Trends in balance sheet management and risk interconnectivity

Leo Armer, Vice President of Client Services at SS&C, dives into the widespread adoption of generative AI and its potential transformative impact on the financial risk sector. The conversation expands into the increasing focus on climate risk management, the role of risk managers in the front office, and the interconnectivity of various risk types like credit, market, liquidity, and climate risks in affecting balance sheet management.

Read the transcript below

Leo, thank you so much for joining me today at RiskMinds HQ. I wanted to talk to you about a couple of things – the hottest things that are happening in risk management today. First of all, generative AI and its adoption. Tell me, what are you expecting in the next three years?

We see the appetite for generative AI as insatiable as we do for the rest of the financial risk sector. In the next three years, we believe that generative AI is going to cause more innovation than it has done over the past maybe 10 to 15. That's largely down to what businesses want to get out of generative AI and how they want to change their approaches and gain new insights.

Specifically, on the financial risk side, there's more data available to us now than there ever has been before – not just structured market data, time series data, but also unstructured information. The unstructured data that we are receiving, with generative AI, clients are asking us to gain more insights into those data sets, and to understand more about scenarios and predictive scenarios that we can build.

There are two really good examples of generative AI that we see on the horizon over the next three years supporting the modelling of private credit and alternatives, using the unstructured data that I've just mentioned, and also in the field of portfolio construction. Here our clients are really interested in finding ideal hedges where generative AI can support optimisation problems and given certain constraints such as positive market sentiment. Then we can help them to rebalance the portfolio and reduce risk and lower sensitivities to risk factors and improve returns. So we're actively exploring AI that helps our clients to analyse and gain greater insights than they've ever had before.

Amazing. So there's a lot going on in the future then. What about today? How is generative AI being used today?

Within SS&C we've looked at generative AI within our Intelligent Automation Framework. So we've already built within the risk capabilities is the ability to support environments, support clients using digital workers, using intelligent automation agents which help our clients to gain more insight into their portfolios. We can compare data, we can provide more analyst reports from back to front end users purely by using our agents that we've deployed and we've been producing that for the last 12 to 18 months. So this is not a new technology for us.

On the credit management side, we're also looking at leveraging digital workers to use credit access management, limits management processes, which then cut down the amount of limits and excesses that an end user has to apply on a daily basis, from thousands of cases that they'd have to investigate down to tens or even individual single digits.

Thank you so much for the insight on the generative AI front. Let's talk about climate risk management. The regulators have now changed their tune a little bit on the disclosures of climate risk materiality. Now it's a must have, rather than a nice to have. But what are financial institutions doing today to help incorporate those risks – the transition risk and climate risk into credit and market risks?

We see significant activity in the climate risk topic and we work very closely with some industry leading partners, people who've got direct links into the regulators. In fact, they helped to write some of the regulations that you've mentioned.

We understand why this is more important now than ever has been before. Traditionally, some of the geographies are not as interested in the climate risk topic as others, but data around transition risk and physical risk is becoming more readily available and in greater coverage.

This is affecting investment decision making – who lends, who trades with whom… and so the material risk of that cannot be ignored. So we continue to invest. We invest significantly in the research on this topic. Climate risk, NGFS scenarios, exogenous ESG factors… all of that research is within our organisation.

We see clients wanting answers to simple questions such as how much of my credit risk exposure would be affected by a specific hurricane? Or which of my heavily exposed counterparties have lagged behind in their migration to a topic like NetZero? We've explored lots of approaches and we've been working with our clients to put together roundtables so we've got their opinions on this topic and applying and integrating NGFS scenarios into our portfolios, modelling the physical and transition risk within both our market and credit risk simulation framework.

Amazing, Leo! The other thing I wanted to talk to you about is the trend that gears towards risk managers having more of a value driven role in the front office rather than taking the regulatory/ back office type role. Can you maybe give me an insight into what you've seen companies doing well on that front?

For sure! Risk is a greater place in the front office now than before. Our risk solutions have been supporting PFE credit and CVA desks in the front office for over 20 years! Providing real time credit risk calculations to traders and front office credit teams is something we're very used to. We've also been asked by those organisations to open up our framework. Our robust risk models can be accessed now from the front office. That's a key trend we see in the market and we see a lot of those clients making good benefits and use out of the access to those APIs.

Recently, we've seen an increase inside buy-side OMS and PMS, our order management system and portfolio management systems that support the asset managers and support the pension funds, where end users want to get a real-time access to market risk measures and compliance checks. So integrating and embedding the risk engines within those OMS and PMS system has been a key trend we've seen in the marketplace. Why just determine the risk after the fact? AlgoEngine's embedded within the solution that supports the front office teams from breaching a compliance rule.

Absolutely! Tell me more about the interconnectivity of risks. We've seen this with climate risk, which we've just talked about, incorporating into the more traditional risks. How are the new trends in credit risk, market risk, liquidity risk, and climate risk impact the balance sheet management? We're talking about the trading book here, the banking book, etc.

A message of enterprise risk management has been around for many years and the interconnectivity is maybe the part that is the most challenging.

If we look at a risk view from a market risk team, it tends to be looking at portfolios or maybe the sensitivity to certain risk factors. However, if we look at credit risk or capital calculations for example from the counterparty level, then those portfolios start to overlap, the factors overlap, and with the alternative investments of private credit, there's many exogenous risk factors that are involved. It soon gets very complex and difficult to manage.

Climate risk is another good example where factors can impact a firm's exposure to the direct valuation but it also the default probability of the counterparty that we're contracting with. So there's a key interconnectivity that has to be considered.

I think enterprise risk dashboards need to provide an overview to the CRO or to an exec level group. But importantly, they must have the ability to drill down and provide, specific views tailored to the SMEs that are working on those, in those individual risk silos. Going back to your question about, balance sheet management and how does that keep up?

I think we've seen more and more demand now for realistic and dynamic forward looking balance sheet projections strategies, enterprise stress testing, which is embedded within our solution and which our clients are very keen to deploy now because as you say the process has changed internally within the balance sheet management.

Amazing, Leo! Tell me more about the balance sheet management trends here. How are financial institutions keeping up with the challenges of interconnectivity?

We see more and more demand for realistic and dynamic forward looking strategies to beat regulatory driven or enterprise driven stress tests such as ICAAP and ILAAP. Accommodating that interconnectivity of macro market risk factors, the balance sheet positioning and including new factors is a must have for vendors in the balance sheet risk management space.

Nevertheless, when you're comparing multiple risk silos, interconnectivity and interdependency is fundamentally important.

Leo, thank you so much. I wanted to close, finally, on RiskMinds International and you'll be joining us later this year. Tell me, what are you most excited to discuss and learn about at the event?

Yeah, I'm really interested. We've talked about generative AI at the start of this, I see a lot of content in there around generative AI, which is obviously very topical, but also very exciting to understand where people are on that. And I think a lot of your balance sheet risk management topics as well, I think will be really interesting to all of your attendees.

Join Leo and 1,200+ senior risk professionals at RiskMinds International.