Synthesis

INTRODUCTION

Climate and ecological breakdowns already impact human development and economics (IPCC 2022). Without urgent action, global warming and biodiversity loss could push the planet past critical thresholds, leading to rapid, undesirable outcomes (Staal et al. 2020, McKay et al. 2022). The interaction between complex ecosystems, such as the Amazon and the Arctic, suggests that rapid changes in one of these systems can have cascading effects and amplify those effects (Rocha et al. 2018, Rocha 2022). The cascading effects of climate change or nature-related risks impacting multiple economic and financial sectors potentially result in destabilization and are referred to as “domino effects,” which carry enormous social and economic costs (Bastien-Olvera and Moore 2022, Spaiser et al. 2024, Ameli et al. 2025) and threaten economic and financial stability (S. Batten 2018, unpublished manuscript). Unlike direct risk transmission, domino effects involve successive impacts, where a disruption causes another, increasing vulnerabilities and potentially leading to systemic instability.

Financial institutions such as banks, asset managers, pension funds, and multilateral banks play a crucial role in the global economy by financing economic activities that alter the climate system and the biosphere (Crona et al. 2021, Galaz et al. 2023). Examples include critical biomes associated with the stability of the climate system, such as boreal forests and the Amazon biome (Galaz et al. 2018) and marine systems (Jouffray et al. 2019). Climate change and nature degradation also threaten economic stability by creating novel forms of poorly understood economic and financial risks (Bolton et al. 2020; UN PRI 2020). For example, missing the 2 °C target of the Paris Agreement could lead to a 20-fold increase in economic losses by 2050 because of more frequent and intense extreme weather events in coastal cities (Woetzel et al. 2020). Furthermore, extreme weather events could cost up to US$14 trillion annually by 2100 (Jevrejeva et al. 2018). Given the financial impact on the climate and biodiversity crisis, interpretations of the role of finance in tackling Article 2.1.c of the Paris Agreement, which calls for using finance to transition toward low greenhouse gas emissions and climate-resilient development. Similarly, the Convention on Biological Diversity, particularly in the Kunming-Montreal Global Biodiversity Framework, emphasizes the need to increase biodiversity resources, including aligning public and private financial flows with biodiversity objectives. Both frameworks imply a need to grant non-state actors greater finance access and redirect investment toward low-carbon, nature-positive economies.

The strategies to curb, mitigate, and adapt to climate change and ecosystem degradation are also expected to create additional climate and nature-related financial risks and opportunities by inducing policy, technological, and behavioral changes with potential economic impacts (EIOPA 2021a). For example, stricter climate policies might result in assets such as fossil fuel investments becoming stranded, suffering an unanticipated or premature downward valuation, write-offs, or revaluations (FSB 2020, NGFS 2020a). These environment-related financial risks can also be indirect through non-linear effects, negatively impacting economic sectors in new ways (Battiston et al. 2021, Crona et al. 2021).

Environment-related financial risks encompass the financial risks arising from climate change and other natural degradation phenomena. Whereas climate-related financial risks refer to the economic or financial potential losses resulting from climate change’s consequences, nature-related risks entail the exposure of financial actors to nature degradation in the form of biodiversity and ecosystem loss (NGFS 2022, Kedward et al. 2023a). These risks are difficult to predict because of the multiple interactions and potential domino effects between climate and ecosystems (Rocha et al. 2018), potentially destabilizing the financial sector (Bolton et al. 2020, Crona et al. 2021, Kedward et al. 2023b).

In recent years, there has been a rapid expansion of studies examining the risks posed to the financial sector by the combined impacts of climate change and ecological degradation. Each uses different approaches, focus areas, models, and data sources to assess these complex connected risks. Yet, to the best of our knowledge, there is no holistic overview of the main mechanisms of environment-related financial risks. Because of the cross-system and cross-scale interactions and complex temporal and spatial scale properties of environment-related financial risks (Bolton et al. 2020, Kedward et al. 2023a), we believe scholars and practitioners can benefit from using a complex systems thinking approach to study these types of financial risks.

Complex system thinking can help scholars learn about the structure and dynamics of intricate elements of the world, design leverage policies for problem resolution, and catalyze their successful implementation and change (Sterman 2002, Meadows 2008). Drawing from engineering control theory and the modern theory of nonlinear dynamical systems, complex systems thinking involves developing simplified representations of systems that allow us to learn about their structure and dynamics (Sterman 2002, Bossel 2007).

Causal loop diagrams (CLDs) are a complex system-thinking technique to delineate and potentially model social and ecological systems’ dynamics by visually representing causal relationships (Sterman 2002). CLDs have proven to help study economic dynamics in the past (Meadows et al. 1972, Sterman 2002, Bala et al. 2017). Because of the increasingly complex threat that climate change and nature degradation pose to the economy and financial systems (ECB 2020, Bastien-Olvera and Moore 2022, Kedward et al. 2023a), CLDs could offer a more comprehensive understanding of environment-related risk transmission channels. By mapping how environmental shocks propagate through interconnected variables, these diagrams can capture the domino effects that arise when an initial disturbance generates a chain of consequences across financial markets and the real economy.

