% of insurance professionals do not currently assess these nature-related risks in their underwriting practices (SIF, 2021[68]). However, nearly 50% of re/insurers acknowledged the financial materiality of these risks to their underwriting business (SIF, 2021[68]).
Operational and reputational risk
Operational risk involves losses from disruptions to a financial institution’s internal processes, systems, or facilities. Water-related disruptions – such as floods damaging buildings and IT infrastructure or water shortages impairing utility services – can directly impact financial institutions’ operations. Banks, for instance, could have branches, data centres, or ATMs taken offline by severe flooding or storms, leading to service outages and recovery costs (Leyco, 2024[76]; NGFS, 2024[6]). In 2012, Hurricane Sandy’s storm surge flooded parts of New York’s financial district, temporarily disabling trading floors and bank facilities. Similarly, prolonged water rationing (as experienced in the 2018 Cape Town crisis) forced companies to implement emergency measures to keep offices running. While banks and insurers are not water-intensive businesses themselves, they rely on surrounding infrastructure: if city water systems fail or power plants (often water-cooled) shut down, financial firms’ continuity plans may be tested. Even remote workforces can be affected if employees’ communities lack basic water or power services during extreme events.
Reputational risk often intersects with operational considerations, especially when stakeholders perceive an institution’s actions as contributing to water-related problems. Banks and investors are increasingly scrutinised for financing projects with negative water impacts, such as pollution or excessive extraction. If a financial institution is linked to an environmental scandal or seen as financing entities that cause water crises, it can face public backlash, brand damage, and even client attrition (NGFS, 2024[6]; WWF, 2019[77]; ECB, 2020[78]). For example, major banks financing the Dakota Access Pipeline were targeted by civil society and indigenous groups due to concerns over water pollution and indigenous water rights. Investors warned of potential reputational and financial risks for banks involved in such projects, and indeed one city government ended a long-term banking relationship in protest over a bank’s participation (Michel, 2017[79]; Boston Common Asset Management, 2017[80]). This illustrates that stakeholder trust can erode quickly if a bank is deemed misaligned with water stewardship values, resulting in lost business and a damaged brand.
In another instance, BNP Paribas faced public pressure under France’s Duty of Vigilance law, with NGOs alleging the bank’s lending contributed to deforestation and water degradation in the Amazon – a legal and reputational challenge compelling the bank to strengthen its environmental due diligence (Commissaire de Justice, 2023[81]).
Moreover, reputational risk can arise if banks or insurers appear unresponsive to clients suffering from water-related disasters. If, say, an insurer denies many claims after a flood or a bank is slow to offer relief to drought-hit farmers, negative publicity and political criticism may ensue. Such perceptions can reduce market confidence and even affect stock performance or funding costs for the institution.
On the flip side, firms that proactively manage water-related risks, by supporting sustainable water projects or aiding affected communities, may bolster their reputation, turning a risk into an opportunity. Under CDP reporting in 2022, 23 financial institutions identified a maximum potential value of opportunities in water of USD 203 billion. These were linked to increased demand for product and services that support water resilience and increased access to capital related to resilience (CDP, 2023[82]).
Strategy and business model risks
Strategic risk arises from adverse business decisions or an inability to adapt to changing conditions, potentially undermining an institution’s long-term strategy or even viability. Both physical and regulatory factors can pose strategic and business model risks for financial institutions by fundamentally shifting the economic landscape in which they operate. Banks with heavy lending concentrations in water-vulnerable sectors (e.g. agriculture, textiles, power generation) could find their business models challenged if those sectors experience decline or volatility due to chronic water stress. For example, a bank specialising in agricultural finance in a region facing increasing droughts may see its growth prospects diminish and credit losses mount, calling into question the sustainability of that line of business. If certain geographies or industries become “unbankable” due to water scarcity or legal constraints, institutions must pivot strategies or face erosion of their asset base (Özsoy, Rasteh and Yönder, 2025[51]).
Transition policies related to water can also trigger strategic risks. Governments might introduce stricter water-efficiency requirements, pollution penalties, or caps on water withdrawal for industries. While these policies are aimed at sustainable water management, they can render some existing business models less profitable. A failure to anticipate such policy shifts could leave banks over-exposed to clients with high water footprints, who may struggle under new regulations. For instance, if a new law sharply limits groundwater use for mining or manufacturing, companies in non-compliance might downsize or shut, impacting banks that financed those operations. Similarly, insurers that have not diversified away from high-risk coastal properties may find their traditional underwriting focus is no longer tenable as sea levels rise and flooding worsens. The need to invest in new expertise, exit certain markets, or innovate products (like water scarcity insurance or loans for water-saving technology) becomes a strategic imperative.
