To understand how scenario frameworks and narratives have evolved in the context of transition risk assessment, we review (i) the scenario framework from the NGFS; (ii) transition risk assessments using bespoke scenarios and those adapted from NGFS scenarios; and (iii) scenarios from India-specific net-zero or deep decarbonisation studies. The latter are not transition risk assessment studies but rather India-specific literature that explores the key uncertainties in net-zero pathways.

The NGFS scenario framework

NGFS scenarios model a range of plausible outcomes based on assumptions about policy ambition, policy timing, policy coordination across regions, the pace and scale-up of technologies, and the availability of carbon dioxide removal methods (see Figure 1) (NGFS 2020). The figure maps key features of the scenario narratives and their macro-financial risk implications stemming from transition or physical risks. Green means “low risk”, teal means “medium risk”, and grey means “high risk”.

The assumptions underlying each driver form a scenario narrative. For example, an “Orderly” scenario (with low macro-financial risk) has two narratives: one in which the world reaches net zero in 2050 (Net Zero 2050), and another in which the global average temperature increases but below 2°C (Below 2°C). The overall risk of this scenario is low because the slightly higher near-term risks associated with immediate policy action and rapid technological change are partially offset by the much lower long-term risks associated with lower climate impacts and reduced reliance on carbon dioxide removal. The risks associated with each driver are also colourcoded in Table 1.

Table 1. Overview of Network for Greening the Financial Sector (NGFS) scenarios by key assumptions.

Source: Network for Greening the Financial System. 2024a. “NGFS Climate Scenarios Technical Documentation v 5.0.”

Note: Colour coding indicates whether the characteristic makes the scenario more or less severe from a macro-financial risk perspective^

– The impact of CDR on transition risk is twofold: on the one hand, low levels of CDR imply an increase in transition costs, as reductions in gross emissions should be obtained in a different way; on the other hand, high reliance on CDR is also a risk if the technology does not become more widely available in the coming years.

+ Risks will be higher in the countries and regions that have stronger policy. For example, in Net Zero 2050, various countries and regions reach net zero GHG by 2050, while many others have emission of several Gt of CO₂eq.

^ This assessment is based on expert judgment based on how changing this assumption affects key drivers of physical and transition risk. For example, higher temperatures are correlated with higher impacts on physical assets and the economy. On the transition side economic and financial impacts increase with a) strong, sudden and/or divergent policy, b) fast technological change even if shadow carbon price changes are modest, c) limited availability of carbon dioxide removal meaning the transition must be more abrupt in other parts of the economy, and d) stronger policy in those countries and/or regions.

The scenarios can also be understood as a spectrum of “mitigation versus adaptation”. Higher physical risk means higher adaptation needs but lower mitigation needs, and vice versa. Conversely, scenarios based on Nationally Determined Contributions (NDCs) and current policies, while associated with low to medium transition risk, fall in the high physical risk category due to higher temperature outcomes, leading to a Hot-house world with high adaptation requirements. Table 2 provides a concise description of each category.

Table 2. Key drivers of uncertainty in Network for Greening the Financial Sector (NGFS) scenarios

Scenario formulations used in transition risk exercises

While the NGFS scenarios provide a globally harmonised starting point for climate risk assessment, central banks and financial institutions frequently find it necessary to either use (i) alternative and proprietary scenarios for climate risk assessment; or (ii) build scenario narratives along the lines of the NGFS but use their own models to control for assumptions and data points. For these two broad classifications, we discuss the purpose of the exercise and the scenarios, along with their descriptions.

Alternative and proprietary bespoke scenarios in transition risk assessment

Several central banks and financial institutions have developed bespoke transition scenarios to complement or substitute globally harmonised frameworks such as the NGFS. These exercises are generally designed to address institution-specific objectives, incorporate country-specific economic and policy conditions, or explore particular dimensions of transition. The following examples illustrate a range of approaches adopted in the literature and practice:

De Nederlandsche Bank study

One of the earliest climate stress-testing and scenario analysis exercises undertaken before the NGFS framework was conducted by De Nederlandsche Bank (Vermeulen et al. 2021). The primary aim of the study was to develop a climate stress-testing framework based on existing financial stress-testing practices, with a focus on assessing the resilience of the Dutch financial system to disruptive changes rather than producing central-path projections. The framework was intended primarily for use by financial supervisory organisations and regulators.

Scenario formulation was based on two key drivers: (i) the stringency of climate policy; and (ii) the availability of low-carbon technologies. These were chosen because of their high uncertainty and their potential to trigger abrupt, non-linear changes in the economy.

