ECB Blog post |  Catastrophes caused by climate change, such as rising sea levels or more frequent extreme weather events, will harm our economies. And this will put a strain on the finances of people, companies and governments alike. Because of the risks to individual banks, banking supervisors have already taken steps to enhance how banks identify, assess and manage these institution-specific risks.[1] Such supervisory measures are necessary steps focusing on the risks that climate change may pose to individual banks.
But climate change is also a risk to the broader financial system. The last two decades’ financial crises showed how the build-up of system-wide risk can erupt into costly turmoil. A timely macroprudential policy response is vital to strengthen the system’s resilience to climate-related risks.
Climate change as a systemic risk
Because of their unique nature, climate-related risks are likely to represent a systemic risk.[2] First, the impact of climate change is irreversible. Unlike the economic and financial losses caused by conventional business cycles, rising sea levels, changing precipitation and the loss of arable or liveable land cannot be reversed. Second, the breadth of physical and transition risks mean they might simultaneously and unpredictably affect a significant share of financial institutions across sectors and/or countries.
While financial exposures to climate change are concentrated, they are not isolated. It has been clearly established that climate risks are highly concentrated. For example, high-emission sectors are over 70% of corporate lending of euro area banks. They are also expected to account for two-thirds of banks’ losses in the transition to a lower-carbon economy. These losses are unlikely to be isolated and contained.
Disruptions resulting from climate change are likely to spread along global production value chains and through financial portfolios. For example harder-to-diversify risks will result in a growing insurance protection gap. That could create a negative feedback loop: banks might be reluctant to grant loans to households and companies in vulnerable areas or industries, which in turn might worsen the local ability to adapt to a changing climate.
Why a macroprudential approach is important
The discussion on the role and timing of a macroprudential response has just begun.[3] This is due primarily to uncertainty. Climate risks will eventually materialise, but their severity and form will depend on how climate change and the green transition unfold. While a wait-and-see approach might seem preferable until there is more clarity, this might delay action until it’s too late. Like other cases of systemic risk build-up, today’s underestimation of risks can result in capital misallocation and economic losses tied to the irreversibility of global warming. A macroprudential approach, aiming to reduce the accumulation of such risks, could counter this inaction bias through preventative (and not just corrective) action to contain financial risk.
Another challenge concerns the role of macroprudential policies in the broader policy mix. The progress made by microprudential supervisors and improvements in market participants’ risk management could lead to the misperception that no further action is needed. But this approach is not enough, because climate change will also likely affect risks that cut across the financial system, with financial risks that emanate from collective and not just individual actions. More frequent and severe weather events, for example, will make the negative economic impacts more volatile. Likewise, the transition to a low-carbon economy might be bumpy, with volatility around insufficiently prepared parts of the financial system. This may require additional resilience to account for the increase in system-wide risks that are currently not captured in the prudential framework for supervision of individual banks. Macroprudential policy would complement microprudential measures by both reducing risk build-up and increasing resilience against growing climate risks.
Analytical advances and the development of a shared monitoring framework have significantly improved our ability to understand and manage climate-related financial risks.[4] With the progress being made on the analytical side, developing a common EU macroprudential policy framework is both timely and possible.
Towards a common macroprudential strategy for climate risks
The 2022 ECB-ESRB Project Team report, The macroprudential challenge of climate change, looked at the possible macroprudential response and possible instruments to be used. The 2023 Project Team report will follow up by outlining a comprehensive common EU strategy for macroprudential policies to address climate risks, including a menu of specific policy options ready to be used when necessary.
The framework can use tools to address risks from a lender’s perspective (e.g. general or sectoral capital buffers, concentration thresholds), as well as from a borrowers’ perspective, or with tools targeting informational failures (e.g. enhanced disclosures). The complex and evolving nature of climate risks means an effective macroprudential framework also needs to be adjusted as the understanding of climate risks evolve: they may be scaled up if risks increase, and scaled down if and when risks recede.
The macroprudential response needs to be targeted, gradual and dynamic. The ideal response must prioritise aligning incentives with the prudential objectives. Imposing restrictive capital requirements indiscriminately may unintentionally hinder the financing of the green transition. Taking into account corporates’ forward looking transition plans could make macroprudential tools more efficient and limit possible side effects.
A common framework is key to ensure a consistent policy response. Close coordination across jurisdictions at the European level and beyond will be crucial to maximise efficiency.
Macroprudential policies can complement microprudential policies and ensure that the financial system is robust and resilient in the face of climate-related financial risk. By doing so, they will also ensure that the financial system is able to fulfil its role of financing the economy and the transition to climate neutrality. And, as highlighted in the ECB’s recent second economy-wide climate stress test exercise, the sooner and faster we complete the necessary green transition, the lower the overall costs and risks.
The views expressed in each blog entry are those of the authors and do not necessarily represent the views of the European Central Bank and the Eurosystem.
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Footnotes:

In 2020 the ECB published its Guide on climate and environmental risks setting out its supervisory expectation in that regard, and in 2022 the Basel Committee on Banking Supervision adopted Principles for the effective management and supervision of climate risks.
FSB (2022). Supervisory and Regulatory Approaches to Climate-related Risks. Final report. 13 October 2022.
The 2022 ECB-ESRB Project Team report The macroprudential challenge of climate change provided a first contribution to the development of concrete policy options. Beyond the EU, the Bank of England and the Prudential Regulation Authority discussed an “escalating” climate buffer, based on a risk assessment on the materiality of future system-wide transition and the physical risks associated with climate change.
ECB-ESRB (2022), The macroprudential challenge of climate change.

 
 
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Beginning in the 18th century, the Industrial Revolution ushered in a series of innovations that transformed society. We may be in the early stages of a new technological era—the age of generative artificial intelligence (AI)—that could unleash change on a similar scale.
History, of course, is filled with examples of technologies that left their mark, from the printing press and electricity to the internal combustion engine and the internet. Often, it took years—if not decades—to comprehend the impact of these advances. What makes generative AI unique is the speed with which it is spreading throughout society and the potential it has to upend economies—not to mention redefine what it means to be human. This is why the world needs to come together on a set of public policies to ensure AI is harnessed for the good of humanity.
The rapidly expanding body of research on AI suggests its effects could be dramatic. In a recent study, 453 college-educated professionals were given writing assignments. Half of them were given access to ChatGPT. The results? ChatGPT substantially raised productivity: the average time taken to complete the assignments decreased by 40 percent, and quality of output rose by 18 percent.
If such dynamics hold on a broad scale, the benefits could be vast. Indeed, firm-level studies show AI could raise annual labor productivity growth by 2–3 percentage points on average: some show nearly 7 percentage points. Although it is difficult to gauge aggregate effect from these types of studies, such findings raise hopes for reversing the decline in global productivity growth, which has been slowing for more than a decade. A boost to productivity could raise incomes, improving the lives of people around the world.
But it is far from certain the net impact of the technology will be positive. By its very nature, we can expect AI to shake up labor markets. In some situations, it could complement the work of humans, making them even more productive. In others, it could become a substitute for human work, rendering certain jobs obsolete. The question is how these two forces will balance out.
A new IMF working paper delved into this question. It found that effects could vary both across and within countries depending on the type of labor. Unlike previous technological disruptions that largely affected low-skill occupations, AI is expected to have a big impact on high-skill positions. That explains why advanced economies like the US and UK, with their high shares of professionals and managers, face higher exposure: at least 60 percent of their employment is in high-exposure occupations.
On the other hand, high-skill occupations can also expect to benefit most from the complementary benefits of AI—think of a radiologist using the technology to improve her ability to analyze medical images. For these reasons, the overall impact in advanced economies could be more polarized, with a large share of workers affected, but with only a fraction likely to reap the maximum productivity benefits.
Meanwhile, in emerging markets such as India, where agriculture plays a dominant role, less than 30 percent of employment is exposed to AI. Brazil and South Africa are closer to 40 percent. In these countries, the immediate risk from AI may be reduced, but there may also be fewer opportunities for AI-driven productivity boosts.
Over time, labor-saving AI could threaten developing economies that rely heavily on labor-intensive sectors, especially in services. Think of call centers in India: tasks that have been offshored to emerging markets could be re-shored to advanced economies and replaced by AI. This could put developing economies’ traditional competitive advantage in the global market at risk and potentially make income convergence between them and advanced economies more difficult.
Redefining human
Then there are, of course, the myriad ethical questions that AI raises.
What’s remarkable about the latest wave of generative AI technology is its ability to distill massive amounts of knowledge into a convincing set of messages. AI doesn’t just think and learn fast—it now speaks like us, too.
This has deeply disturbed scholars such as Yuval Harari. Through its mastery of language, Harari argues, AI could form close relationships with people, using “fake intimacy” to influence our opinions and worldviews. That has the potential to destabilize societies. It may even undermine our basic understanding of human civilization, given that our cultural norms, from religion to nationhood, are based on accepted social narratives.
It’s telling that even the pioneers of AI technology are wary of the existential risks it poses. Earlier this year, more than 350 AI industry leaders signed a statement calling for global priority to be placed on mitigating the risk of “extinction” from AI. In doing so, they put the risk on par with pandemics and nuclear wars.
Already, AI is being used to complement judgments traditionally made by humans. For example, the financial services industry has been quick to adapt this technology to a wide range of applications, including introducing it to help conduct risk assessments and credit underwriting and recommend investments. But as another recent IMF paper shows, there are risks here. As we know, herd mentality in the financial sector can drive stability risks, and a financial system that relies on only a few AI models could put herd mentality on steroids. In addition, a lack of transparency behind this incredibly complex technology will make it difficult to analyze decisions when things go wrong.