Market trends indicate that forward-looking financial institutions are already adjusting their strategies on the basis of considering water-related risks. Major banks, such as HSBC, have begun mapping the water dependency of their portfolios and setting limits or enhanced due diligence for clients in water-stressed regions (CISL and HSBC, 2022[33]). Asset managers, too, are shifting strategies: funds are reallocating portfolios to avoid companies with poor water management, anticipating that these companies could underperform or face higher capital costs.
Crucially, the viability of certain business models under future water scenarios is being tested through scenario analysis. Regulators encourage banks to consider scenarios of water supply changes in major river basins that underpin regional economic activity (ECB, 2020[78]). If the analysis shows unsustainable impacts, the institution may need to realign its business model (e.g. financing more water-efficient industries, pricing in water-related risk, or developing contingency plans for affected areas). Inaction could lead to competitive disadvantages or even ratings downgrades if the market perceives a bank is not prepared for foreseeable water challenges.
4.3.5. Financial system interactions can lead to systemic risks
Water-related financial risks have the potential to accumulate and interact in ways that threaten broader financial stability, beyond individual firms. When many institutions are exposed to the same water-related risk – for example, when several banks are lending to a drought-stricken agricultural region, or multiple insurers cover a flood-prone coastline – a single shock can hit multiple balance sheets at once, thereby creating a systemic risk. The feedback loops between the real economy and finance can amplify this: a severe water crisis can depress economic output, increase loan defaults, reduce asset values, and force insurers to withdraw coverage, all of which may further slow recovery in the real economy. This negative spiral means that water crises and financial system health are closely linked. For instance, a protracted drought could undermine farm incomes and local government finances, leading to widespread loan losses and even weakening the creditworthiness of a sovereign; all such events combined can strain the banking system and sovereign bond markets simultaneously.
Researchers and regulators are increasingly mapping these interconnections. The Financial Stability Board (FSB) and NGFS have highlighted that cascading effects, such as climate change intensifying water shortages, which in turn impair economic productivity and firms’ ability to repay debt, could collectively pose systemic risks if not addressed (FSB, 2024[83]). One analysis by the European Central Bank found that the combined impact of increased flood risk and degradation of natural flood protections (like wetlands) could significantly amplify losses for banks, far beyond the effect of each factor in isolation (FSB, 2024[83]). Such compound events suggest that traditional risk assessments, which often consider hazards in silos, might underestimate tail risks where multiple water-related factors converge. In other words, the tail-end (“worst-case”) outcomes for financial loss distributions may be fatter than assumed, raising the probability of systemic banking stress under extreme scenarios of water-related risks (FSB, 2024[83]).
Contagion can occur through direct exposures, such as interbank loans, where financial distress at one institution can increase the likelihood of distress at others due to the network of contractual obligations between them (BIS, 2019[84]). This vulnerability also extends to banks' loans to corporate and retail clients, as well as securities holdings. Indirect mechanisms, such as exposure to common asset classes, can further propagate risks across the system (Roncoroni et al., 2019[85]; Alonso and Stupariu, 2019[86]). The extent and impact of such risk propagation are largely determined by the connectivity and concentration of significant financial institutions (Gai, Haldane and Kapadia, 2011[87]). For example, in Hungary, it was found that five banks held the majority of assets that depended on nature, increasing the risks of contagion (Boffo et al., 2024[88]). In general, financial institutions continue to allocate significant investments to unsustainable activities. Most private credit remains directed toward sectors that significantly impact and depend on water, including ICT, healthcare, consumer discretionary, industrials, and extraction of raw materials and natural resources (IMF, 2024[89]).
There are also substantial investment by major financial institutions in water dependent sectors. For example, globally systemically important institutions such as Wells Fargo, Bank of New York Mellon, and Morgan Stanley are major shareholders in Phillips 66 - an extractive company with a CDP water score of C, indicating significant water-related risks (Fintel, 2024[90]; CDP, 2023[91]).The longer and more complex the credit intermediation chains - particularly those involving investments in ETFs and trusts - the higher the risk of contagion, as it becomes more challenging to manage when information on these links is limited (Alonso and Stupariu, 2019[86]). Furthermore, even financial institutions actively addressing water-related financial risks can still be affected by contagion from other entities within the system.