Our study aims to create a CLD typology of the transmission channels for environment-related financial risks to provide a more comprehensive understanding of climate and nature-related risks. To achieve this, we conducted a systematic review of academic and non-academic literature on how financial entities are impacted by climate and nature-related risks. The review covers relevant publications from 2015 to early 2022, focusing on two main questions: (1) How is the finance literature defining the ways in which climate and nature-related financial risks are transmitted? (2) How are practitioners and researchers examining these environment-related financial risks? Answering these questions allowed us to assess the state of knowledge in this domain to develop a domino-effect typology of environment-related financial risks and identify research gaps in their study.

METHODS

Search criteria

We conducted a systematic literature review (Grant and Booth 2009). Searches were carried out in June 2021, with an update search in December 2021 on Scopus, resulting in 399 potential climate and nature degradation relevant publications. Based on expert recommendations in February 2022, an additional search was carried out in the suggested economic-related preprints Econstore and RePec to include relevant but potentially yet-to-be-published articles, which led to nine additional publications. Given the increasing number of non-peer-reviewed publications on this topic, we conducted an additional search across the web pages of relevant financial institutions to make our analysis more comprehensive in March 2022. All relevant reports, working papers, and occasional papers in English published between 2015 and 2021, along with additional publications recommended by experts and preprints from 2021 that were subsequently published in 2022, were included in the preliminary analysis. Online information only available on dynamic websites was excluded. We chose 2015 as the starting year because the Paris Agreement explicitly called for global action to address climate-related risks. We identified 120 additional reports from a strategic selection of relevant and influential international organizations in this domain, including the Network for Greening the Financial System (NGFS) and Task Force on Climate-related and Disclosures (TFCD; see Appendix 2; Table A.1). We classified the consulted institutions into seven categories: multilateral financial institutions, central banks, think tanks, international non-governmental organizations, academic institutions, financial regulators, and multilateral forums for policy makers (see Appendix 2; Table A.2). We selected 31 reports based on the type of institution and the number of publications per category to get as diverse a set of reports as possible. The publications included were selected to capture the categories’ most elaborate reasoning on nature- and climate-related financial risks. To capture relevant publications not available in academic databases, we later emailed a list of experts requesting additional academic papers and grey literature describing and (or) measuring climate-nature-finance domino effects, resulting in 33 suggested additional publications. The experts were selected from known international science-policy domains in the climate- and nature-related financial risk domain. Note that the selection was not intended to be complete but to include additional relevant material that could complement published literature.

Inclusion criteria and data analysis

Based on the publications’ abstracts and titles, we first included all unique documents whose aim was to examine, describe, or measure the impacts, effects, and (or) risks of climate change and (or) environmental degradation on the financial system (n = 108). The impacts of investments in climate change and nature degradation could have both direct and indirect effects. These impacts could also affect financial assets through various pathways (Wassénius and Crona 2022, Chenet 2024). It should be noted that additional search terms could have been added, yet we assumed that the terms “impacts,” “effects,” and “risks” capture the most relevant literature.

After a full-text reading, we only included studies with a sufficient description or measurement of one risk, effect, or impact of climate change or ecosystem degradation on finance. The selection process resulted in 88 relevant documents (Fig. 1). Figure 1 summarizes the procedure for selecting relevant publications for the analysis. For each chosen publication, we identified (1) the mechanisms of climate change and nature-related financial risks or potential impacts or effects; (2) the methods used to measure chain reaction or domino-effects; (3) the required data for analysis; and (4) the quantification of the impacts, scenarios, and projections. Each paper was appraised in detail by one author and overseen by another, with any concerns being resolved by the other. We classified publications based on the type of research conducted—empirical (i.e., refers to work based on original data collection), synthesis (i.e., relates to work based on a compilation of existing data), and conceptual (i.e., refers to work that is primarily conceptual or opinion, where arguments are not likely supported by references)—and the type of publication. Based on this systematic review, we developed a domino effect typology using nested causal loop diagrams (CLDs; Sterman 2002).

CLD domino effect typology

To develop the CLD typology, we conducted a text analysis of the mechanisms of climate change and nature-related financial risks identified after the full-text reading in NVivo. Following a qualitative content analysis approach (Kuckartz 2014), we first identified key climate, natural, economic, and financial variables, such as climate change, environmental degradation, economic growth, and inflation. Subsequently, we established cause-effect relationships between these variables using a plus or minus sign to indicate a proportional or inverse relationship, e.g., climate change + extreme weather events, or credit risk - willingness to lend.

Based on this, we created nine nested CLDs based on the types of environment-related financial risks described in the finance literature. The construction of these CLDs follows principles from system dynamics modeling (Sterman 2010), which is commonly used to map complex financial and economic feedback mechanisms. We made no distinction between the supporting information because our goal was to provide a comprehensive overview of the transmission mechanisms of environment-related financial risks. However, the reviewed literature supports all causal links, with references provided in the text.

