This is how we work with risk in the fund | Risk Summit 2026 | Norges Bank Investment Management

Technology shares on Wall Street have fallen sharply in response to the emergence of a low-cost chatbot.

Salesforce, Snowflake, few other software names falling sharply to start the week again as AI disruption fears pummel the sector.

Agentic AI is basically a robot in a digital form. AI is sucking up incredible amount of capital.

About 80% of the gains in the stock market this year have been powered by AI plays.

In a few moments, I will sign a historic executive order instituting reciprocal tariffs. Reciprocal. That means they do it to us and we do it to them. Very simple.

We begin with developments from Kiev, the ongoing war.

Like the Ukrainians, I very much hope that we will have peace in Ukraine. But I am worried that we might push this to a cheap ceasefire which will lead to a very expensive peace.

You don't have the cards right now.

New strikes across Tehran tonight as the US-Israeli war on Iran is expanding.

They all rely on the same narrow passageway, the Strait of Hormuz.

Iran's Revolutionary Guard is sending radio transmissions to ships, warning them that quote, 'No ship is allowed to pass the Strait of Hormuz.' Oil prices have been on a roller coaster and remain quite a bit higher this morning.

We need Greenland working with everybody involved to try and get it. One way or the other, we're going to get it.

Says he's serious about something, he means it.

Is the United States now at war with Venezuela?

There's not a war.

The essence of investment management is the management of risks, not the management of returns. Benjamin Graham, the father of value investing, wrote that. And tonight is about exactly that: understanding risk, managing it, and making better decisions because of it. My name is Espen Fristrup, and I will be your host for tonight. Welcome to NBIM's first ever risk summit.

We live in a world testing risk managers in ways we haven't seen in decades. Wars in Europe and the Middle East, a changing global order, shifting trade relationships, and AI transforming how we work while introducing risks we may not yet fully understand. In that world, the work done by risk professionals, by the people presenting here tonight, has never been more important. Tonight you will hear from colleagues at NBIM who integrate risk thinking into investment, along with experienced voices from the broader investment community. We have a full program ahead of us. So let's get started. And for your information, photos will be taken during the event and made available to all participants tomorrow. Our CEO needs no introduction. But I will say this: 20,000 billion kroner, the shared savings of the Norwegian people. He is responsible for that risk. That responsibility in times like this, I'm not quite sure how he sleeps at night. Nicolai Tangen.

Next is a question central to risk management today: how do you measure something as complex and unpredictable as geopolitical risk, conflicts, sanctions, and disrupted supply chains? A world that may be generating tail risks beyond what our models were designed to handle. Tensin and Marta Palino have built the frameworks we use to measure and stress test geopolitical risk across the fund. Please welcome Marta.