Feedback loops can also arise from the financial sector’s response to water-related risk. Nature- and water-related risks are not only amplified by the financial system but also through feedback loops with the real economy (BIS, 2021[52]; NGFS, 2024[6]; FSB, 2024[83]). These dynamics can initially intensify mild shocks, enabling them to propagate across financial institutions (FSB, 2024[83]). If banks react to rising water-related risk by rapidly pulling back credit from certain regions or industries, this could exacerbate economic distress in those areas – potentially making the water crisis worse by undermining investment in adaptation (for example, firms can’t get loans to improve water efficiency, so the water situation deteriorates further). This, in turn, can loop back as even higher defaults and losses, creating a vicious cycle. Conversely, a lack of insurance availability for water disasters can leave economies more vulnerable and recovery slower, which feeds back to higher credit losses for banks. Another systemic consideration is correlation risk: many financial actors may unknowingly be exposed to the same water-related risk hotspot (e.g. global investors holding bonds from a cluster of cities all reliant on a single river basin). When that hotspot faces a crisis, what seemed like diversified portfolios may all suffer simultaneously, stressing the system’s shock absorbers.
Moreover, by continuing to finance harmful activities, financial institutions reinforce a feedback loop that increases financial materiality through heightened exposure to both transition and physical risks arising from degradation of water ecosystems (Kedward, Ryan-Collins and Chene, 2021[92]; OECD, 2023[1]). For instance, in 2023 alone, approximately USD 705 billion was directed to the fossil fuel industry, a sector heavily dependent on, and impactful on water ecosystems (Rainforest Action Network (RAN) et al., 2024[93]).
There are early warning signs of such systemic dimensions. For instance, analysis indicates that sovereign climate risks, including notably water-related risks, amounts to about USD 78 trillion, equivalent to about 57% of the world's current GDP at Power Purchase Parity (PPP), which is situated along flood-prone coastlines, riverways, and low-lying deltas (Four Twenty Seven, 2020[94]). A systemic water supply failure – say, the collapse of water availability in a major economic region – would therefore send shockwaves through trade, investment portfolios, and banking systems worldwide.
Overall, this means that water-related risks can no longer be viewed as idiosyncratic or niche concerns: in aggregate, they carry systemic implications. Financial supervision must therefore incorporate environmental risk analysis, ensuring that buffers and safeguards are adequate for correlated water stress events. Policy coordination is also key: financial authorities, water regulators, and government planning agencies need to communicate to avoid perverse outcomes (for example, banks simultaneously divesting from a water-stressed region without a plan for transition finance).
On the positive side, early action to build resilience, such as by promoting diversified water sources, developing insurance schemes like drought or flood pools, or investing in water infrastructure to boost resilience, can all reduce systemic risk over time by lowering the potential severity of water shocks. In summary, safeguarding the financial system against water-related crises is an integral part of ensuring long-term economic stability, and it requires a forward-looking, holistic approach from supervisors.
References
[59] Abedifar, P., S. Kashizadeh and S. Ongena (2024), “Flood, farms and credit: The role of branch banking in the era of climate change”, Journal of Corporate Finance, Vol. 85, p. 102544, https://doi.org/10.1016/j.jcorpfin.2024.102544.
[86] Alonso, J. and P. Stupariu (2019), “Financial system interconnectedness”, Financial Stability Review, No. 37, Banco de Espana, https://www.bde.es/f/webbde/GAP/Secciones/Publicaciones/InformesBoletinesRevistas/RevistaEstabilidadFinanciera/19/noviembre/Financial_system_interconnectedness.pdf (accessed on 10 October 2024).
[61] Bafin (2020), Guidance Notice on Dealing with Sustainability Risks.
[3] Bhowmik, S. (2020), “Ecological and Economic Importance of Wetlands and Their Vulnerability”, https://doi.org/10.4018/978-1-7998-1226-5.ch006.
[52] BIS (2021), Climate-related risk drivers and their transmission channels, https://www.bis.org/bcbs/publ/d517.pdf (accessed on 19 August 2024).
[84] BIS (2019), The Basel Framework, https://www.bis.org/baselframework/BaselFramework.pdf (accessed on 10 October 2024).
[88] Boffo, R. et al. (2024), “Assessing nature-related risks in the Hungarian financial system”, OECD Environment Working Papers, No. 243, OECD, https://www.oecd-ilibrary.org/finance-and-investment/assessing-nature-related-risks-in-the-hungarian-financial-system_24fd70e3-en (accessed on 29 August 2024).
[80] Boston Common Asset Management (2017), “Investors Urge Banks to Support Re-routing Dakota Access Pipeline, Protect Water”, PR Newswire.
[44] Brouwer, R. and M. Hofkes (2008), “Integrated hydro-economic modelling: Approaches, key issues and future research directions”, Ecological Economics, Vol. 66/1, pp. 16-22, https://doi.org/10.1016/j.ecolecon.2008.02.009.