Combining these two dimensions resulted in four stress scenarios:

• A strong and sudden tightening of climate policy in the absence of major technological change

• A positive technological shock characterised by rapid breakthroughs in low-carbon technologies without accompanying policy action

• A combined scenario featuring simultaneous policy tightening and technological breakthroughs

• A delayed transition scenario with neither climate policy nor technological developments, leading to prolonged policy uncertainty and subdued investment in low-carbon technologies

These scenarios were then translated into macroeconomic and sector-specific outcomes using multiple modelling approaches (Vermeulen et al. 2021).

Ortec Finance

Ortec Finance, in partnership with Cambridge Econometrics, offers proprietary climate scenarios. They provide five scenarios, with two variants specifically designed for high-stress testing. These scenarios are designed to translate a wide range of plausible climate futures into quantified financial impacts across economies, asset classes, sectors, and regions. The primary purpose of these scenarios is to support institutional investors such as pension funds in measuring, monitoring, and managing climate-related risks. One of the key advancements in Ortec’s framework is that its models capture the endogeneity of the financial system in risk materialisation, i.e., they also account for the financial system’s response to risks. The five scenarios are as follows:

• Net Zero: An ambitious but orderly transition with climate adaptation, characterised by highly ambitious low-carbon policies, a rapid technology transition, and low physical risks

• Net Zero Financial Crisis: A stress version of the Net Zero scenario, where sudden divestments to align with Paris Agreement goals disrupt financial markets, leading to repricing, stranded assets, and sentiment shock

• Delayed Net Zero: Financial markets price in transition and physical risks in 2030, leading to stranded assets and sentiment shock

• Limited Action: Evaluates the implications of failing to meet emissions targets, leading to high exposure to chronic and acute physical risks, with markets pricing in lower performance due to lost productivity and extreme weather

• High Warming: Assesses a future without further policy action, triggering multiple climate tipping points and very severe physical risks, with financial markets pricing in risks as their scale becomes widely accepted

Additional stress variants of these scenarios explore deeper tail risk outcomes, including systemic stress or complete market collapse under worst-case assumptions.

No Time To Lose (NTTL) scenarios used by the Universities Superannuation Scheme (USS)

USS is one of the largest private pension schemes in the United Kingdom (UK). As part of its Task Force on Climate-Related Financial Disclosures (TCFD) mandate, in 2022, it undertook a climate risk assessment using NGFS scenarios. However, it identified “significant limitations” in the available approaches and shared these concerns with other industry experts in the Real World Climate Scenarios (RWCS) initiative. These perceived limitations stemmed from scenarios “failing to capture key aspects of the real world, including acute physical risk, politics and policy, unemployment, finance, asset prices, volatility, tipping points, path dependency and complex feedback loops” (University of Exeter and Universities Superannuation Scheme 2025, p. 6), which in turn produced implausible and partial narratives and reduced the practical usefulness of the scenarios, especially in the near term.

To address these gaps, USS and the University of Exeter developed global “Decision Useful Climate Scenarios” for up to 2030. Both the short-term as well as the “realism and decision-useful” criteria of the framework, led to the development of two key groups of scenario drivers: (i) politics and policy; and (ii) economics and markets. The former captures uncertainties around geopolitics – policy coordination or lack of cooperation among countries – and policy stringency and timing. The latter captures business and consumer dynamism – shifts in technological innovation and deployment – and changes in consumer preferences, acceptance of green policies, and the impacts of climate change. These drivers resulted in four scenarios:

• Roaring 20s: Policy and markets align. Constructive competition between nations accelerates technological progress and deployment. Proactive climate policies and dynamic markets create powerful positive feedback loops.

• Green Phoenix: A cleaner market-driven transition occurs in the absence of strong policy leadership, but it is fragile and prone to volatility.

• Boom and Bust: Policy steps up after the fossil fuel surge bursts, triggered by energy price shocks that lead to boom cycles, central bank tightening, and financial crashes, followed by a partial recovery.

• Meltdown: Policy failures compound weak growth. This scenario is characterised by geopolitical fragmentation, energy trade wars, inflation spikes, and a global recession.

The Hong Kong Monetary Authority (HKMA) Climate Risk Stress Test (CRST 2.0)

The Hong Kong Monetary Authority (HKMA) conducted its second round of a sector-wide Climate Risk Stress Test (CRST 2.0) in March 2025 (Hong Kong Monetary Authority 2024). CRST 2.0 employed two distinct sets of scenarios: a short-term scenario (until 2027) featuring simultaneous climate-related shocks from extreme events and a global economic downturn leading to regional recession, and three long-term scenarios adopted directly from the NGFS framework.