To ensure coherence and clarity in the representation of financial risk transmission, we held multiple in-person and online meetings among the authors to refine and validate relationships found in the literature. These iterative discussions facilitated resolving ambiguities, harmonizing terminology, and more cohesive structuring of relationships. Throughout this process, we refined variables and causal links to ensure consistency and alignment of theoretical coherence. Our deductive approach depended directly on the sources reviewed, and no relationships were introduced independent of the literature.

To account for differences in the strength of supporting evidence, we used dashed lines to indicate relationships primarily supported by conceptual studies, while solid lines represent causal links that are well documented in empirical research or strongly backed by synthesis sources. This distinction ensures transparency regarding the robustness of the causal mechanisms presented. The authors reached saturation when establishing the cause-effect relationship between climate change and natural changes leading to systemic risks. The codes for the text analysis are presented in Appendix 1.

RESULTS

Climate and nature-related financial risks

Despite the growing number of studies examining environment-related financial risks, fewer studies have examined financial risks related to nature degradation (Appendix 3; Fig. A.1), and no publications have studied the trade-offs between these environmental risks. However, the impact of environment-related, i.e., both climate change and nature degradation-related, financial risks is expected to affect a wide range of actors across the economy (Appendix 3; Fig. A.2). More than half of the publications expect climate change and nature degradation to affect financial actors at the global, regional, or national scales (Appendix 3; Fig. A.3). In contrast, only 27 publications expect these impacts to be felt at the local or sub-national level, even though effects are occurring in both the short and long term (Appendix 3; Fig. A.4).

Moreover, despite the generalized effect of environment-related risks, our findings indicate that most climate- and nature-related risk assessments have been conducted for Global North economies like the USA, the UK, and Europe with some additional publications addressing economic impacts in other large economies in the Global South such as China and Brazil (Fig. 2). Surprisingly, 40 publications mentioned ocean-related financial risks compared to 84 studies mentioning inland-related financial risks. However, only four studies considered ocean-related financial risks beyond economic losses due to rising sea levels, ocean acidification, and rising temperatures.

These studies investigated the impact of climate change and ocean degradation on stranded ocean assets and technologies, offshore energy production, maritime transport, coastal and marine tourism, and the seafood industries, especially in Small Island Developing (SID) countries and Least Developed Countries (LDC; Jouffray et al. 2021, Tokunaga et al. 2021, UNEP FI SBE 2021, Sanctis et al. 2022). However, no studies have explored high- and deep-sea-related financial risks, such as reputational and liability risks in the deep-sea mining industries. Conversely, inland-related risks are examined from a broader perspective, including biodiversity and ecosystem services loss, agriculture, freshwater and forest loss and management, resource scarcity, terrestrial mining, and pollution (e.g., DNB 2020, Retsa et al. 2020, University of Cambridge Institute for Sustainability Leadership 2020, UN PRI 2020, World Economic Forum 2020, Baralon et al. 2021, NGFS 2022, Kedward et al. 2023b).

The literature generally presents the negative effects of climate change and nature degradation on the financial system. Still, more than half of the publications acknowledge the potential for new growth and investment opportunities linked to the transition to a low-carbon and greener economy. Only 13 publications suggest that climate change and nature degradation will have no net or long-term effect on the economy or financial sector (Appendix 3; Fig. A.5). These publications indicate that economic growth or income levels may bounce back to pre-extreme events trends (S. Batten 2018, unpublished manuscript), not compromise macroeconomic stability (Diluiso et al. 2021), or show no yield difference between green and conventional bonds, as well as limited financial risk under orderly transition scenarios (Osofsky et al. 2019, Palea and Drogo 2020).

Positive and negative environment-related risks are generally understood as sector-specific or systemic. Sector-specific risks are expected impacts on firms or sectors due to physical and transitional risks, while systemic risks can affect the entire financial system, potentially leading to a crisis (Bolton et al. 2020, Battiston et al. 2021). Physical risks are the projected hazards and material impacts of environmental impacts on the economy, while transitional risks arise from the actions taken to transition to a greener economy (M. Carney 2015, unpublished manuscript). Only a quarter of the publications do not mention physical or transitional risks, with 10 more publications addressing transitional risks (Appendix 3; Fig. A.6). Although more than half of the publications recognize the general uncertainty and complexity of environment-related risks on the financial systems (see Appendix 3; Fig. A.5), some publications point out transition risks are more difficult to assess because of the divergent effects that they might have on different sectors (Battiston et al. 2021, Bernardini et al. 2021, Diluiso et al. 2021).

Out of 88 publications, 59 recognize climate change and nature degradation as having a systemic impact. Battiston et al. (2021) argue the financial sector faces systemic shocks because of the complexity of environment-related risks and the interconnectedness among financial institutions. Some publications indicate that this results in non-linear and radically uncertain systemic risks that historical data cannot predict (Thomä and Chenet 2018, Chenet et al. 2021). Others suggest central banks and financial supervisors are essential in preventing these risks as macroprudential policies can enhance financial resilience against environment-related financial risks (ESRB 2016, Chenet et al. 2021).