Data privacy is another concern, as firms could unknowingly put confidential data into the public domain. And knowing the serious concerns about embedded bias with AI, relying on bots to determine who gets a loan could exacerbate inequality. Suffice it to say, without proper oversight, AI tools could actually increase risks to the financial system and undermine financial stability.
Public policy responses
Because AI operates across borders, we urgently need a coordinated global framework for developing it in a way that maximizes the enormous opportunities of this technology while minimizing the obvious harms to society. That will require sound, smart policies—balancing innovation and regulation—that help ensure AI is used for broad benefit.
Legislation proposed by the EU, which classifies AI by risk levels, is an encouraging step forward. But globally, we are not on the same page. The EU’s approach to AI differs from that of the US, whose approach differs from that of the UK and China. If countries, or blocs of countries, pursue their own regulatory approach or technology standards for AI, it could slow the spread of the technology’s benefits while stoking dangerous rivalries among countries. The last thing we want is for AI to deepen fragmentation in an already divided world.
Fortunately, we do see progress. Through the G7’s Hiroshima AI process, the U.S. executive order on AI, and the UK AI Safety Summit, countries have demonstrated a commitment to coordinated global action on AI, including developing and—where needed—adopting international standards.
Ultimately, we need to develop a set of global principles for the responsible use of AI that can help harmonize legislation and regulation at the local level.
In this sense, there is a parallel to cooperation on the shared global issue of climate change. The Paris Agreement, despite its limitations, established a shared framework for tackling climate change, something we could envision for AI too. Similarly, the Intergovernmental Panel on Climate Change—an expert group tracking and sharing knowledge about how to deal with climate change—could serve as a blueprint for such a group on AI, as others have suggested. I am also encouraged by the UN’s call for a high-level advisory body on AI as part of its Global Digital Compact, as this would be another step in the right direction.
Given the threat of widespread job losses, it is also critical for governments to develop nimble social safety nets to help those whose jobs are displaced and to reinvigorate labor market policies to help workers remain in the labor market. Taxation policies should also be carefully assessed to ensure tax systems don’t favor indiscriminate substitution of labor.
Making the right adjustments to the education system will be crucial. We need to prepare the next generation of workers to operate these new technologies and provide current employees with ongoing training opportunities. Demand for STEM [science, technology, engineering, and math] specialists will likely grow. However, the value of a liberal arts education—which teaches students to think about big questions facing humanity and do so by drawing on many disciplines—may also increase.
Beyond those adjustments, we need to place the education system at the frontier of AI development. Until 2014, most machine learning models came from academia, but industry has since taken over: in 2022, industry produced 32 significant machine learning models, compared with just three from academia. As building state-of-the-art AI systems increasingly requires large amounts of data, computer power, and money, it would be a mistake not to publicly fund AI research, which can highlight the costs of AI to societies.
As policymakers wrestle with these challenges, international financial institutions (IFIs), including the IMF, can help in three important areas.
First, to develop the right policies, we must be prepared to address the broader effects of AI on our economies and societies. IFIs can help us better understand those effects by gathering knowledge at a global scale. The IMF is particularly well positioned to help through our surveillance activities. We are already doing our part by pulling together experts from across our organization to explore the challenges and opportunities that AI presents to the IMF and our members.
Second, IFIs can use their convening power to provide a forum to share successful policy responses. Sharing information about best practices can help to build international consensus, an important step toward harmonizing regulations.
Third, IFIs can bolster global cooperation on AI through our policy advice. To ensure all countries reap the benefits of AI, IFIs can promote the free flow of crucial resources—such as processors and data—and support the development of necessary human and digital infrastructure. It will be important for policymakers to carefully calibrate the use of public instruments; they should support technologies at an early stage of development without inducing fragmentation and restrictions across countries. Public investment in AI and related resources will continue to be necessary, but we must avoid lapsing into protectionism.
An AI future
Because of AI’s unique ability to mimic human thinking, we will need to develop a unique set of rules and policies to make sure it benefits society. And those rules will need to be global. The advent of AI shows that multilateral cooperation is more important than ever.
It’s a challenge that will require us to break out of our own echo chambers and consider the broad interest of humanity. It may also be one of the most difficult challenges for public policy we have ever seen.
If we are indeed on the brink of a transformative technological era akin to the Industrial Revolution, then we need to learn from the lessons of the past. Scientific and technological progress may be inevitable, but it need not be unintentional. Progress for the sake of progress isn’t enough: working together, we should ensure responsible progress toward a better life for more people.

