In this video blog Denny Yu, VP of Numerix Client Solutions Group speaks with Alex Tabb, Partner & COO of the Tabb Group about new methodologies moving beyond the traditional regulatory required stress test and how a robust risk scenario framework can be implemented in today’s complex environment.
Widely recognized as an onerous task, namely the hundreds of thousands of man hours it takes to fulfill stress test reporting requirements, banks are starting to seek more automated approaches where an enterprise level framework can be leveraged for user-defined risk scenarios and stress tests. Denny explains how this approach can not only save considerable time, but enable the ability to look at data across the organization for better insight into daily risk management needs.
Alexander Tabb (Host): We here at TABB Forum have given a lot of thought and discussed the topic of risk, big data, and advanced analytics. Today I’m joined by Denny Yu from Numerix, and I want to talk about putting those things into the operational use. And I really want to talk about the new methodologies around stress tests. Denny thanks for joining us today. Can you tell me a little bit about moving beyond the traditional regulatory required stress test in today’s complex environment?
Denny Yu (Guest): Of course. Thanks for having me again Alex. So when we talk about stress testing today we know that a lot of banks are mandated under regulatory requirements to produce stress tests for the Fed under SCAP, CCAR, or CapPR, but what we’re talking about really when we’re talking about going beyond regulatory stress testing is creating insight from frameworks that allow us to really get at the underlying risk factors to the portfolios as well as the underlying trades where the risk concentrations are essentially in terms of where would we want to mitigate risk with hedges. And when we’re talking about robust stress testing, we’re not talking about running a spreadsheet which is looking at one trade at a time. We’re really talking about looking across the enterprise. Whether you’re a buy side or sell side institution.
Tabb: So you are basically talking about creating a mechanism within these institutions that can do this in an automated fashion. Is that where you’re getting at?
Yu: Very much an automated fashion that allows you the flexibility to create new scenarios on the fly and then run them on the fly. Today what we see when we speak with a lot of different participants is it’s very much a spreadsheet exercise. Every time management wants to run an enterprise level stress test it’s a fire drill. And it can take weeks to really produce final numbers at which point the market has shifted.
Tabb: Yeah I had heard a fact that a regulatory mandated stress tests for large institutions could take hundreds of thousands of man hours. I assume what you’re trying to get people to do is to move beyond that manual process and start moving into an automated process where they can then take those outputs and do what with them?
Yu: Right. So in terms of that, number of hours it takes, the Fed actually estimated their mandated stress test would require a bank to run around 680,000 man hours to actually complete the stress test. And what we’re talking about is moving that from typically a three to four month manual exercise to a daily ability to implant new scenarios. And that requires actually some technology infrastructure that automates that process and joins all the disparate data together.
Tabb: Now, is this only for large sell side institutions that are maybe your banks that are regulated by the Fed or other national entities or is this something for more of the mid-tier sell side or possibly even the larger buy side folks?
Yu: This is really for any institution that is a market participant. So the regulators that actually just made it part of the forefront because it’s a mandate. But hedge funds, asset managers, pension funds have all been thinking about or actively engaging in stress test frameworks and so it really runs the spectrum of how far along they are in building this framework.
Tabb: How hard is it to put this mechanism together? I can’t imagine if you’re a large institution gathering all that data and automating it and combining it in one centralized desk or one centralized operation is an easy task.
Yu: I would say it’s always going to be difficult in terms of getting the data from different places to talk to each other. But really in the last decade, we’ve seen technology evolve to the point where they’re a lot of off the shelf, even open source software that I could usually integrate different pieces together. And we find the biggest challenge is not technology or bringing different pieces of data together, it’s the political challenge of getting different departments and groups to be willing to share that information and work in a collaborative manner.
Tabb: So let’s say that I’m interested in trying to do this. Where are the benefits? I know the cost. We’ve talked about what’s involved. Why should I do it? What drives me as an institution if I’m not mandated by the Fed, why should I even go down this path?
Yu: Sure I’ll give you a perfect example. When the Lehman Crisis happened, every institution that had some exposure to Lehman asked the same question. It was, how much do I have against, or for Lehman? And that became phone calls, faxes, emails, to gather that information. Today, five years later, a lot of institutions still cannot answer that question in hours. And that’s one of the big benefits of having this framework. If you have a robust stress testing framework, it actually implies that you have the ability to look at data across the organization.
Tabb: And can that mechanism be used to start generating alpha? If I have better understanding and better analysis of where my positions are, and what my overall risk is, to me that’s a perfect leeway into developing strategies that can create new channels for alpha.
Yu: Absolutely. Stress testing has always been a way to looking at what can attack the portfolio but also looking at what can produce outsize gains in the portfolio. Now that we have a lot of mandates for central clearing, one of the things we’re seeing more and more being done is collateral anticipation needs. So, forecasting exposer profiles of the trading portfolio to anticipate collateral posting needs one week, one month from now and actually creating alpha by essentially saving on funding.
Tabb: Well Denny I really want to thank you very much for joining us at TabbFORUM to discuss this very interesting topic. I think we’re going to hear more about institution mandated stress testing and moving beyond the standard regulatory platforms that exist.
Yu: Thank you Alex.
Tabb: Thank you.