Mar 19, 2012

Model Risk Management: Assessing and Tackling the Key Challenges

These days, many of us find ourselves up late at night mulling over the potential implications of Dodd-Frank and Basel III. Questions such as, “How much risk is really out there, and who is holding it?” may be dancing in our heads. As we find ourselves older and wiser post-2008 crisis, we’ve come to see that in the past, many market practitioners have overlooked an important component of risk management: model risk. With all the new regulations out there targeting different aspects of financial risk management, just how important is model risk and, moreover, how do we frame it?

“Model risk is really about assessing the quality of the models being used and being aware of the risks underneath these models, and measuring them on a regular basis,” explained Satyam Kancharla, Senior VP of Client Solutions at Numerix, in a recent interview with Gregory Crawford at Tabb Forum. “This is profound because not many people had been looking at this before,” said Satyam. “It’s like the rug being pulled out from under your feet, because nobody is looking at this,” he added.

In a compelling interview with Mr. Crawford, Satyam outlined the three key challenges facing model risk today, explaining that “all models are modeling the financial markets and the human beings participating in these markets.” That being said, that is also the challenge in itself: How do we adequately model the changing and often unpredictable dynamics of the financial markets and of human behavior? How can we predict what will happen?

According to Satyam, when it comes to model risk, key challenges exist in the following three areas:

  1. Knowing and understanding the assumptions behind the models
  2. Problems with the data quality that goes into the models
  3. Understanding the results, and interpreting them accurately

Other challenges facing model risk include: measuring liquidity risk in a consistent manner, which no model is capable of handling completely; and measuring volatility, which can be equally complex to model because capturing the entire volatility smile is not possible in most cases.

For more information on Numerix model risk solutions, contact

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