Author: Gita Gopinath, First Deputy Managing Director, IMF.

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IMF Blog post |  Policymakers need fuller view of consequences of illicit flows, including tallies of the fiscal, monetary, financial, and structural costs.
The fight against financial crime isn’t lost, but the world needs to do more to limit the economic impact of crime.
Money laundering is a necessary component of the organized crime that too frequently spans borders, skirts taxes, funds terrorism and corrupts officials—and it comes with hefty macroeconomic costs. Bad actors are also embracing new technologies on top of their traditional techniques, all of which makes economic growth less inclusive and sustainable, fueling inequality and informality.
The international community has made significant progress toward strengthening safeguards against money laundering and terrorist financing, with help from the IMF and other organizations. We decided a decade ago to take a more bespoke approach to identifying key risks, working with member countries and international partners, particularly, the Financial Action Task Force, the international standard-setter in this area.
But the overall efforts are still broadly insufficient. For example, as the FATF noted last year, there is still a major gap between progress countries have made on technical compliance, such as enacting new laws, and on the effectiveness of these efforts. For example, very little laundered ill-gotten proceeds are ever confiscated.
Accordingly, the IMF recently reviewed our strategy on anti-money laundering and combatting the financing of terrorism (AML/CFT). The goal is to better help our 190 member economies address these critical financial integrity issues.
High costs
We must first recognize that financial crime affects lives and livelihoods, especially those of the most vulnerable, and that the costs it imposes are very high—and increasing. Direct costs vary and can include lower revenues, higher expenditures, sanctions, lost banking services, and even increased financial instability.
For example, and as recent IMF work has shown in the Nordic Baltic Region, AML/CFT deficiencies are associated not only with large drops in stock prices for the most directly affected banks, but also declines in share prices of other lenders who simply happen to be in the same country, as well as banks in the region that have similar cross-border exposures.

The indirect costs are even greater because they are imposed across an economy, whether by fueling boom-and-bust cycles or making home prices unaffordable. Potential financial stability impacts include bank runs and lost foreign investment. Large-scale money laundering can even spur volatility in international capital flows, undermine good governance, spark political instability, and just generally erode trust—in governments and institutions.
Liquidity, as measured by deposit flows, tends to deteriorate around financial integrity events for the affected bank while other domestic banks’ liquidity could benefit from positive substitution effects in the short-term.