[20] CDP (2024), Global water Report 2023, CDP, London, UK, https://www.cdp.net/en/insights/global-water-report-2023 (accessed on 1 April 2025).
[11] CDP (2024), Stewardship at the Source Driving water action across supply chains, https://www.cdp.net/en/responses.
[82] CDP (2023), Financial Institutions are Valuing Water, CDP, https://www.cdp.net/en/insights/financial-institutions-are-valuing-water.
[22] CDP (2023), Global Water Report 2022, https://www.cdp.net/en/responses.
[91] CDP (2023), Phillips 66 - CDP Water, https://www.cdp.net/en/responses/44635/Phillips-66?back_to=https%3A%2F%2Fwww.cdp.net%2Fen%2Fresponses%3Ffilters%255Bprogrammes%255D%255B%255D%3DWater%26per_page%3D20%26queries%255Bname%255D%3D66%26sort_by%3Daccount_name%26sort_dir%3Dasc&filters%5Bprogrammes%5D%5B%5D=Water&queries%5Bname%5D=66 (accessed on 10 October 2024).
[37] CDP (2022), High and Dry: How Water Issues Are Standing Assets -A report commissioned by the Swiss Federal Office for the Environment (FOEN), CDP, London, https://www.cdp.net/en/research/global-reports/high-and-dry-how-water-issues-are-stranding-assets (accessed on 6 January 2023).
[47] Christoffersen, P. (2003), ELEMENTS OF FINANCIAL RISK MANAGEMENT.
[50] CISL (2022), Nature-related financial risk: use case Impact of water curtailment on the credit rating of heavy industry companies in East Asia, https://www.cisl.cam.ac.uk/files/cisl_hsbc_water_stress_heavy_industry_credit_risk_apr_22.pdf (accessed on 19 August 2024).
[65] CISL (2021), Handbook for Nature-related Financial Risks: Key concepts and a framework for identification, https://www.cisl.cam.ac.uk/system/files/documents/handbook-for-nature-related-financial.pdf (accessed on 26 April 2024).
[33] CISL and HSBC (2022), Nature-related financial risk: use case. Impact of water curtailment on credit rating of heavy industry companies in East Asia, University of Cambridge Institute for Sustainability Leadership (CISL) and HSBC.
[55] Colesanti Senni, C., S. Goel and A. von Jagow (2024), “Economic and financial consequences of water risks: The case of hydropower”, Ecological Economics, Vol. 218, p. 108048, https://doi.org/10.1016/j.ecolecon.2023.108048.
[81] Commissaire de Justice (2023), Assignation Devant Le Tribunal Judiciaire De Paris Comissão Pastoral da Terra and Notre Affaire à Tous v. BNP Paribas, https://climatecasechart.com/wp-content/uploads/non-us-case-documents/2023/20230227_19040_summons.pdf (accessed on 8 October 2024).
[21] Davies, L. and M. Martini (2023), “Watered down? Investigating the financial materiality of water-related risks”, OECD Environment Working Papers, No. 224, OECD Publishing, Paris, https://doi.org/10.1787/c0f4d47d-en (accessed on 25 September 2024).
[26] DNB (2024), Nature-related financial risks in our own account investments: An exploratory case study and deep dive in electric utilities, https://www.dnb.nl/media/q5jf0td4/dnb-analyse-nature-related-financial-risks-in-our-own-account-investments-an-exploratory-case-study-and-deep-dive-in-electric-utilities.pdf#page=16.20 (accessed on 16 September 2024).
[78] ECB (2020), Guide on climate-related and environmental risks: Supervisory expectations relating to risk management and disclosure, https://www.bankingsupervision.europa.eu/ecb/pub/pdf/ssm.202011finalguideonclimate-relatedandenvironmentalrisks~58213f6564.en.pdf.
[74] EIOPA (2023), EIOPA Staff paper on nature- related risks and impacts for insurance, https://www.eiopa.europa.eu/system/files/2023-03/EIOPA%20Staff%20paper%20-%20Nature-related%20risks%20and%20impacts%20for%20insurance.pdf#page=15.15 (accessed on 7 October 2024).
[7] ENCORE Partners (2024), ENCORE: Exploring Natural Capital Opportunities, Risks and Exposure, https://encorenature.org (accessed on 13 June 2024).
[2] FAO (2024), AQUASTAT - FAO’s Global Information System on Water and Agriculture, https://www.fao.org/aquastat/en/ (accessed on 26 April 2024).
[5] Faunt, C. et al. (2016), “Water availability and land subsidence in the Central Valley, California, USA”, Hydrogeology Journal, Vol. 24/3, pp. 675-684, https://doi.org/10.1007/s10040-015-1339-x.
