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5 Advantages of Adopting High-Performance Trading and Risk Technology
By Jay Bagchi | January 14, 2016

Instead of facilitating business, buy-side firms are now finding that their legacy trading and risk systems are actually impeding it. While once legacy technology may have been enough, today’s buy-sides need more sophisticated architecture to support complex investment strategies. It was this trend that I discussed during FINCAD’s recent webinar: Trading and Risk Technology: Drive Value with High Performance Architecture.

During the event, I explained that many firms’ technology is making it increasingly difficult for them to meet key requirements for on-demand risk analytics, large complex portfolios, new asset classes, multiple data sources and substantial regulatory reporting. Therefore, they are turning to modern trading and risk solutions that help them break down silos and access consistent analytics for a holistic view of risk across the enterprise. The end result for many is scalability, rapid ROI, improved performance and governance, and lower cost of ownership. Below I’ll discuss five key advantages of adopting modern trading and risk solutions.

1: Enforce Accurate Modeling  

Buy-side firms commonly rely on Microsoft ®Excel spreadsheets to manage curves. Typically it is individual users’ responsibility to keep curves up-to-date and in sync. However, the nature of any manual process is that it introduces greater risk for error that could potentially cost firms valuable business.  

To address this issue, many organizations are adopting sophisticated valuation and risk analytics solutions that help them ensure curves are used in a self-consistent way, reducing the incidence of expensive modeling mistakes. Such a solution should make it obvious to users which curve version is the most up-to-date, ensuring everyone is on the same page. This approach will make it easier to share curves and their associated assumptions with all stakeholders throughout the enterprise. Instead of merely overwriting an outdated curve, the technology should keep a running record of all previously published versions, enabling firms to create a proper audit trail.  

2: Automate Data Reconciliation   

Financial organizations utilize data from a myriad of different sources in their trading workflows. But often the data is not formatted uniformly. This can potentially cause mismatches in not only the data itself, but also the data semantics—that is, the way one user uses and understands a given data field could be different than another user. Discrepancies in data can ultimately lead to mismatched valuations, and unclear or unusable risk numbers. To work around this issue, many firms spend considerable time and money having data reconciled. 

Today’s leading valuation and risk analytics solutions ensure that any data type, whether it be market data, trade data or reference data, can be used in a consistent way. This is accomplished through data normalization and transformation functionality that uses data-specific parsers to resolve any data format incongruities. Once the data has been properly parsed, it is then converted into a normalized, uniformed format, which also enforces consistent semantics. What all of this means is that everyone across the organization is working with the same data, ultimately helping firms make better-informed business decisions.

3: Speed the Process of Valuing Complex Instruments 

In search of greater revenue opportunities, many firms are adopting trading strategies that involve complex instruments. However, they are challenged by pricing these products using Excel, as the tool slows down under the weight of heavy computational demands. Furthermore, because Excel is a single-threaded tool, it is incapable of performing such calculations as Monte Carlo simulations in parallel. This makes pricing large-sized portfolios very time-intensive. In essence, what this all means is that no one individual in an organization has enough power on their local platform to perform complex calculations in a swift timeframe.

As a solution, many firms are adopting high-performance valuation and risk analytics technology that allows them to scale on demand, as it makes sense to do so. This way, users are not restricted by their local hardware, nor are they limited in their ability to do business. For example, FINCAD’s F3 Platform allows you to add a set of calculation managers and engines on the fly, creating two places for requests to be forwarded. This doubles the scale of your system without downtime. Outstanding portfolios can then be priced in parallel, helping you close deals faster, and ensuring you don’t miss key deadlines.

4: Establish Enterprise Scalability

Many derivatives organizations are challenged by the need to add extra hardware components in order to address fluctuations in processing demands on their trading systems. But often the addition of hardware, such as a new server, means that organizations need to perform significant systems redesigning and recoding. This is because their software lacks scalability and is not distributed.  

To achieve enterprise-wide scalability, firms need access to a flexible analytics solution based on generic architecture, allowing them to easily tack-on hardware as necessary. This approach can foster better capacity planning, as firms will be able to quickly and easily scale their technology as needed to accommodate an uptick in demand, such as, for example, the need to value large numbers of portfolios simultaneously. Organizations that adopt solutions designed to scale on demand typically experience cost savings and an overall lower cost of ownership when stacked up against the traditional approach of having to buy a new server or redesign software to cope with changes in processing volume.

5: Accelerate Workflow

Some trade and risk analytics solutions in the marketplace have been designed with only the quant user in mind. They lack simplicity of use making key tasks like working with models slow and convoluted.

A modern risk and analytics solution should help simplify the process of creating, obtaining, and valuing trades for all users –whether they are traders, risk analysts, quantitative analysts, or software developers. A toolkit providing guidance for entering input values in a function and the ability to easily drill down into curve and market data will accelerate your workflow. Pre-built models and curve definitions will enable easier and faster model building, helping you speed up the delivery of new applications. Furthermore, the option to customize interfaces, views and dashboards will provide an optimal user-experience that meets individual users’ varying needs.

High-performance trading and risk architecture is becoming a necessity for buy-side firms because it accelerates the process of pricing trades, thereby helping you take advantage of a wider range of profitable trading opportunities. To keep operational costs low, you should seek technology that enables a reduction in the time and effort attached to reconciling front and middle office differences in data. This approach will promote better capacity planning and resource sharing, as well as overall efficient use of available hardware. 

For more information on how sophisticated technology can help your firm be more competitive, watch our on-demand webinar: Trading and Risk Technology: Drive Value with High Performance Architecture.