This dual focus on short-term shocks and long-term trends reflects a comprehensive approach to climate risk, acknowledging both immediate vulnerabilities and gradual, structural shifts. The participating banks were provided with scenario variables and assumptions, including sectoral implications and macroeconomic indicators. HKMA also identified 11 business sectors for transition risk assessment. These sectors were either high-emitting industries or those that tend to be severely affected by transition policies, such as steel, non-ferrous metals, and paper.

Scenario framework derived from the NGFS framework and using additional modelling approaches

According to the NGFS survey, several respondents use additional modelling approaches to augment NGFS macroeconomic variables, integrate alternative macroeconomic models, or modify NGFS scenarios to constrain outputs based on their own macroeconomic models (NGFS 2021). The following examples illustrate transition risk exercises that use such approaches.

Bank of Canada

As part of its transition risk exercise, the Bank of Canada decided to construct its own scenarios while drawing on NGFS narratives. Their scenarios differed in terms of two key drivers: (i) the ambition and timing of climate policy; and (ii) the pace of technological change, including the availability of carbon dioxide removal (CDR) technologies (Chen et al. 2022; Hosseini et al. 2022). This led to four scenarios: Current policies, Below 2°C Immediate, Below 2°C Delayed, and Net Zero 2050. These scenario narratives broadly mirror those used by the NGFS.

The main aim of the Bank of Canada in developing its own scenarios was to provide economic and financial data at an appropriate geographic and sectoral granularity (Chen et al. 2022; Hosseini et al. 2022). In other words, by constructing scenario narratives along the lines of the NGFS while using its own modelling framework and data, the Bank of Canada was able to achieve standardisation through NGFS narratives while retaining greater control over assumptions, sectoral granularity and policy implementation in the models.

Goldman Sachs’ Climate Aware Capital Market Assumptions model

Goldman Sachs uses the Climate Aware Capital Market Assumptions model to conduct portfolio risk assessments. The model starts with NGFS scenarios but incorporates additional assumptions relating to transition and physical risks by applying a bottom-up abatement cost curve1 and a proprietary physical risk damage function2 (Goldman Sachs 2024). Specific variables from this analysis are used to determine the potential economic and financial impacts of the transition through Goldman Sachs’ Probabilistic Graphical Model (PGM).

The Bank of England’s Climate Biennial Exploratory Scenario (CBES)

The Bank of England’s Climate Biennial Exploratory Scenario (CBES) includes three scenarios that explore both transition and physical risks. The exercise considered two possible routes to net-zero UK greenhouse gas emissions by 2050: an Early Action (EA) scenario and a Late Action (LA) scenario. A third No Additional Action (NAA) scenario explores the physical risks that would materialise if governments around the world fail to enact policy responses to global warming.

The scenarios are built on NGFS scenarios but include “additional risk transmission channels and adding additional variables” (Bank of England 2021, “2.2: Scenarios”). These include labour market frictions to simulate the reallocation of labour towards low-carbon sectors, as well as larger financial market shocks (Bank of England 2021).

HSBC’s climate scenario analysis 

HSBC’s climate scenario analysis considers both physical and transition risks. In its 2023 scenario analysis exercise, HSBC developed four scenarios based on publicly available climate scenarios, including those produced by the NGFS, the Intergovernmental Panel on Climate Change (IPCC), and the International Energy Agency (IEA). HSBC adapted these external templates to reflect the specific climate risks and vulnerabilities faced by the bank and its customers across different business sectors and regions, resulting in a set of scenarios that vary in severity.

• The Current Commitments scenario assumes that climate action is limited to existing government commitments, resulting in a global temperature increase of around 2.4°C by 2100.

• The Delayed Transition Risk scenario assumes climate action is postponed until 2030, followed by a late and disorderly shift towards net zero that is nonetheless stringent and rapid enough to limit warming to below 2°C by 2100. HSBC uses this scenario to stress-test the impacts of severe yet plausible transition risks.

• The Downside Physical Risk scenario assumes that climate action remains limited to currently implemented policies, resulting in extreme warming exceeding 4°C by 2100. This scenario is used to assess the physical risks associated with intensified climate impacts.

• The Near Term scenario assumes a sharp increase in climate policies that triggers a disorderly transition towards net zero, alongside a marked rise in extreme climate events over a five-year period to 2027. This scenario focuses specifically on HSBC’s business exposure in Asia.