[4] Fessahaye, A. et al. (2025), “Groundwater Over-Extraction: Comprehensive Review of Socio-economic Impacts and Pathways to Sustainable Management”, European Journal of Theoretical and Applied Sciences, Vol. 3/2, pp. 190-211, https://doi.org/10.59324/ejtas.2025.3(2).15.
[24] FfB (2025), FfB Foundation Launches Sovereign Debt Focus Group to Bridge the Nature-Finance Gap, Finance for Biodiversity (FfB) foundation, https://www.financeforbiodiversity.org/ffb-foundation-launches-sovereign-debt-focus-group-to-bridge-the-nature-finance-gap/ (accessed on 21 July 2025).
[90] Fintel (2024), PSX - Phillips 66 Stock - Stock Price, Institutional Ownership, Shareholders (NYSE), https://fintel.io/so/us/psx (accessed on 10 October 2024).
[58] Foroudi, L. (2020), “How Cape Town’s drought led to a housing market downturn”, Financial Times, https://www.ft.com/content/89672cac-49ce-11ea-aee2-9ddbdc86190d (accessed on 17 April 2025).
[31] Forslid, R. and M. Sanctuary (2023), “Discussion paper: DP17855 Climate Risks and Global Value Chains: The impact of the 2011 Thailand flood on Swedish firms”, Centre for Economic Policy Research, Vol. DP17855, https://cepr.org/publications/dp17855 (accessed on 17 April 2025).
[94] Four Twenty Seven (2020), Measuring what matters: new approach to assessing sovereign climate risk, https://www.preventionweb.net/publication/measuring-what-matters-new-approach-assessing-sovereign-climate-risk.
[83] FSB (2024), Stocktake on Nature-related Risks- Supervisory and regulatory approaches and perspectives on financial risk, Financial Stability Board (FSB), https://www.fsb.org/uploads/P180724.pdf (accessed on 10 February 2025).
[87] Gai, P., A. Haldane and S. Kapadia (2011), “Complexity, concentration and contagion”, Journal of Monetary Economics, Vol. 58/5, pp. 453-470, https://doi.org/10.1016/j.jmoneco.2011.05.005.
[14] Global Commission on the Economics of Water (2024), The Economics of Water: Valuing the Hydrological Cycle as a Global Common Good, Global Commission on the Economics of Water, https://watercommission.org/publications/ (accessed on 28 February 2025).
[28] Global Commission on the Economics of Water (2024), The Economics of Water: Valuing the Hydrological Cycle as a Global Common Good, Global Commission on the Economics of Water, https://watercommission.org/publications/ (accessed on 28 February 2025).
[57] Global Commission on the Economics of Water (2023), The What, Why and How of the World Water Crisis: Global Commission on the Economics of Water Phase 1 Review and Findings, The Global Commission on the Economics of Water, Paris, http://watercommission.org/publication/phase-1-review-and-findings (accessed on 6 February 2025).
[12] Greenpeace (2011), Dirty Laundry, https://www.greenpeace.org/static/planet4-international-stateless/2011/07/2303cc74-dirty-laundry-12pages.pdf (accessed on 8 August 2024).
[45] Harou, J. et al. (2009), “Hydro-economic models: Concepts, design, applications, and future prospects”, Journal of Hydrology, Vol. 375/3-4, pp. 627-643, https://doi.org/10.1016/j.jhydrol.2009.06.037.
[19] Hofste, R. et al. (2019), Aqueduct 3.0: Updated decision relevant global water risk indicators. Technical note., World Resources Institute (WRI), Washington DC, USA, https://www.wri.org/resources/data-sets/aqueduct-global-maps-30-data (accessed on 8 April 2025).
[89] IMF (2024), Global Financial Stability Report, April 2024, International Monetary Fund, Washington, D.C., https://doi.org/10.5089/9798400257704.082.
[54] IMF (2023), Global Financial Stability Report 2023 - Financial and Climate Policies for a High-Interest-Rate Era, International Monetary Fund (IMF), https://www.astrid-online.it/static/upload/imf_/0000/imf_gfsr_10-23.pdf (accessed on 21 July 2025).
[53] IMF (2020), Global Financial Stability Report: Markets in the Time of COVID-19, International Monetary Fund, Washington, https://www.imf.org/en/Publications/GFSR/Issues/2020/04/14/global-financial-stability-report-april-2020#Chapter5 (accessed on 10 January 2023).
