The New Risk Management – Data Management?
These days, risk management is high on most trading firms’ agendas. That is risk management in both the broadest and narrowest sense. Increased oversight, regulation and both the rapid evolution and increasing speed of markets is driving this need. In a climate of price volatility, volumetric uncertainty, innovation in deal structures, changing regulations and globalization, effective risk management and the ability to respond to valuation challenges and portfolio optimization opportunities are pre-requisites to profitability for organizations that deal in commodities.
Risk Management Problems
But there is problem. A set of problems, in fact, that make the risk management issue one which is difficult to solve. Those problems often include the following issues (and this list is far from being complete):
- The need to access accurate and timely data from a number of different systems, including Commodity Trading & Risk Management (CTRM) solutions, price feeds, internal systems and spreadsheets, online trading systems, and more;
- The use of multiple CTRM solutions for different commodities which store and process data differently and are often not integrated;
- The inability of some CTRM solutions to keep pace with developments in energy and commodity risk metrics. CTRM vendors have a broad range of functionality to focus on and requirements to meet, and sometimes are unable to deliver everything for a particular release. This is often a problem for more sophisticated trading operations, and it can force them to go off system for risk solutions;
- Inability of some CTRM solutions to run stochastic risk metrics in a timely fashion;
- Data quality issues which can result in costly errors, or omissions which invalidate batch runs of stochastic risk metrics;
- Inability to perform certain specific risk metric calculations, or perform stress tests.
As a result of these issues, many users turn to other ways to handle various aspects of risk and risk reporting. Certainly, one of these ways is to deploy a risk management overlay of add-on to their suite of systems from specialist solution providers such as Lacima Group, SAS and Ascend Analytics, for example. Indeed, for many risk issues specific to energy or commodities such as the ability to more accurately address commonly used instrument types, assets and so forth, this is certainly a solution. Other vendors have made attempts to differentiate themselves with an innovative approach to risk management—particularly for physical energy businesses such as, for example, Abacus Solutions with its SATURN software. Unfortunately, many of these solutions are still relatively new to the market and most traders rely on solutions procured in earlier buying cycles.
Before going too much further, I do not want to give the impression that leading CTRM solutions don’t handle risk management effectively, as that is certainly not true. Almost all CTRM solutions handle basic market risk very well, and some also handle credit risk effectively. Almost all CTRM vendors are working diligently on enhancing their risk functionality across the board and will meet many requirements in the risk management area. But the big picture, shown in our research1, is one in which traders are struggling with broader risk issues, and quite frequently with specific risk issues around particular assets, instruments and the particular specifics of their business. These areas are where risk specialist solution providers, such as Lacima Group, excel.
Data Management
But what of the broader risk picture? In fact, it seems that an array of data management solution providers are eyeing that space including vendors like LIM, SunGard FAME, Datagenic, SAS and Hyper Rig. The data management software providers can help solve a number of broader issues around risk management, such as:
- Ensuring data validation and cleansing with their validation tools. Data from a variety of different sources can be validated and checked before being pushed into a data warehouse or other repository. Further, vendors such as LIM have also developed tools to check for valid and omitted data in CTRM solutions prior to running risk analytic batch jobs, thereby helping to reduce the risk that, say, a batch VaR calculation, which can take many hours to complete, actually runs.
- These tools are often real-time and event driven, meaning that the data repository has valid data that is populated in near real-time as things, like prices, change.
- Once the data from multiple sources has been validated and deposited into the repository, users may query and report on it and, of course, perform more sophisticated risk analysis on it using various software tools, either provided by the data management solution provider or other specialist risk tools.
- Depending on the nature of data pulled in the purpose of the data management, the solution can be to perform risk optimization, risk management, regulatory reporting, etc.
Vendors such as Hyper Rig have developed sophisticated data management tools specifically for risk management purposes, providing risk optimization and risk aggregation tools which come armed with innovations in risk analytics and risk analytic processing. Others are more focused on bringing in various price and market data.
Summary
In the end, it may be that data management is the solution to the broader risk issue. The ability to extract data from across multiple internal and external systems and sources helps eliminate the integration issue, the ability to cleanse data solves issues around data quality and the storage of that data in another data store allows more manipulation and analysis of data in a relatively real-time environment. The emergence of vendors such as Hyper Rig and others who are focused on data management for risk management in the commodities trading environment reinforces this possibility.
1 Energy Risk Management Software Report, 2009, CommodityPoint & Seminel