The study of environment-related financial risks

Most publications base their findings on empirical evidence, with a minority conducting a synthesis or conceptual analysis (Appendix 3; Fig. A.7). Additionally, 79 (n = 39 grey literature) out of 88 articles mention at least one method to assess climate change or nature-related risks. Empirical studies use econometric methods (18), qualitative/case-study approaches (12), simulation system models (11), scenario or stress-testing analyses (2), or mixed methods (1). Only 33 (n = 29 grey literature) reflect on limitations, and 32 (n = 18 grey literature) highlight the advantages of the described method.

A key challenge in assessing environment-related risks is reaching standardized best-practices and ensuring data availability. Of 29 publications addressing methodological issues, 21 (n = 12 grey literature) mention the absence of standardized best-practices in assessing environment-related financial risks. Likewise, 51 (n = 23 grey literature) out of 54 reports addressing data availability argue insufficient data for proper risk assessments. However, only 22 (n = 11 grey literature) publications describe the type of data requirements for developing such additional analysis. Some publications recognize limited data availability for risk analysis is a widespread issue, mainly because firms and financial actors do not disclose their environmental and ecological footprints (Abramskiehn et al. 2015, ESRB 2016, Battiston et al. 2017, ECB 2020, FSB 2020, Caldecott et al. 2021, Chenet et al. 2021, ECB and ESRB 2021). These authors generally call for action from governments, central banks, and financial authorities to mandate the disclosure of this information (Abramskiehn et al. 2015, Deutz et al. 2020, University of Cambridge Institute for Sustainability Leadership 2020, Caldecott et al. 2021, IPSF 2021).

Understanding the timing and potential impact of climate- and nature-related financial risks on the broader financial system is also challenging for financial institutions (Kedward et al. 2021). Some experts suggest that better information is needed to assess accurately and price systemic environment-related risks (Rennert et al. 2022, Rising et al. 2022). However, others argue that because of the complex and uncertain nature of the interactions between climate, the biosphere, the economy, and the financial system, it is unlikely that systemic risks can be accurately quantified (Bolton et al. 2020, Kedward et al. 2021). Although scholars have proposed various methods such as integrated assessment models (IAMs), agent-based modeling, network-based approaches, qualitative risk assessment, and politically grounded analyses to address radical uncertainty (Chenet et al. 2021, 2022, Chenet 2024), there is still no consensus on which methods are the most effective alternatives.

Many publications refer to IAMs as the foremost tools for assessing environment-related financial risks (Campiglio et al. 2018, Monasterolo and Raberto 2018, Stolbova et al. 2018, Monasterolo et al. 2019, Bolton et al. 2020, Monasterolo 2020, NGFS 2020b, Bertram et al. 2021, Keppo et al. 2021, Liu et al. 2021, Svartzman et al. 2021, In et al. 2022; S. Batten 2018, unpublished manuscript). However, of the 44 empirical studies, only one draws on IAMs (Bertram et al. 2021), while two conceptual studies use IAM frameworks as a foundation to simulate and analyze complex climate-economy interactions, thereby supporting risk pricing and policy design in the context of energy and finance (Keppo et al. 2021In et al. 2022).

Still, IAMs are reported by authors to be often be needed for methods used by central banks, such as scenario analysis and stress-testing (S. Batten 2018, unpublished manuscript). IAMs are a type of scientific modeling that provides simplified representations of the interaction between the economy, society, and the environment. They employ cost-benefit analysis to identify effective climate mitigation policies or model potential pathways to achieve long-term policy objectives. However, IAMs have been criticized by some authors for oversimplifying the financial system and neglecting agent heterogeneity. IAMs are combined with scenario analysis to address these limitations to assess potential environment-related risks (ECB and ESRB 2021). This aims to create plausible representations of the future and explore the vulnerabilities of financial actors and firms to environmental changes, policies, and technological developments.

Some publications indicate that although climate-related risk assessments are based on standardized atmospheric metrics, most assessments of nature-related risks are based on the dependence of economic activities and sectors on ecosystem services (NGFS 2022). Furthermore, some authors argue that assessing nature-related financial risks is more complex than evaluating those induced by climate change for several reasons. Biodiversity and ecosystem loss are multidimensional, making it harder to create benchmarks and simple metrics (e.g., tons of atmospheric CO₂) to assess changes (Díaz et al. 2020, NGFS 2022). Additionally, the lack of clarity on how ecosystem services and the economy interact and the difficulty in determining the time horizon (or time delays) of environmental loss impacts increases the complexity of creating robust assessments of nature degradation as a source of financial risk. The lack of standardized data and metrics and limited expert knowledge to evaluate corporate risk, performance, and dependence linked to nature degradation pose additional challenges (DNB 2020, UN PRI 2020).