[27] Ingraham, C. (2017), “Houston is experiencing its third ‘500-year’ flood in 3 years. How is that possible?”, Washington Post, https://www.washingtonpost.com/news/wonk/wp/2017/08/29/houston-is-experiencing-its-third-500-year-flood-in-3-years-how-is-that-possible/ (accessed on 16 April 2025).
[17] Insight Investment (2024), Water risk: a ripple effect. Nature-related risks in corporate bonds, BNY Mellon Investment Management, New York, USA, https://www.bny.com/assets/investments/imemea/pdfs/water_risk_and_corporate_bonds.pdf (accessed on 15 April 2025).
[92] Kedward, K., J. Ryan-Collins and H. Chene (2021), “Understanding the financial risks of nature loss: exploring policy options for financial authorities”, SUERF Policy Briefs, No. 115, SUERF.
[60] Klomp, J. (2014), “Financial fragility and natural disasters: An empirical analysis”, Journal of Financial Stability, Vol. 13, pp. 180-192, https://doi.org/10.1016/j.jfs.2014.06.001.
[38] Koren, O., B. Bagozzi and T. Benson (2021), “Food and water insecurity as causes of social unrest: Evidence from geolocated Twitter data”, Journal of Peace Research, Vol. 58/1, pp. 67-82, https://doi.org/10.1177/0022343320975091.
[41] Laczynski, P. et al. (2015), “Natural disasters and their impacts on supply chains”.
[67] Lang, Q. et al. (2023), “The interaction of climate risk and bank liquidity: An emerging market perspective for transitions to low carbon energy”, Technological Forecasting and Social Change, Vol. 191, p. 122480, https://doi.org/10.1016/j.techfore.2023.122480.
[76] Leyco, C. (2024), Flooding forces big banks to temporarily close some branches, https://mb.com.ph/2024/7/24/flooding-forces-big-banks-to-temporarily-close-some-branches (accessed on 7 October 2024).
[79] Michel, M. (2017), “Post-truth reputational risk: The Wells Fargo saga”, Global Trade Review, https://www.gtreview.com/magazine/volume-15issue-5/post-truth-reputational-risk-wells-fargo-saga/ (accessed on 17 April 2025).
[63] Mirza, N. et al. (2023), “The impact of green lending on banking performance: Evidence from SME credit portfolios in the BRIC”, Economic Analysis and Policy, Vol. 77, pp. 843-850, https://doi.org/10.1016/j.eap.2022.12.024.
[10] Molnar, K. and D. Sasarean (2021), “Does Your Company Face Water-Related Investment Risk?”, https://www.morningstar.com/economy/does-your-company-face-water-related-investment-risk (accessed on 21 July 2025).
[49] Moody’s (2023), Trillions of dollars in global sectors’ debt highly exposed to environmental risks, https://www.moodys.com/web/en/us/about/insights/data-stories/2023-environmental-credit-risk-exposure.html (accessed on 19 August 2024).
[66] Morgan, A. et al. (2019), LINKING WATER RISK AND FINANCIAL VALUE-PART I.
[71] MunichRe (2020), https://www.munichre.com/en/risks/natural-disasters-losses-are-trending-upwards/floods-and-flash-floods-underestimated-natural-hazards.html.
[6] NGFS (2024), Nature-related Financial Risks: a Conceptual Framework to guide Action by Central Banks and Supervisors [Final version], https://www.ngfs.net/sites/default/files/medias/documents/ngfs-conceptual-framework-nature-risks.pdf (accessed on 19 August 2024).
[34] NGFS (2023), Nature-related Financial Risks: a Conceptual Framework to guide Action by Central Banks and Supervisors, Network for Greening the Financial System (NGFS), https://www.ngfs.net/system/files/import/ngfs/medias/documents/ngfs_conceptual-framework-on-nature-related-risks.pdf.
[40] NGFS (2023), Recommendations toward the development of scenarios for assessing nature-related economic and financial risks, Network for Greening the Financial System, Paris.
[36] OECD (2025), Global Drought Outlook: Trends, Impacts and Policies to Adapt to a Drier World, OECD Publishing, Paris, https://doi.org/10.1787/d492583a-en.
[1] OECD (2023), A supervisory framework for assessing nature-related financial risks, OECD Business and Finance Policy Papers, No. 33, OECD Publishing.
[51] Özsoy, S., M. Rasteh and E. Yönder (2025), “Understanding drought shocks: Bank financial stability and loan performance”, Global Finance Journal, Vol. 65, p. 101100, https://doi.org/10.1016/j.gfj.2025.101100.
[56] Painter, M. (2020), “An inconvenient cost: The effects of climate change on municipal bonds”, Journal of Financial Economics, Vol. 135/2, pp. 468-482, https://doi.org/10.1016/J.JFINECO.2019.06.006.