Hi everyone, my name is Marta and I was born in 1997. When I was preparing this presentation, I thought let me go back in time and see how the world looked like when I was born, and I found some very interesting headlines. Let me show you. Let's start with the European Union. In 1997, 11 countries from the European Union met in Amsterdam to discuss and agree on one single currency, the euro. And that was the first move towards a united European Union. 122 countries met here in Oslo to agree and discuss on an anti-personnel landmine ban. And there was a first push towards global disarmament. And this one I found very interesting. NATO and Russia met in Paris to agree on a founding act. They put in writing that they would live peacefully together. And the optimism was so high that some even thought that Russia could eventually join NATO. Three different pictures, three different countries and three different situations. But one common thing underneath: that in front of a challenge, countries come together, sit together, discuss and find the solution together. There was a world of cooperation. If we move back in time and we move forwards to 2016, the United Kingdom decided to leave the European Union. And less than a month ago, Hungary decided to put a veto and block 26 countries from the European Union to make a decision about aid to Ukraine. And the European Union keeps fragmenting. What about disarmament? Well, last year NATO decided to increase the defense spending up to 5% of GDP. And NATO and Russia—Russia didn't join NATO after all. But last year we actually experienced Russian drones invading the European airspace. Three different pictures, three different countries and three different situations. But one common thing underneath: the countries do not come together anymore, do not sit and find a solution together. We live now in a world of competition. The point I'm trying to make here is that the order we knew is not coming back. At least not in the form and in the shape it was before. And even if this might make you feel pessimistic, I don't think it is the right read. We live in a historic period, a period of transition. And what is different compared to before is that it's moving faster. It's moving much faster. And what is happening today will have impact on the long-term investment outcomes. So let me bring all of this together. The old playbook no longer works. Geopolitical risk was something considered as a footnote for decades, but it cannot be considered a footnote anymore. It is essential for investment analysis because the assumption that countries come together, sit together, find the solution and there is some sort of stability is gone. The assumptions have changed. The logical power has changed, and this that is happening today, it's already impacting the financial returns. Geopolitical risk is not something you read about in the news and you move on. It is affecting asset pricing and it sits in our investment decision. So how do we manage this risk? So we think about geopolitical risk analysis along four pillars. Firstly, inform: making sure that everyone in the organization is on the same page when it comes to these risks. That means across different teams and all the way up to the executive board. Secondly, simulate: get together over tabletop exercises where we can play out how events might unfold. This helps us with awareness and preparedness about operational risks as well as the financial risks. And then integrate: making sure that when we have geopolitical risk analysis, it flows through our financial risk analysis and our stress tests. And then finally, consult. We're a small team. We don't have all the answers. So we rely on internal as well as external experts because in this field no one has all the answers. Our geopolitical risk scenarios focus on three main things that are important for us. It is war and conflict between great nations. It is financial sanctions, and finally investment restrictions that makes it more difficult to trade and invest across nations. So how do we make these scenarios? If you start on the left side, it starts with an annual horizon scanning where we identify the top risks to the fund, and then we focus on making some scenarios where we look at the tail risks of these scenarios and the economic and financial impact of these tail risks. Then we have some early warning signals that we call key indicators that tells us whether we're likely to get towards one scenario or the other scenario. And finally, probabilities. We assign probabilities on these based on expert judgment, and then we update these probabilities on a quarterly basis. In between the quarters, we use AI to monitor these scenarios. And then we have our annual stress test which we publish on our website. This is a good example of a collaborative team effort between the risk department, the strategy research team, and our portfolio managers. Here you see four different stress scenarios, and the value of the fund on the left side is 20,000 billion Norwegian kroner. It was much lower when I started here, and it does translate to around $2 trillion US dollars. And the scenario in the middle is a scenario called 'fragmented world.' This is a world where there's a total collapse of trust between countries, and countries start forming their own economic blocks, and there's limited trade and investment across these blocks. In such a scenario, the fund can lose 37%. This is not a prediction. It is the tail risk. But it is something that tells us about something about what is at stake. Scenarios is the main tool we have to make sense of the world we're in. Scenarios also help us to communicate the risk across the organization and to external stakeholders. These scenarios also help us to spark the right discussions that we need. We cannot predict the path the world will take. But our job is not to predict. It is to be prepared for the journey, no matter the final destination.

Geopolitical risk at the macro level. Now, let's bring it closer to the portfolio. Matthew Brunette is our global head of financing and responsible for our securities lending strategy. Trude is our head of credit and counterparty risk. Securities lending generates stable returns by lending out our inventory of equity and fixed income assets in exchange for a fee. In fact, it has contributed to roughly a quarter of our long-term relative performance. It is commonly viewed as a low-risk strategy. But when something quietly earns billions year after year, you have to ask, are there some big risks here that we should be concerned about? Trude.

Yes, Espen. Counterparty defaults do happen. Securities lending isn't risk-free. Matt and I know this firsthand. We were both here in this building when Lehman defaulted, and that experience still shapes how we think about downside risk today. Yes. So securities lending has been very profitable for NBIM. So profitable in fact that the recent independent review of the active management actually singled it out as a remarkable success. So why don't we just lend as much as we can? There's a catch, and that's counterparty risk. If a borrower defaults, we could face significant losses given the volumes we lend. So the last 12 months we've lent securities worth almost 2,000 billion Norwegian kroner. So a counterparty default is a low probability event. But when it happens, the consequence could be large. So managing that tail risk is a joint effort between our two teams.

