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.