[15] Pellet, V. et al. (2020), “Long-term total water storage change from a Satellite Water Cycle reconstruction over large southern Asian basins”, Hydrology and Earth System Sciences, Vol. 24/6, pp. 3033-3055, https://doi.org/10.5194/hess-24-3033-2020.
[93] Rainforest Action Network (RAN), E. et al. (2024), Banking on Climate Chaos, https://www.bankingonclimatechaos.org/wp-content/uploads/2024/07/BOCC_2024_vF3.pdf (accessed on 17 October 2024).
[13] Restiani, P. and A. Khandelwal (2016), WATER GOVERNANCE MAPPING REPORT: TEXTILE INDUSTRY WATER USE IN INDIA, https://siwi.org/wp-content/uploads/2017/06/Water-Governance-Mapping-Report-INDIA.pdf (accessed on 8 August 2024).
[39] Reuters (2025), Worsening water crisis can weigh on India’s sovereign credit strength, Moody’s says, Reuters, Mumbai, India.
[85] Roncoroni, A. et al. (2019), “Interconnected banks and systemically important exposures”, ECB Working Paper Series, No. 2331, ECB, https://www.ecb.europa.eu/pub/pdf/scpwps/ecb.wp2331~ab59126ee2.en.pdf (accessed on 10 October 2024).
[43] Salin, M., K. Kedward and N. Dunz (2024), Assessing Integrated Assessment Models for Building Global Nature-Economy Scenarios, Banque de France, Paris, https://www.banque-france.fr/en/publications-and-statistics/publications/assessing-integrated-assessment-models-building-global-nature-economy-scenarios (accessed on 21 July 2025).
[68] SIF (2021), Nature-Related Risks In The Global Insurance Sector, https://sustainableinsuranceforum.org/wp-content/uploads/2021/11/UN_Nature-Related-Risks-in-the-Global-Insurance-Sector_v9.pdf#page=28.06 (accessed on 7 October 2024).
[16] Stadler, K. et al. (2018), “EXIOBASE 3: Developing a Time Series of Detailed Environmentally Extended Multi‐Regional Input‐Output Tables”, Journal of Industrial Ecology, Vol. 22/3, pp. 502-515, https://doi.org/10.1111/jiec.12715.
[64] Su, C. et al. (2022), “Resource extraction, greenhouse emissions, and banking performance”, Resources Policy, Vol. 79, p. 103122, https://doi.org/10.1016/j.resourpol.2022.103122.
[32] Swiss RE (2021), Economic insights The world’s costliest flood: the 2011 Thailand flood, 10 years on, Swiss Re, https://www.swissre.com/dam/jcr:18bd73c2-4bf1-4e47-91b3-c3bb7c5c96e3/EI-21-2021-thailand-10year-anniversary.pdf (accessed on 21 July 2025).
[73] Swiss Re (2023), Natural catastrophes in focus: Floods, https://www.swissre.com/risk-knowledge/mitigating-climate-risk/floods.html#:~:text=Risk%20management&text=In%20the%20decade%20through%202022,losses%20during%20the%20previous%20decade. (accessed on 15 July 2024).
[70] SwissRE (2022), Natural catastrophes in 2021: the floodgates are open, https://www.swissre.com/institute/research/sigma-research/sigma-2022-01.html#:~:text=In%202021%2C%20there%20were%20more,are%20becoming%20ever%20more%20apparent.
[72] SwissRE (2021), Sigma - Natural catastrophes in 2020: secondary perils in the spotlight, but don’t forget primary-peril risks, https://www.swissre.com/dam/jcr:16271084-77b5-478f-b6ce-8948f94cba4e/sigma-1-2021-secondary-perils-en.pdf.
[46] Tanoue, M. et al. (2020), “Estimation of Direct and Indirect Economic Losses Caused by a Flood With Long‐Lasting Inundation: Application to the 2011 Thailand Flood”, Water Resources Research, Vol. 56/5, https://doi.org/10.1029/2019WR026092.
[23] TNFD (2025), IFRS Foundation and TNFD formalise collaboration to provide capital markets with high-quality nature-related information, e Taskforce on Nature-related Financial Disclosures (TNFD), https://tnfd.global/ifrs-foundation-and-tnfd-collaboration-to-provide-capital-markets-with-high-quality-nature-related-information/ (accessed on 15 April 2025).
[48] TNFD (2023), Guidance on the identification and assessment of nature related issues: The LEAP approach, https://tnfd.global/wp-content/uploads/2023/08/Guidance_on_the_identification_and_assessment_of_nature-related_Issues_The_TNFD_LEAP_approach_V1.1_October2023.pdf?v=1698403116 (accessed on 19 August 2024).