Domino effect typology of environment-related financial risks

Our review shows that financial actors are aware of the increasing risk that changes to the climate and biosphere pose to the financial system. This awareness is reflected in a growing body of published material; however, much of it is produced by financial institutions themselves, raising questions about the depth and independence of the findings analysis. We show that environment-related risks are expected to affect a wide range of actors and are likely to destabilize the overall financial and economic systems. However, studies on environment-related risks are concentrated in Global Northern economies, and only recently have other nature-related risks been integrated beyond those directly related to climate change. Moreover, our review shows that studying environment-related financial risks can be challenging given their inherent complexity and radical uncertainty, as well as the lack of suitable data and methods to address them.

Climate and nature-related financial risk assessments could benefit from complex systems thinking to better deal with complexity and radical uncertainty. Complex system thinking can help scholars understand environment-related risks, design effective policies, and implement successful changes by studying the structure and dynamics of the economic and financial systems (Meadows et al. 1972, Sterman 2002, Bala et al. 2017). To contribute to this, we use our literature review to develop a causal loop diagram (CLD) domino effect typology of environment-related financial risks. This typology features nine nested causal diagrams derived from the financial literature on physical and transition environment-related risks, being our primary contribution to the field.

In our typology, CLDs depict the feedback structure of climate-biosphere-finance. Arrows connect variables to show reported causal relationships, with positive connections indicating amplifying effects and negative ones showing dampening effects. Feedback loops, formed by causal chains that create a cycle, can reinforce or balance based on their overall polarity. Solid lines represent well-documented empirical or theoretical links causal relationships, dashed lines indicate conceptual causal mechanisms, and double lines indicate a time lag. Physical and transitional transmission channels are depicted in orange and purple, respectively.

The first three CLD typologies (damage and repair, damage liability, and damaged productivity) describe the transmission channels by which physical risks can lead to insurance, liability, credit, and operational risks and how these can destabilize the economy. We define liability risk as the potential exposure to legal action and financial loss that an individual, business, or organization faces when responsible for causing harm, injury, or damage to another party. Insurance risk refers to the risk of a change in value due to deviations between actual and expected insurance or reinsurance outcomes. On the other hand, credit risk is the potential that a bank borrower or counterparty will fail to meet its obligations according to the agreed terms. Finally, operational risk encompasses the potential for losses due to errors, breaches, interruptions, or damages (both intentional and accidental) caused by people, internal processes, systems, or external events.

Two additional CLD typologies (regulation of unsustainable investments and scale-up of green production) explain how transitioning to a greener economy can lead to a reduction of unsustainable investment and a scale-up of greener production. This transition will create new forms of insurance, liability, credit, operational, and market risks. Market risks are expected to arise from movements in stock prices, interest rates, exchange rates, and commodity prices to which an organization is exposed. We finish the section with an overview of the systemic typology. Three underlying CLDs (aggregate demand engine, green production cycle, and unsustainable production cycle), showing economic and financial causal relationships without any connection to climate or environmental change, were included in Appendix 4.

Damage and repair

Climate change will increase the intensity and frequency of extreme and chronic events, increasing infrastructure damage and repair costs in a highly unpredictable manner (Fig. 3; Abramskiehn et al. 2015, ESRB 2016, IAIS 2018, Andersson et al. 2019, Lamperti et al. 2019, Bateson and Sccardi 2020, Bernardini et al. 2021, FSOC 2021). With more money being allocated to finance costly infrastructure repairs, there is a growing inability of households and businesses to meet their payment obligations (liquidity risk), further decreasing borrowers’ ability to pay their loans (credit risk; NGFS 2020b, FSOC 2021, Svartzman et al. 2021). A large-scale liquidity crisis linked to extreme chronic and extreme events or ecosystem services loss results in a lack of cash or easily-convertible-to-cash assets across many businesses or financial institutions simultaneously, leading to widespread defaults and bankruptcies that compromise the stability of the economic system (systemic risk; ECB 2020). As the costs of damage and repairs grow, so do insurance (and thus reinsurance) costs, increasing the number of uninsurable assets and therefore further raising the cost of repairing damage to them; for example, insurance premiums increased up to 60% in Saxony following the 2002 flooding (ESRB 2016, Campiglio et al. 2018, IAIS 2018, Bolton et al. 2020, FSB 2020, NGFS 2020b, Caldecott et al. 2021, EIOPA 2021b, FSOC 2021; S. Batten 2018, unpublished manuscript) As households’ incomes decline because of increasing damage and repair costs, so does their ability to repay debts, increasing credit risk. Credit risk is also increased by the growing number of uninsured assets, reducing banks’ willingness to lend and thus increasing systemic risk (FSOC 2021).