Another important consideration is that illicit financial flows are a global problem. Insufficient AML/CFT frameworks in some countries, including international financial centers, can attract criminal proceeds from abroad. In countries exporting illicit flows, we see there is less opportunity, higher inequality, higher poverty, more illegal immigration, misused resources, and environmental degradation. For example, one study shows that illicit financial flows in Africa (an estimated $1.3 trillion since 1980 has left sub-Saharan Africa) drain domestic revenues that could be used for the continent’s development, have a strong and negative effect on investment rates, notably private investment, and are curtailing Africa’s savings rate. These effects can also have a cascading effect on countries transiting or receiving the illicit proceeds.
This underscores why we must better understand how money laundering and terrorist financing can hurt individuals, countries, and even the global economy. And because of the wide-ranging consequences, we are deepening AML/CFT considerations across all the work that we do, while urging our members to safeguard their financial sectors and broader economy to help ensure global financial stability.
Deeper understanding
Analysis of money laundering and terrorist financing historically focused on threats and vulnerabilities. Both are central to gauging and containing risks, but more is needed. Knowing the full extent of consequences for economies requires being able to understand the fiscal, monetary, financial sector and structural costs of illicit flows. This is needed to document just how financial integrity affects both a given country’s financial stability and broader economy, plus how global financial stability might be affected.
Accordingly, the IMF Executive Board has endorsed a plan for the institution to expand its data analytics capacity to focus on these issues and deepen the coordinated approach across all of our key work areas, including IMF surveillance, lending engagements, capacity development and Financial Sector Assessment Programs. This new approach will also give the IMF new evidence to answer key questions including:

Which sectors are most vulnerable for money laundering, from banks and real estate to virtual assets and precious metals?
What countries export illicit flows, allow them to transit, and what countries integrate them?
How do these illicit flows affect the economy, including its prospects for inclusive and sustainable growth and development?

Even after decades of progress in financial integrity, the Fund and the international community must persist and press on in this fight. Crime is a moving target, but we can—and must—broaden and deepen our containment efforts. This includes improving cooperation among stakeholders, including governments, international bodies, and civil society. For our part, the IMF will use its strength as a macroeconomic institution with global reach to help its members assess the impact of financial crimes and illicit flows and design and implement policies to address them. The cost of failure is simply too high.
—See our new AML/CFT page for the recent Executive Board paper: 2023 Review of the Fund’s Anti-Money Laundering and Combating the Financing of Terrorism Strategy and the background papers.
 
For more information, please contact the authors:
> Carolina Claver, Senior Financial Sector Expert – Financial Integrity Group, IMF
> Chady El Khoury, Deputy-Unit Chief of the Financial Integrity Group, IMF
> Rhoda Weeks-Brown, General Counsel and Director –  Legal Department, IMF
 
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High energy prices triggered by Russia’s war of aggression against Ukraine prompted governments to reduce excise taxes during 2022, leading to lower tax levels in many countries, according to new OECD analysis.
Revenue Statistics 2023 shows that the average tax-to-GDP ratio in the OECD fell by 0.15 percentage points (p.p.) in 2022, to 34.0%. This was only the third such decline since the Global Financial Crisis in 2008-09: the level fell by 0.6 p.p. in 2017 and by 0.1 p.p. in 2019.
Revenues from excise taxes fell as a share of GDP in 2022 in 34 of the 36 countries for which preliminary data is available, declining in absolute terms in 21 of these. In some countries, notably in Europe, these declines were related to reductions in energy taxes as well as lower demand for energy products. Revenues from value-added tax (VAT) also declined as a share of GDP in 19 countries, in part due to policies to cushion consumers against high prices for energy and food.
The decline in revenues from excise taxes in 2022 was partly offset by increases in revenues from corporate income taxes (CIT), which rose as a share of GDP in more than three-quarters of OECD countries amid higher corporate profits, especially in the energy and agricultural sectors. CIT revenues in Norway rose by 8.8% of GDP due to exceptional profits in the energy sector.
Overall tax revenues declined as a share of GDP in 21 of the 36 countries in 2022, increased in 14 countries and remained at the same level in one. The largest decline was observed in Denmark (-5.5 p.p., to 41.9%) while the largest increases were seen in Korea (2.2 p.p., to 32.0%) and Norway (1.8 p.p., to 44.3%).
The decline in the OECD’s average tax-to-GDP ratio followed two years of increases during the COVID-19 pandemic, of 0.15 p.p. in 2020 and 0.6 p.p. in 2021. Tax-to-GDP ratios in 2022 ranged from 16.9% in Mexico to 46.1% in France.
A special feature in the new report examines the extent to which tax revenues in OECD countries have kept pace with economic growth in recent decades by analysing tax buoyancy for different tax types for the period from 1980 to 2021. The study finds that tax revenues typically increased at the same rate as GDP over this period; revenues from CIT were the most buoyant over the long run – increasing faster than economic growth – while revenues from excise taxes were the least buoyant, increasing at a slower rate than GDP.
To access the Revenue Statistics report, data, overview and country notes, go to https://oe.cd/revenue-statistics.
 
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