[8] UN (2024), System of Environmental-Economic Accounting Ecosystem Accounting (SEEA-EA), United Nations (UN), European Union, Food and Agriculture Organization of the United Nations, International Monetary Fund, Organisation for Economic Co-operation and Development, The International Bank for Reconstruction and Development/The World Bank, https://seea.un.org/sites/seea.un.org/files/documents/EA/seea_ea_f124_web_12dec24.pdf (accessed on 8 April 2025).
[75] UNEP (2023), Addressing water-related conflict and disasters, https://www.unep.org/explore-topics/water/what-we-do/addressing-water-related-conflict-and-disasters#:~:text=Most%20of%20the%20impacts%20of,impact%20on%20societies%20and%20economies.
[25] UNEP FI and WWF (2024), Navigation Nature-Related Regulations for Banks, United Nations Environment Programme Finance Initiative and World Wide Fund for Nature., https://wwf.panda.org/wwf_news/?13243466/New-report-maps-nature-related-regulations-for-banks-finding-rise-in-initiatives-across-key-regions (accessed on 14 February 2025).
[9] UNEP-WCMC (2024), Explanatory note on the updated ENCORE knowledge base outlining business dependencies and impacts on nature, United Nations Environment Programme World Conservation Monitoring Centre , London, https://encorenature.org/resources/explanatory-note-on-the-updated-encore-knowledge-base-outlining-business-dependencies-and-impacts-on-nature (accessed on 10 February 2025).
[42] World Bank (2016), “High and Dry: Climate Change, Water, and the Economy”, https://www.worldbank.org/en/topic/water/publication/high-and-dry-climate-change-water-and-the-economy (accessed on 17 April 2025).
[30] World Bank (2012), Thai flood 2011 : rapid assessment for resilient recovery and reconstruction planning (Vol. 1 of 2) : Overview, World Bank Group, Washington DC, USA, https://documents.worldbank.org/en/publication/documents-reports/documentdetail/677841468335414861/overview (accessed on 16 April 2025).
[29] WWF (2023), “High Cost of Cheap Water: The true value of water and freshwater ecosystems to people and planet”, https://wwf.panda.org/wwf_news/?9842941/water-report-2023 (accessed on 2 May 2024).
[18] WWF (2023), WWF Water Risk Filter Methodology Documentation, https://cdn.kettufy.io/prod-fra-1.kettufy.io/documents/riskfilter.org/WaterRiskFilter_Methodology.pdf.
[77] WWF (2019), Hidden Risks And Untapped Opportunities: Water And The Indian Banking Sector, https://wwfeu.awsassets.panda.org/downloads/hidden_risks_and_untapped_opportunities_water_and_the_indian_banking_sector_1_.pdf (accessed on 7 October 2024).
[69] WWF and CDP (2024), Addressing The Giants, https://wwfes.awsassets.panda.org/downloads/wwf-addressing-the-giants-reportv4.pdf (accessed on 18 October 2024).
[62] Yu, B. et al. (2022), “Forecasting credit ratings of decarbonized firms: Comparative assessment of machine learning models”, Technological Forecasting and Social Change, Vol. 174, p. 121255, https://doi.org/10.1016/j.techfore.2021.121255.
[35] Zaveri, E., R. Damania and N. Engle (2023), Droughts and Deficits: The Global Impact of Droughts on Economic Growth, World Bank Group, Washington DC, USA, https://openknowledge.worldbank.org/handle/10986/39840 (accessed on 17 April 2025).
← 1. More information: https://www.globalwater.online/
← 2. More information on CSRD: https://finance.ec.europa.eu/capital-markets-union-and-financial-markets/company-reporting-and-auditing/company-reporting/corporate-sustainability-reporting_en
← 3. More information on ISSB standards: https://sasb.ifrs.org/standards/
← 4. More information on IFRS S2: https://www.ifrs.org/issued-standards/ifrs-sustainability-standards-navigator/ifrs-s2-climate-related-disclosures/
← 5. More information on GRI: https://www.globalreporting.org/
← 6. More information on European Sustainability Reporting Standards E3: https://www.efrag.org/sites/default/files/sites/webpublishing/SiteAssets/ED_ESRS_E3.pdf
← 7. More information on the European Sustainability Reporting Standards E2: https://www.efrag.org/sites/default/files/sites/webpublishing/SiteAssets/09%20Draft%20ESRS%20E2%20Pollution%20November%202022.pdf
← 8. More information on TNFD sector guidance: https://tnfd.global/new-set-of-sector-guidance-published/