Damage liability

As climate change and biodiversity loss increase the likelihood and intensity of extreme events, chronic impacts and loss of ecosystem functions and services (ecosystem loss), the liability risk faced by high-carbon and other unsustainable firms and investors increases (Fig. 4; IAIS 2018, Bateson and Sccardi 2020, ECB 2020, NGFS 2020b, 2023, Retsa et al. 2020, Bernardini et al. 2021, Caldecott et al. 2021). For example, in January 2018, the City of New York filed lawsuits against five fossil fuel companies to fund adaptation measures (IAIS 2018). Meanwhile, biodiversity-related liability risks may stem from actors failing to prevent, manage, or adapt to ecosystem impacts or failing to comply with regulatory requirements (Caldecott et al. 2021). For example, BP had to pay US$61.6 billion in court fees, penalties, and clean-up costs because of its 2010 oil spill in the Gulf of Mexico (NGFS 2020b). This can both increase insurance risk due to insurance claims on legal costs, and increase the fines and penalties faced by these actors, disrupting their revenue stream and thus increasing credit risk (ESRB 2016, Berenguer et al. 2021). Both insurance and credit risks (via reduced willingness to lend) increase systemic risk.

Damaged productivity

Climate change directly reduces the production of goods and services in three ways: chronic impacts (such as rising burdens of heat, humidity, and disease) reduce labor productivity; chronic and extreme climatic events disrupt and damage ecosystem function, reducing the availability of ecosystem services, which production depends on (higher operational risk), for example through changing growing seasons or the scarcity of essential resources; and both chronic and extreme climatic events such as weather and sea level rise undermine the integrity of infrastructure, affecting the production of goods and services (operational risk; Fig. 5; Abramskiehn et al. 2015, Campiglio et al. 2018, IAIS 2018, Andersson et al. 2019, Bateson and Sccardi 2020, Bolton et al. 2020, ECB 2020, Monasterolo 2020, Retsa et al. 2020, Bernardini et al. 2021, Caldecott et al. 2021, ECB and ESRB 2021; S. Batten 2018, unpublished manuscript). Alternatively, ecosystem services may be lost through non-climatic means, such as pesticide-induced pollinator decline (NGFS-INSPIRE Study Group on Biodiversity and Financial Stability 2022).

Declining infrastructure integrity reduces investor confidence, further reducing the liquidity of business and production, further increasing operational risks of firms and financial institutions (FSB 2020; S. Batten 2018, unpublished manuscript). Higher operational risks resulting from climate change are expected to negatively affect the production cycle feedback, squeezing profits both by reducing the level of production and by reducing employment, striking aggregate demand and increasing the risk of an economic recession (systemic risk), which further suppresses demand. Besides, the resulting shrinking of production increases credit risk as firms lose their ability to pay their loans, negatively impacting demand (FSB 2020, Battiston et al. 2021, Bernardini et al. 2021, ECB and ESRB 2021, Liu et al. 2021, Semieniuk et al. 2021, CISL 2022). A higher number of non-performing loans further increases liquidity and systemic risks; systemic risk may also arise if extreme events reduce the value of collateral assets (FSB 2020, NGFS 2020b, Bernardini et al. 2021). Rising damage and repair costs faced by firms and households increase their precautionary savings, reducing sales (and so profits) and the proportion of profit reinvested in further production (Batten 2018, Andersson et al. 2019, Le Fur and Outreville 2021).

Regulation of unsustainable investments

A growing desire for environmental protection is expected to increase the prevalence and strength of nature and environmental policies and regulations, yet the social and political mechanisms driving a change in consumers’ behavior and policies are highly uncertain, indicated by the dashed arrows. Such policies and regulations may increase liability risk by holding firms and investors legally accountable for contravening the regulations, raising insurance risks from legal fees, and thus increasing revenue volatility (and therefore credit risk) caused by fines and penalties (Fig. 6; Abdul Razak et al. 2020, FSOC 2021). However, improved reporting reliability can also reduce liability and credit risks (Palea and Drogo 2020). The increased availability of standardized and verified metrics and the enhanced reliability of reporting gives investors a more accurate perception of climate and ecological risks, which in some cases is expected to reduce their allocation of capital to unsustainable industries (Abramskiehn et al. 2015, IPSF 2021).

Investors can also use better pricing and assessment of climate and environment-related risks as a tool to push for changes in unsustainable industries. It has been argued that investors should exercise their financial power over firms in their portfolios to change unsustainable practices, yet when investors should divest or engage is still unclear (Galaz et al. 2018). However, it is unlikely to threaten a fossil fuel company’s survival (Cleveland et al. 2015, Ruzzenenti et al. 2023). Divestment is most commonly taken by NGOs, faith groups, pension funds, and universities; for example, the Norwegian sovereign wealth fund has divested from coal (Cleveland et al. 2015, Ruzzenenti et al. 2023). On the other hand, investor pressure has forced unsustainable industries to improve disclosure of carbon asset risk (Cleveland et al. 2015, ESRB 2016).