Key insights from the literature review

Across these exercises, several cross-cutting lessons emerge that are relevant for designing India-specific transition risk scenarios. First, although NGFS scenarios often serve as a common starting point, many institutions (including Goldman Sachs, the Bank of Canada, the Bank of England, and HSBC) adapt them to improve sectoral granularity, regional relevance, or policy representation. Second, several exercises (including those by De Nederlandsche Bank, HSBC, the Bank of England, the Hong Kong Monetary Authority, and USS) increasingly emphasise the importance of near-term shocks and disorderly transitions, where abrupt changes in policy, technology, financial markets, or energy prices may generate material financial risks. Third, uncertainty around policy timing, policy coordination, and technological change consistently emerges as a key determinant of transition pathways in several exercises (Bank of Canada, De Nederlandsche Bank, USS, and Ortec Finance). Finally, several frameworks (USS, Bank of Canada, and Hong Kong Monetary Authority) increasingly recognise the role of geopolitical fragmentation, trade disruptions, and international policy influences in shaping transition risk outcomes.

These lessons are particularly relevant for India, where transition pathways are closely linked to development priorities, industrial growth, trade exposure, and energy security concerns. Consequently, we contend that India-specific scenarios must place greater emphasis on macroeconomic shocks, policy uncertainty, external trade measures, and technology access constraints than is typical in globally harmonised scenario frameworks.

India-specific scenarios of decarbonisation

As noted in Section 2.1, transition risk scenarios should incorporate key sources of uncertainty within their analytical framework. This section focuses on Indiaspecific studies that examine key drivers shaping future emissions and energy-mix trajectories. A growing body of modelling studies has explored pathways for India to achieve deep decarbonisation and net-zero emissions. While some studies adopted an economy-wide perspective, others focused on specific sectors. Table A1 in Annexure 1 lists the studies reviewed. Only studies published from 2020 onwards were included, resulting in a total sample of 12 studies. Below, we highlight key insights from this literature.

Policy ambition and timing

A number of studies have investigated how the timing and stringency of policies shape decarbonisation pathways in India. Policy stringency has been examined through alternative carbon-budget formulations (Mathur and Shekhar 2020; Bhattacharya et al. 2024), differing global temperature outcomes (e.g., 1.5°C and 2 °C) (Dhar, Pathak, and Shukla 2020), or through the choice of net-zero year (Chaturvedi and Malyan 2022; A. Das et al. 2023a). Policy timing has been explored through early- and delayed-transition scenarios (Malik et al. 2020; Mathur and Shekhar 2020) and alternative peaking and net-zero years (Chaturvedi and Malyan 2022). Studies show that both policy stringency and timing significantly affect the required pace of the transition and its feasibility.

Macroeconomic drivers

Future energy demand is a key determinant of emissions trajectories and is driven by macroeconomic variables that are inherently uncertain.

• GDP and manufacturing growth: Garg et al. (2024) and Das et al. (2025) model scenarios based on high, medium, and low GDP growth rates. A “High Growth” (HG) scenario, particularly one where growth is driven by a high share of manufacturing activity (aligned with Viksit Bharat), could significantly increase energy demand and emissions, potentially negating reductions achieved through other interventions.

• Urbanisation and income inequality: Das et al. (2025) model scenarios exploring high urbanisation rates and variations in urban–rural income equity. While higher urbanisation increases electricity demand, this may be partially offset by lower rural demand.

• Economic shocks: Sudden and unexpected disruptions of economic activity can be described as economic shocks. Such shocks can alter growth trajectories and affect the pace and feasibility of decarbonisation by constraining investment capacity, delaying technology adoption, or changing sectoral demand patterns. Unforeseen disruptions, such as pandemics and geopolitical conflicts, create uncertainty through disruptions in energy markets, trade flows, critical mineral supply chains, and international climate cooperation. The IEA (2021) includes a Delayed Recovery Scenario, in which the prolonged economic impacts of the COVID-19 pandemic suppress energy demand and investment capacity. Similarly, Das et al. (2025) model an Economic Shocks scenario, where growth dips to zero periodically, drastically reducing long-term energy demand.

Technology availability, maturity, and cost

A central uncertainty across studies is whether critical breakthrough technologies will be commercially available and cost-competitive in time to meet net-zero targets.

• Carbon Capture and Storage (CCS): Several scenarios hinge on the availability of CCS to mitigate emissions from the industrial sector and thermal power plants. Chaturvedi and Malyan (2022) model scenarios in which CCS is either “available” or “unavailable”, noting that without CCS, the share of fossil fuels must decline drastically to 5–6 per cent by the net-zero year. Conversely, Garg et al. (2024) note that CCS is currently an “untested technology” in India with uncertain economic viability and geological storage potential. Similarly, Vishwanathan et al. (2023), who do not explicitly model CCUS in their scenarios, identify it as a major source of uncertainty due to social acceptability, geological constraints, and potential environmental risks.

