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Risk Management

02:26 PM
Oskar Mencer, Maxeler Technologies and Imperial College London
Oskar Mencer, Maxeler Technologies and Imperial College London

Trading & Risk: What's Your Favorite Risk Flavor?

Market participants who master the convergence of trading, risk and market data will create a competitive advantage, as a Risk-as-a-Service (RaaS) model emerges.

Oskar Mencer, Maxeler Technologies
Oskar Mencer, Maxeler Technologies

With events of the last decade, the world of the back office is converging with the world of the front office while investment banking is converging with exchange traded financial products. Convergence is driving a need for predictable order entry with increased risk management to manage both OTC and exchange traded products.

We all know that over the past decade, the computerization of financial markets has increased the volume of trading. As complex financial products evolved, coupled with the increased appetite for leverage, extreme risks emerged for all market participants. Ever since 2008, the financial industry has been going through significant convergence via reorganization and changes in the regulatory landscape. As a result, Over-The-Counter (OTC) products are becoming available on exchanges, while Basel III, Solvency II and Dodd Frank are being tuned to reduce uncertainty in financial markets. The result for traders is that more legislation means more computation (of risk analytics) and therefore more technology, more complexity and more cost.

On the technology front, we are also experiencing the convergence of hardware and software. More and more functionality that could previously only have been achieved with custom hardware development can now be accomplished in software. As financial institutions take on more and more components of the technology stack to respond to the convergence, that technology tower becomes more customized and more dependent on computation. This leads us to a thesis from many venture capital firms that “software is eating hardware.”

We are living in an Era of Convergence." -- Dataflow Session, Hotchips Conference, Stanford University, August 2013.

The amount of customization that can be done via software is increasing to meet the computational and functional needs, but there is a need for scale and cost efficiency that can only be achieved by leveraging best in breed products based on open specifications. There is simply a limit to the number of highly skilled practitioners who can support the complex needs presented by convergence. Financial institutions can create competitive advantage by reevaluating their technology stack through the lens of convergence, scale and efficiency.

Risk Flavors

Risk comes in many flavors and nobody likes uncertainty. Risk analytics form a computable component of uncertainty just as weather models are computable components of the uncertainty of weather. We know the weather report might not be right, but we are happy to pay for the comfort of even slightly reduced uncertainty. Yet we do not all try to come up with weather models and compute the likelihood of rain. Instead we count on our local meteorologists on TV or radio to deliver the forecast. The same is true when it comes to calculating risk in the enterprise. It is more efficient to use third-party platforms for risk than to build it from scratch. This allows firms to spend more time developing their “secret sauce” (competitive advantage) that they can add on top of the risk platform.

However, the convergence of trading and risk poses distinct challenges across the technology stack. Trading starts with order entry. Does it make sense to have fast order entry without fast risk management? These days, full Tier-1 level risk models do not have to be slow any more. Investment banks have invested heavily in risk management software, using quantitative analytics to manage risk on trading desks and across entire banking groups.

To put things into perspective, the American Finance Technology Award for the "Most Cutting Edge IT Initiative" in 2010 went to the trading desk of an investment bank for moving risk calculations for credit derivatives from a single over night risk calculation to intraday calculation of tens of thousands of scenarios – permutations of future events and their impact on the bottom line.

Once order entry and risk are pushed to the next level, market data becomes the fabric creating a huge burden on operational costs and challenging the viability of the technology stack. Thus, market data becomes the challenge and the opportunity to differentiate. Consequently, market participants will benefit from a significant increase in market data processing efficiency that can be achieved through open standards and specifications along with the convergence of hardware and software. In particular, market data is born, lives and dies at the exchange. So, at the heart of the system we now have exchanges driving the efficiency of order entry, risk and market data. The competition resulting from the convergence of trading and risk will ultimately maximize the efficiency of financial markets and benefit everyone.

The market participants that succeed with the convergence of trading, risk and market data will be ahead in the race to come. Firms will be looking at risk scenarios and trading transactions in real-time, which essentially creates a Risk-as-a-Service (RaaS) model. These are competitive truths that apply to any financial institution irrespective of the type of strategy or business model.

About The Author: Oskar Mencer, CEO, Maxeler Technologies and Imperial College London Prior to founding Maxeler, Oskar was Member of Technical Staff at the Computing Sciences Center at Bell Labs in Murray Hill, NJ, leading the effort in "Stream Computing". He joined Bell Labs after receiving a PhD from Stanford University. Besides driving Maximum Performance Computing (MPC) at Maxeler, Oskar was Consulting Professor in Geophysics at Stanford University and he is also affiliated with the Computing Department at Imperial College London.

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