Thanks, Trude. Yeah, so we've been pretty successful with the strategy: 6 billion kroner in 2025 in excess return for the fund. But two things: it's complicated and the numbers are quite large. So, first of all, we're lending equity and fixed income securities across 35 markets globally. And at any given time, there can be more than 7,000 unique securities out on loan. Look at the chart here. The red line shows you the market value of securities out on loan at any given time as a percentage of the NAV of the fund. So, this tells you two things here. One, 10% to the NAV of the fund, like Trude said, is two trillion kroner, right? So massive in exposure. The second thing is it's not static over time, so we're actively making decisions to scale up or scale down risk depending on the opportunity set in the market. So when we're lending securities, equities and fixed income, we're taking other securities as collateral and sometimes cash as collateral. The primary risk, or the principal risk, the legal risk in this transaction is with prime brokers. These tend to be very large international investment banks, but we need to remember that behind them, they're facilitating transactions for their hedge fund clients. So, this becomes super important when we start looking at the asset risk in our securities lending portfolio in a Lehman-type situation. So in that situation, we're selling collateral in the market to try to buy back our loan portfolio, but we need to remember that the collateral that we're selling is the hedge fund longs, and the loans that we're buying back are their shorts. So in other words, we're positioned the same way as very active levered investors in the market. So we refer to this as tail risk because it is a low-risk strategy by definition. But in my experience in financial markets, tail risks that are meant to happen every hundred years kind of happen every eight or 10 years. So what are the components of securities lending risk? The first is counterparty default. So what is the probability that another Lehman-type event will happen with the counterparty that you're transacting with? Well, it's really small but it does happen, right? Second is a loss on default. This is where we start looking at the asset risk. So what is your expectation for this portfolio of loans and collateral, and how is that going to perform in this type of market environment? So think in terms of volatility and liquidity. So again, not normal markets but a situation where a major bank has defaulted. Finally, insurance. Most institutional lenders have some type of insurance around this type of risk. In the industry we call it indemnification. But the question we should be asking is, again in this type of crisis market environment, what is the insurer's ability to make good on their commitments? All of this wraps up into the trading decision, which is the revenue piece on the bottom. So the traders on my team, I really want them asking themselves two questions. One, for negotiating an individual transaction, am I getting paid for the risk that I'm taking here? So, is the accumulated revenue over time going to compensate me versus future losses? And two, probably more importantly, how does this individual transaction that I'm executing right now contribute to the total portfolio of risk with that counterparty?

Yes. So, within counterparty risk, we assess two things as Marta alluded to: is the credit risk, what is the likelihood of a counterparty defaulting, and then the asset risk, how much could we lose if it defaults. So bank defaults are rare, but they do happen. We had a big scare in March 2023 with the collapse of Credit Suisse and then the subsequent forced merger with UBS. So credit risk had been on our watch list already since March 2021 following the bank's over 50 billion kroner loss from the Archegos default. So as we watched Credit Suisse credit quality worsen, we shifted our focus to asset risk. How can we mitigate losses in case of default? We worked with financing to run down on securities lending exposures. At the same time, financing asked for more collateral and got it. The result: we went from 60 billion kroner in securities lending exposure to just 600 million, and we were very well collateralized. So by the time Credit Suisse actually collapsed, we were quite confident that we wouldn't face any losses, even if the bank hadn't been bailed out. But we could also experience a sudden counterparty default. And in that case, we don't really have time to run down securities lending exposure or ask for more collateral while the bank is still operating. So this means that we truly need to understand the asset risk that we are facing for the different investment strategies. So we develop and use a model to estimate losses in bad but realistic scenarios. And this allows us to set effective requirements on exposure limits, collateral concentration risk, liquidity risk, etc. So close cooperation with Matt and his team ensures we have all the necessary information and that we truly understand the different securities lending strategies that we are facing. Ultimately, the requirements we set shape Matt's investment mandate and define the boundaries for which financing can operate. So counterparties' credit quality, as I said, they can worsen quickly or suddenly. It's very hard to know up front how things will develop. So that's why the monitoring of our credit quality is so key to what we do. To strengthen that monitoring, we have recently developed an AI tool that looks through thousands of news articles all over the world in different languages. And we set the bar high so we actually get the relevant articles with negative news. So every morning when we come in, a news summary is waiting for us. This is a great way to keep up to date on events that we should really pay attention to, and we use this insight in a conversation with financing about counterparties. Here you see a younger Matt right after the Lehman default. He's looking quite relieved. He didn't lose any money. At the time, we had no plans in place and we just had to manage the default as we went along. But we'd rather be ready. So now we have detailed response plans in place. We have clear responsibility across teams, and we all tie that together in a common run book. This ensures that we know who does what and that we do the right thing at the right time in a stressful situation. To improve and be ready, we practice together. These drills also include colleagues from legal, trading, and operations. When we find weaknesses, we improve our procedures. We have, for example, found weaknesses in our collateral processes, which we then quickly rectified. We've also updated some of our contracts so that they are more in our favor. And the legal team has taken this a step further. They're now using AI to extract key terms across our contracts, mapping trends and analyzing what these mean for our access to our collateral and our creditor rights. So our drills are cross-team because when the moment comes, it's a common effort—we all need to be ready. So to conclude, there is tail risk in securities lending, and that risk needs to be actively managed. We do this on three fronts. We monitor the credit quality of our counterparties. We manage our asset exposure to contain potential losses, and we test our response so that when the moment comes, we know what to do.