Environmental regulations such as a carbon tax will raise the cost of fossil energy while increasing consumers’ preference for greener products and services. This growing consumer preference for greener products may also reduce the value of unsustainable assets and affect the demand for unsustainable products, increasing market risk (ESRB 2016, Semieniuk et al. 2021). These channels disrupt the feedback reinforcing the unsustainable investments, resulting in declining investor confidence, devaluation of unsustainable assets, and rising costs of unsustainable production methods (see Appendix 4; Abramskiehn et al. 2015). If unsustainable assets are devalued too quickly, there are greater chances of asset stranding, potentially triggering asset stranding cascades, exacerbating liability, market, and systemic risks. For example, the premature shutdown of power generation facilities often provokes legal disputes over profit losses, and fire sales, also known as balance sheet contagion, may occur if sudden changes in regulatory capital requirements force banks to rapidly sell assets, amplifying losses (Costanza et al. 2014, Abramskiehn et al. 2015, ESRB 2016, Battiston et al. 2017, 2021, Andersson et al. 2019, Hunt and Weber 2019, Löffler et al. 2019, Ansari and Holz 2020, Bateson and Sccardi 2020, Bolton et al. 2020, ECB 2020, FSB 2020, Monasterolo 2020, NGFS 2020a, Schumacher et al. 2020, Bernardini et al. 2021, Cahen-Fourot et al. 2021, FSOC 2021, Semieniuk et al. 2021, Tokunaga et al. 2021). Fossil fuel-intensive sectors are exposed to asset stranding via first, second, and third round shocks through high-indirectly exposed sectors like the real state, public administration, and land transportation, as shown by Cahen-Fourot et al. (2021).

The high degree of interconnectedness within the financial sector, due to interbank lending, for example, means financial institutions are heavily exposed to each other; the sector can therefore amplify shocks and losses due to physical and transition risks, increasing systemic risk (Battiston et al. 2017, 2021, Stolbova et al. 2018, Bateson and Sccardi 2020, Mandel et al. 2021, Semieniuk et al. 2021). Moreover, fossil fuel companies, being heavily debt-financed, could cause credit losses due to unsustainable asset price revaluation, further destabilizing the financial system (ESRB 2016).

An orderly transition with consistent policies could reduce systemic risks by enabling banks and the market to better anticipate price changes (Costanza et al. 2014, Cleveland et al. 2015, ESRB 2016, Battiston et al. 2017, Bateson and Sccardi 2020, Caldecott et al. 2021, Diluiso et al. 2021, ECB and ESRB 2021, FSOC 2021). Alternatively, a decline in production brought on by a rising cost of fossil energy could increase inflation (Andersson et al. 2019, Bernardini et al. 2021). High inflation can lead to economic uncertainty, influencing interest rates, reducing consumer purchasing power, and impacting corporate profits. These effects can increase volatility in financial markets, causing investors to see higher risks in their investments, thus increasing market risk (Campbell and Vuolteenaho 2004). This can also slow overall demand and lead to an unsustainable production cycle, further destabilizing the economy. Asset stranding risks can also result from biodiversity protections, such as the “no deforestation, no peat, no exploitation” policies that had stranded 28% of Indonesia’s palm oil land concessions as of April 2020 (Global Canopy and Vivid Economics 2020, Jouffray et al. 2021).

Scale-up of green production

A growing desire for environmental protection is thought to increase the prevalence and strength of nature and environmental policies and regulations, although the mechanism is uncertain. Increasing public investment in green alternatives will expand the supply of green energy and stimulate innovation in green sectors as well as raising the value of green assets; through these channels government policies (as well as higher economic growth) raise investors’ confidence in green technology leading to further investment by firms (Fig. 7; Abramskiehn et al. 2015, Andersson et al. 2019, Heine et al. 2019, Semieniuk et al. 2021, Sanctis et al. 2022). The declining cost of green energy reduces credit risk by lowering the cost of production (and thus enabling greater production) and by improving revenue stability because of the more predictable maintenance costs of renewable energy (Abramskiehn et al. 2015, Semieniuk et al. 2021). Investment in green energy also reduces firms’ liability risk and, hence, insurance risk (Heidari and Pearce 2016).

Systemic overview

Climate- and nature-related physical risks will likely increase liability risks for firms and investors. These types of risks are expected to increase with a growing public desire for environmental protection, leading to more and stricter environmental policies and regulations, making firms and investors accountable for environmental and climate change (regulation of unsustainable investments). Accountability is expected to increase the fines and penalties firms and investors face, disrupting their revenue stream and thus increasing credit risk. A higher number of non-performing loans further increases liquidity and systemic risks; systemic risk may also arise if extreme events reduce the value of collateral assets (damage liability; Fig. 8).

On the other hand, environmental regulations may improve reporting reliability and methods and help reduce liability risks. Environmental regulations such as a carbon tax will raise the cost of fossil energy and a growing consumer preference for greener products may also reduce the value of brown assets. These factors disrupt the feedback loop that supports the unsustainable production cycle, leading to a decline in the value of non-renewable assets and higher costs for fossil fuels. If brown assets are devalued too quickly, there are greater chances of asset stranding, potentially triggering asset stranding cascades, exacerbating market and systemic risks (regulation of unsustainable investments). Asset stranding risks can also result from biodiversity protections, such as the “no deforestation, no peat, no exploitation” policies. Simultaneously, the public desire for environmental protection will increase public investment in green alternatives, expanding the supply of green energy and stimulating innovation in green sectors as well as raising the value of green assets; through these channels, government policies (as well as higher economic growth) raise investors’ confidence in green technology leading to further investment by firms (regulation of unsustainable investments).

