We recently hosted an interactive discussion on buy side risk management with experts from S&P Global Market Intelligence and senior risk management specialists from leading firms in Amsterdam.

Increased levels of volatility, an uncertain rate environment and liquidity concerns all on top of heightened Geopolitical and Domestic risk have put the spotlight on risk management in financial institutions.

Here is a summary of these discussions.

Value at Risk

The discussion started with a question on screen; how is Value at Risk (VaR) used in your risk management process in today's challenging market?

Approximately 27% of respondents indicated that they primarily use VaR for regulatory purposes. This suggests that regulatory compliance plays a significant role in their risk management process. About 18% of participants reported using VaR to set guideline limits on mutual funds. This implies that VaR serves as a crucial tool for ensuring adherence to investment guidelines and restrictions. Highlighting the versatility of VaR, 55% employ VaR as a combination of both.

In the discussion some participants suggested that the most time consuming was challenging portfolio managers. One risk manager suggested that considering the appropriate time horizons was the key challenge. Further, the group agreed that it was important to have a flexible approach to the risk settings used in VaR calculations. Having the ability to manipulate things like the look-back period, confidence percentile and especially decay factor were all discussed with some risk managers running multiple types of VaR daily to be able to compare and contrast the difference in output. This enables risk managers to have constructive discussions with front office teams as well as investors as they can adapt their VaR modelling based on different market regimes.

Stress Testing

Participants were asked "Which of the following Stress tests are your priority for improving for your investment risk process and why?"

The options were:

- Historical Market Risk stress tests
- Predictive/inferred Market Risk stress tests
- Climate Risk Scenario stress tests
- Liquidity Risk stress tests

The results and discussion were as follows:

Liquidity Risk Stress Tests (33.33%):

Liquidity risk management has become a key part of a risk managers job off the back of recent market events such as the LDI crisis in the UK and the collapse of SVB and Credit Suisse with one member of the group commenting that it takes up to 20% of their day. Liquidity stress tests evaluate how liquidity shocks i.e., stresses on the inputs to a liquidity model such as bid/ask spread impact the overall liquidity of a portfolio. On top of this, liquidity stress testing is a requirement from the European Regulatory body ESMA and should be monitored as closely as traditional market risk measures. The group discussed that having a risk solution with a fully integrated liquidity model would enable them to analyse market risk and liquidity risk in one place rather than having to use separate systems.

Predictive/Inferred Mark Risk Stress Tests (23.81%):

Predictive/inferred stress testing allows risk managers to define several core risk factor shocks and then use a covariance matrix based on a defined correlation period to infer or predict the impact on other risk factors in the portfolio. This was discussed as a popular approach by the group especially with recent periods of stress such as COVID 2020 enabling risk managers to have an up-to-date view on how the correlation of the risk factors in their portfolios behaved in a stress scenario. On top of this, the group discussed how converting macro, economic based scenarios into financial risk scenarios were becoming an interesting approach to setting up these types of stress tests.

Climate Risk Scenario Stress Tests (23.81%):

Climate stress scenarios allow risk managers to estimate the P&L impact to a portfolio based on climate related shocks. It came as no surprise that Climate Stress tests were becoming of increasing importance for buy side risk managers with demands from clients and regulators on the rise It was interesting to note that, it was the Social & Governance parts of ESG that were still considered a work in progress by the participants and that there was more visibility into the environmental aspects of risk.

Climate Risk

Time to abord the question of Climate Risk. We asked our participants "What areas of Portfolio Climate Risk are your focus priorities in 2024?"

42.9% of those polled said they would be embedding sustainability as a risk factor in their modelling choices. While 28.6% they would be looking at the climate impacts on the VaR of their portfolios and similar 28.6% said that uniform data and scenarios are being used in their portfolio investment risk decisions.

These results show that for risk managers, adding Climate Risk to their workflow, is a key goal for this year.

One large institution said that whilst they had a team for this, there are increasing demands for this from clients. There was a discussion on carbon impact and carbon reduction, and the impact on spreads. It was also said that due to the nature of climate change happening over several years beyond our usual horizons, it is essentially difficult to test within the short-term lens.