Earlier you heard about our scenario analysis in the presentation on geopolitical risk. Now we will dig deeper into it. Our stress test report has attracted attention from both Norwegian and international media. But publishing the analysis is only the start. The big question is what comes next. That is why this panel will discuss how to channel scenario analysis into real impact. Whether that means portfolio decisions, educating asset owners, or simply building a deeper understanding of the risks we face. Yun Nin, head of market risk measurement here at NBIM, will moderate, joined by Lars Kjærgaard Sørensen from Storebrand and Danny Schots from PGGM Investments. Danny, Lars, and Yun, the floor is yours.

Okay, thank you, Espen. So in our most recent stress test report, we had four scenarios that we modeled. We had AI correction, fragmented world, regional debt crisis, and extreme weather events. Over the past year, we have actually seen elements of the first three in the markets. But every time the crisis didn't fully materialize and the markets recovered quite fast. So one could say that we got it wrong very accurately. As Marta showed you, our models estimate the impact of the scenario to the nearest percentage point, but the markets didn't read the report. Now, while this is of course good for most investors, it also raises an uncomfortable question. If the markets keep defying our carefully defined scenario narratives, what should we actually do with the scenarios? Acting defensively on any of these would have cost returns last year. Not acting leaves us exposed if the next one does escalate or plays out differently than our careful narrative anticipates. So that is what this panel is about. Not the scenarios themselves, but how to use them. So how to balance scenario risk against expected return, and how to turn analysis into real insight and action for the organization. Now with me, I'm lucky to have here two friends of the fund. So Lars Kjærgaard Sørensen, head of index and quant strategies at Storebrand, previous employee of the fund. So welcome back.

Thank you.

And then Danny Schots, the chief financial and risk officer from PGGM Investment Management, which is a large Dutch asset manager with assets of 260 billion euros. So Danny, Lars, both of you run scenario exercises. So in a few words, what is the main thing that this exercise delivers? Is it quantifying risk, challenging assumptions, preparing the organization, or perhaps managing asset owner expectations for what might come?

I think that for us the order would be organizational preparedness first, because you can sort of prepare the organization for what is typically an adverse scenario, and then when such a scenario hits, you can sort of have the feeling that you've seen the film before, you know what comes next, and you know how to address the situation. And then the second, we use, and probably many people here do, we use factor models for risk and return, and those are typically based on historical correlations, but in such stressed scenarios those correlations might break down, and that's one of the values I think that scenarios do have. And I know some of the limitations of these models because I used to work for two of the leading providers of such models, Barra and RiskMetrics. So I know they have limitations and I know that scenario analysis can address some of those gaps. And finally, the quantities themselves, the losses themselves, I don't think when you said for example that the equity portfolio would lose 53% in an AI correction scenario, you know, you have to take that with a pinch of salt. It's a very uncertain number but maybe the ordering is kind of correct. So I think those are good use cases. And if I just may add, when a scenario hit us in practice, when Russia invaded Ukraine on February 24, there was a lot of confusion what to do. Do we exclude the entire country? Do we exclude state-owned securities? Or do we exclude all Russian stocks? And NBIM acted first and then other asset managers followed, and we divested, but we knew exactly what to do because we had sort of prepared and we had a decision authority matrix in place. So factor regimes are the most important for us, but it's probably a little bit different for you, Danny.

Thank you. Well, we don't have a uniform way of using scenarios within PGGM. Of course, scenarios are used and they're used all across the investment chain. The main point where we use a scenario is for the strategic long-term ALM and asset allocation. So we use stochastic scenario sets to mainly determine a base scenario, and then use deterministic scenarios as the ones you've just described to test the robustness of that base scenario instead of using it as a prediction for the future. So main usage and where it really affects the portfolio is for ALM and strategic asset allocation. But all through the investment chain, scenarios are used. So they're used in stress tests for financial but also climate simulations. They're used for decision making in operational portfolio buy decisions. And again, those sets are not uniform for the whole organization. So there is not one, let's say, mandatory set for the whole investment chain to use. Different teams, different managers can use different scenario sets.