• Green hydrogen: The commercial maturity of green hydrogen is a major source of uncertainty. Scenarios differ on whether hydrogen will successfully penetrate hard-to-abate sectors such as heavy transport and steel. If hydrogen technologies do not mature, the transport sector will become heavily dependent on electrification, and industrial decarbonisation will become significantly more difficult. Garg et al. (2024) also note substantial uncertainty around hydrogen uptake and cost assumptions.

• Nuclear power: The scalability of nuclear power is uncertain due to constraints relating to technology transfer, fuel availability, and capital costs. Das et al. (2023) performed a sensitivity analysis of nuclear capacity, limiting it to 30 GW in some scenarios due to historically slow progress, whereas other scenarios envision much higher uptake by 2070. Garg et al. (2024) also construct specific net-zero scenarios with a greater emphasis on nuclear power.

• Renewable energy and storage costs: While solar and wind costs have fallen, future cost trajectories remain uncertain. Das et al. (2023) model both “fast” and “slow” decline rates for capital costs.

Resource and physical constraints

Deploying renewable energy infrastructure introduces significant uncertainties relating to land, water, and minerals, especially in a highly populated, water-stressed country like India.

• Land availability and water security: Achieving net zero requires substantial land to support solar and wind farms. Gupta et al. (2022) estimate that growth and decarbonisation combined may require 45 million hectares beyond currently available land resources in an accelerated scenario. This creates risks of social conflict and implementation delays. Vishwanathan et al. (2021) highlight water scarcity as a critical constraint often overlooked in energy modelling. In water-constrained scenarios, thermal power plants face “stranded asset” risks due to water shortages, necessitating a shift to drycooling technologies or renewable energy sources. This, in turn, can alter the cost and mix of electricity generation. Several other studies also identify land and water availability as critical physical constraints that can limit progress towards net-zero targets (Chaturvedi and Malyan 2022; IEA 2021; Malik et al. 2020; Vats and Mathur 2022).

• Critical minerals: The transition from fossil fuels to renewable energy shifts dependence from oil and gas to critical minerals, such as lithium, cobalt, and copper, which are essential inputs for batteries and electrical grids. Garg et al. (2024) note that India lacks domestic sources for many of these raw materials, creating supply-chain vulnerabilities and increasing import dependence.

• Social constraints: Social constraints include a lack of acceptance by interest groups such as fossilfuel labour unions, consumer groups, and industry associations, as well as by the broader public of technologies such as nuclear energy and CCS. These constraints are important and are mentioned qualitatively in several modelling studies, but they are not specifically incorporated into scenario design (Chaturvedi and Malyan 2022; Gupta et al. 2022; Bhattacharya et al. 2024).

The discussion here does not focus on physical climate risks in the conventional sense, such as extreme weather events. Rather, it focuses on physical and resource constraints that can shape transition pathways. Land availability, water stress, and access to crucial minerals can all affect energy system choices, thereby influencing transition risks. As a result, these constraints interact with transition paths, making them relevant to transition risk assessment.

In this study, we began by discussing the need for Indiaspecific scenarios, noting that “off-the-shelf” and “general purpose” scenarios from NGFS serve as a useful starting point and support global standardisation, but they lack country-level granularity regarding policies, development aspirations, and other dimensions. NGFS itself encourages institutions to tailor scenarios to their own needs. This naturally raises the question: How should India develop its own scenario framework? To address this question, we first examined the logic underpinning the NGFS scenario framework and how it integrates transition and physical risks into broad scenario narratives. We then reviewed transition risk assessments that either use alternative bespoke NGFS scenarios, modify NGFS for specific purposes, or complement bespoke scenarios with NGFS scenarios. We also reviewed the scenario drivers employed in the Indian netzero literature and grouped them into broad categories. Finally, we synthesised these findings to identify key elements to consider when developing an India-specific scenario framework. These include divergent scenarios that incorporate shocks to the economic system as well as scenario drivers relating to technology adoption and innovation, policy ambition and timing, and the influence of geopolitics and international climate policy coordination. More broadly, this paper contends that the important distinction is not just between global and India-specific scenarios, but also whether it is designed for long-term energy transition planning or for financial-sector transition risk assessment. The latter requires greater attention to shocks, uncertainty, and sector-specific financial vulnerabilities. Although there is considerable value in India developing its own scenario framework, given the widespread use of NGFS scenarios and their ongoing development, India should also engage with NGFS to improve assumptions, sectoral coverage, and the representation of India-specific policy and development considerations.