Climate-related physical risks will directly affect growth by undermining investors’ confidence, labor productivity, and ecosystem functioning and services. Climate change is also likely to affect infrastructure integrity, further reducing investor confidence and, in turn, reducing the liquidity of businesses and increasing operational risks of firms and financial institutions. Higher operational risks resulting from climate change are expected to negatively affect the production cycle feedback, squeezing profits by reducing production and employment and increasing the risk of an economic recession (systemic risk; damaged productivity).

CONCLUSIONS

There is a growing recognition that changes to the climate system and the biosphere pose intertwined, novel, and unfolding risks to the financial system. Our review offers an overview of this growing body of literature by providing insights on (1) the conceptualization of the transmission channels of climate- and nature-related risks and (2) commonly used methods and their limitations to assess such risks. We showed that, although there is a growing interest in environment-related risks, their connections to nature degradation have been underdeveloped, focusing mainly on mechanisms from climate to finance. Our review also confirms that the methods to assess the transmission channels of climate and other nature-related financial risks are still underdeveloped, as suggested by Kedward et al. (2023a), with little consensus, comparative efforts, and standardization of best practices for risk evaluation.

Using a complex system thinking approach to deal with the complexity and uncertainty of environment-related risks can provide a better overall understanding of the transmission channels of these types of risks. Our research offers a preliminary attempt to use complex system thinking in creating a domino effect typology of nine nested causal loop diagrams. This typology, on the one side, provides a more comprehensive understanding of how climate change and environmental degradation can lead to higher insurance risks due to more frequent and intense extreme weather events and loss of ecosystem functions and services (damage and repair), raising liability risks for firms and investors (damage liability), and decrease investors’ confidence and liquidity and increase operational risks for business and investor (damaged productivity). Conversely, it describes the expected impact of a growing desire for environmental protection on increasing the demand for greener products, reducing the value of unsustainable assets (regulation of unsustainable investments), and raising the value of green assets (scale-up of green production). Most importantly, our typology illustrates how physical and transmission risks could destabilize the economy by creating new forms of liability, operational, credit, and market risks (systemic overview).

This domino-effect typology can contribute to the future development of CLD quantitative assessments like cognitive maps and dynamical systems models, like the ones conducted in Gray et al. (2017) and Rocha et al. (2018). These quantitative analyses could address current methods’ epistemic and data availability issues by offering an alternative for studying the uncertainty linked to non-linearities in physical, transitional, and systemic financial risks under different scenarios (Bolton et al. 2020, Keen 2021). Our diagrams are meant to guide future research and policy debates rather than be directly applied without considering the underlying uncertainties and varying perspectives present in the literature. Developing these types of more accessible and comprehensive assessments for quantifying the interaction between climate and nature-related risks is critical for investors and other financial actors to understand their overall performance, management opportunities, and dependence on the biosphere.

Future attempts to develop complex thinking analysis in environment-related finance will require further research on how the interactions between climate change and nature degradation amplify financial risks (Pörtner et al. 2021, Ranger et al. 2023, Svartzman et al. 2023). This aspect was overlooked in our study because only more recent publications have addressed these interactions (NGFS 2022, Kedward et al. 2023a). A further limitation of our CLD mapping is that it may not fully capture all mechanisms of risk creation and transmission, particularly those involving shifts in consumer preferences influenced by environmental regulations or the transmission of physical risks into market risks, for example, through climate- or biodiversity-related supply chain disruptions that affect commodity prices. Although these pathways are conceptually important, they were not consistently or explicitly represented in the literature we reviewed and were, therefore, not included in our mapping. Moreover, the mapping shows a greater focus on climate-related financial risks than biodiversity-related ones, which mirrors the disparity in the reviewed literature. Consequently, new efforts should expand the typology further to include the connections between biodiversity loss and financial risks.

Another limitation of our study is that the financial literature examined failed to consider that non-financial and financial corporations are not only materially vulnerable to climate- and nature-related risks but also contribute to enabling environmental degradation. This is an issue that has been better explored by other sustainability scholars (Galaz et al. 2018, 2023, Jouffray et al. 2019, 2021, Crona et al. 2021, Tokunaga et al. 2021, Galaz and Collste 2022). Rigorously incorporating these types of studies in our CLD typology could help better explore the double-materiality effects of finance, which requires focusing not only on the financial performance but also on the environmental and social impacts of investments (Adams et al. 2021, Baumüller and Sopp 2021). This could allow investors and other financial actors to better understand their risk exposure and dependency on the Earth system. Additionally, it could help financial actors and institutions understand their role in mitigating the climate and biodiversity crises by enabling them to identify critical actions that could produce significant changes.

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