It can also be tough for Risk Managers when Portfolio Managers pick investments that may have positive carbon reduction goals. Also, a few agreed that picking Best in Class Investments was their favoured approach as the idea that limiting the investable universe too much could risk Alpha generation.

As an aside, you can read S&P Global's article: ESG factors for predicting changes to CDS spreads

Liquidity Risk

The question asked: "Which of these scenarios have had the biggest impact on the liquidity profile of your funds?" and the options were:

- Rising inflation & Quantitative tightening
- Global increases in interest rates
- LDI UK Crisis or US SVB collapse
- Private asset holdings

The results were firstly, that global increases in interest rates have had the most significant impact, accounting for 40% of the respondents. Following closely, private asset holdings contribute to liquidity considerations at 26.67%. The LDI UK crisis or US SVB collapse scenario stands at 20%, while rising inflation & quantitative tightening has the least impact, with 13.33% of respondents.

One firm retold their experience with the U.K. GILT crisis of 2022; the sheer speed of the yield increase had taken them by surprise; it was not something they had previously been testing for and have since added a short-term horizon to their liquidity stress tests.

Private investments have become more popular over the last decade due to asset managers seeking yield in a low interest rate regime, but liquidity concerns associated with these assets was clearly a concern. Interestingly, one firm noted that exposure to private assets had increased due to investments in climate friendly companies where exposure was only obtained via private securities due to the size of the company.

Refinancing and Credit Risk

Corporates are facing considerable refinancing requirements in the remainder of 2024, 2025 and 2026. Almost $2 trillion of debt is due between 2025 and 2027, the majority issued by US corporates ("Global Credit Outlook 2024", S&P Global Ratings). Though rates are expected to fall in most developed economies in 2024, the cost of refinancing is likely to be punitive for many issuers, particularly in the high yield universe. Default rates are expected to rise this year for speculative grade debt and our participants acknowledged that increasing credit risk was a major factor under consideration. Use of the correct historical data was crucial in managing this risk in bond and leveraged loan markets. Private markets are more challenging due to paucity of data, with some participants utilizing solutions from third-party vendors.

For analysis on how market volatility is affecting liquidity in loan and CLO markets, read this note

Artificial Intelligence in Risk Management

We asked our roundtable participants "What use cases do you see for AI in Risk Management?"

The top answer was Automatic Detection of Outliers and Early Warning Signals (34.78%). AI algorithms excel at identifying anomalies and deviations from expected patterns. Detecting outliers and providing early warnings can help mitigate risks before they escalate.

Next was Automatic Generation of Risk Reports (30.43%). AI can automate the creation of comprehensive risk reports; this could streamline the process, enhances consistency, and ensures timely delivery of critical information.

Followed by risk analysis generated from natural language questions (21.74%). AI could use historical risk data to interpret natural language queries related to risk and present risk analyses in a unique and insightful way.

Finally, by using Stress Tests Generated from a Large Language Model (13.04%). Leveraging AI-driven language models to create stress scenarios based on natural language inputs. This could allow risk managers to define a test and have AI work out the specifics of the stress tests based on the risk factors in a given portfolio.

Though at risk of being something of a buzzword, participants were all keen to discuss the use of artificial intelligence in the risk management setting. Some had been using well known LLM providers to help with report writing though review was still necessary. Another use case that was discussed was leveraging AI to act as an early warning signal; allowing AI to train themselves using the firm's own data and getting more and more accurate over time- noticing trends, changes and other patterns that might not have been possible.

Everyone who participated in our insightful discussion on buy-side risk management engagement and expertise made this event truly exceptional. We plan to continue this dialogue beyond this event.

Thanks once again to our attendees for their valuable contributions.

To learn more about our Buy Side Risk solution please click here.

Statements by persons who are not S&P Global Market Intelligence employees represent their own views andopinionsand are not necessarily the views of S&P Global Market Intelligence.

S&P Global provides industry-leading data, software and technology platforms and managed services to tackle some of the most difficult challenges in financial markets. We help our customers better understand complicated markets, reduce risk, operate more efficiently and comply with financial regulation.

This article was published by S&P Global Market Intelligence and not by S&P Global Ratings, which is a separately managed division of S&P Global.