May 28, 2015

Dealing with Model Risk – Highlights and Perspectives from Greenwich Associates & Numerix Panel Discussion

A recent industry panel discussion led by Numerix Chief Marketing Officer, Jim Jockle, addresses many of the key challenges associated with model risk faced by today’s financial market practitioners. So, just where is the prioritization of model risk management these days, and how has it been shifting?

From regulatory drivers and quantifying model risk, to new trends in model risk management and model-based limits—let’s face it: the level of complexity we’re looking at is off the charts when it comes down to managing model risk. Moreover, at the end of the day, a model can only ever be ‘a model’ based on reality. That being said, maybe the question we should all be asking ourselves is, “How do you know when your model is bad?” or furthermore, 'Just how bad is this model?"

Where do we begin our quest toward the achievement of model risk management’s holy grail? Join panelists Kevin McPartland, Head of Market Structure and Technology Research at Greenwich Associates, along with Dr. David Eliezer, VP and Head of Model Risk, and Satyam Kancharla, SVP and Chief Strategy Officer at Numerix as they address key issues and new trends related to model risk.

In this moderated discussion addressing some of the findings revealed in the analyst report “Reducing the Risk of Using Financial Models,” our experts answer top-of-mind questions raised by a wide range of derivative market participants.

Below is a short excerpt highlighting some key discussion points from the panel:

Q:
Jim Jockle: Based on your report, how are banks looking at model-based limits, and are they in some ways at a disadvantage? What are ways that individual firms can fast-track models?

A:
Kevin McPartland:
At a high level, it’s actually pretty simple. If you have a new product, the faster you can get it to market in theory, the more beneficial it will be to your revenue in the end. However, when we are talking about complex structured products (for example, a structured deal that’s set-up for a particular client that needs to go through the model review process) it can take much longer.

Most of the banks we spoke with in our research did have some way of letting the trading desk go ahead to the client with a model under a certain threshold (for example, if a client had USD 500 million to put into the deal, the model risk team said you can go with 10 percent of that amount, until we do a full model review). It wasn’t a set amount of time, or a set dollar value, because all of the deals are very different typically.

However, in cases where it took the model team a month to get the final approval, opportunities very well could have been lost. Streamlining the process would provide a huge competitive advantage, if you are able to respond to client demands much more quickly.

Does this discussion sound interesting to you? Watch our moderated panel discussion between experts at Greenwich Associates’ Kevin McPartland, Principal, Market Structure and Technology, along with Numerix’s Dr. David Eliezer, Vice President, Head of Model Validation and Satyam Kancharla, Chief Strategy Officer & SVP of Client Solutions Group. View panel discussion.
 

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