Thank you. So if we go to the tension in the scenario analysis. So an AI correction scenario has been on, I think, everyone who works in investment management, so they have had it on their list for a few years now. So if someone would have acted or has acted on it, it has actually—they have given away significant returns. So how do you balance the expected return on the one hand and then the scenario risk on the other hand?

Well, that's a great question. I recall there was an expert panel recently by Helandre and Magnus who sort of gave topics that the fund should be and the Ministry of Finance should be concerned about, and sort of concentration in the US technology stocks was one of the things that they highlighted. And I think it might even be worse than sort of just looking at the weight of Mag 7, because if you think about this as sort of a production line, then you have one company produces the machines, ASML. One company produces the chips, TSMC in Taiwan, and one company designs them, Nvidia, and then you have the hyperscalers buying them. And so I think that in a traditional risk model, these will be in different countries—Netherlands, Taiwan, US—different sectors, IT, communication services, etc. And so in a traditional risk model, it might look like they're quite diversified, but it's really one single bet. And so I mean, it's super interesting because it's a well-worth risk that you should highlight. But the question then becomes what do you do about such a risk? If you run an index tracking portfolio, we have both quant funds and index tracking portfolios. In an index tracking portfolio, it's not within my mandate to say I think this is too risky, I want to derisk, and neither I guess can NBIM, because if you are underweight communication services, you'll blow the tracking error limit rapidly. In an active mandate, you have to assess whether you get paid for the concentration risk. So, it depends on the type of mandate. I think what you can do about it otherwise is educational.

I agree in all the things you said. I'd like to introduce a different perspective, and that's the context of the asset manager or the investment manager that we are, and that is we are investing for a pension fund. So what does that mean? We have a very long horizon to look at, and then when we were talking about the AI bubble and what to do with it, we have to put it into that perspective. A lot of nervousness arises around this point when you look at all the news we've just seen, and that triggers decision makers as well. So what we need to do is to put those decision makers in the perspective of this long-term investment, and then look at what the scenarios mean and what we should do. So there's two decisions or two perspectives to look at: what question are we trying to answer with the scenario? Because when we look at the AI bubble, it can very easily be mixed with, for example, a geopolitical scenario. So which answer are we trying to put a solution to? Is it the AI bubble? Is it geopolitical risk? Is it a mix of both? So we have to separate the questions and then answer each question separately with the proper scenario. So that's one thing. And the other thing is put decision makers back in the chair of a long-term investor. What should we do given this scenario being a long-term investor? And we of course we're constantly looking at this scenario. We're looking at it again both from the AI bubble perspective and from the geopolitical perspective and trying to make sense of it all. But in balancing return and risk from this perspective, we also have to look at the opportunity loss that might be at stake here, especially in the long term. So what we do is not only model and look at what the risk might be, but also look at what the opportunity loss can be. And for decision makers, we use tools like what we call a premortem: the decision went haywire, why did that happen? And use that as well as the downside risk scenario for decision makers to base their decision on in this scenario. And so far, this scenario has—the AI bubble scenario—has led to the decision not to do anything yet, but we're still looking at it because the world is changing ever more rapidly. So, we have to stay in a ball at every time.

Yeah, those are good points, I think. And balancing the expected return loss against—we know the answer is that you should hold the market portfolio, that's the best trade-off between return and risk, but then there might be other considerations from a client's have approached us and want to sort of diversify a little bit away from AI risk. So can I have a question? Does reputation play a role in this as well? Reputational risk in the sense that decision makers want to lower concentration risk, yes or no, or the AI bubble or not.

Yeah, probably. I mean, we found that for example, I think clients want us to have a sort of tailor-made solution in place where we follow something that is possible to track. So for example, many people want to have an equal-weighted index, which I personally find a little bit strange, but that sort of has the reputational risk for the asset owner is probably less than allocating between regions. If that's what you were after, maybe something else.

No, reputational risk for being in these stocks or not being in these stocks. Reputational risk from taking no decision versus a decision, for example.