01.14.10Edward Cuoco, Director of Utilities and Energy Markets, Martin Dawes Analytics

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Lower commodity prices and more competition in energy markets continue to pressure profits and margins which, in turn, increase the importance of fast and accurate risk reporting in energy trading. Internally, faster position reporting and optimization cycles are required to in order to maintain a competitive position. Simultaneously, this reporting must maintain a high level of granularity as regulators and auditors seek balance at 60, 30 and sometimes even 15 minute intervals. While organizations continue to move towards intra-day position reporting, the breadth of detailed data and the frequency with which they are provided are not adequately leveraged through the normal risk reporting process.

As illustrated above, positions are generated daily and intra-day, these reports leverage estimates of generation and off-take data. Consequently, the actual data end up as part of manual portfolio optimization that occurs daily, weekly or even less frequently. It is possible, however, to enhance risk reporting with tools found in other industries, allowing for faster integration of detailed supply and demand data and eliminating this longer reconciliation cycle. Those companies that adopt effective analytic tools will be able to rapidly assess, evaluate and react to these critical data and put themselves in a stronger position to make more timely and informed decisions about future trades and contracts.

Integrating intra-day supply and demand data with intra-day reporting creates competitive advantage through reduced risk in the portfolio, lower fines and/or penalties for being out of balance and ultimately, in improvements to trading strategy. Operationally, integrated data improves the firm's ability to adapt trading strategies faster. Timelier accounting for supply and demand data will also reduce risk for long-term contracts and provide improved insight into counterparty and contract profitability. Few organizations are using either supply or demand generation data on an intra-day basis despite the obvious benefits. Thus, trading desks are forced to perform a "true up" by means of manual reconciliation of the data to position reporting days or weeks after the fact, sacrificing margin or even moving from profit to loss due to "unexpected" changes.

Hidden Gaps in Current Systems

The difficulty trading organizations face when assessing the data in a more timely fashion stems from a perceived inability to apply the data to risk reporting more frequently, while ensuring that the data is granular enough to revise the position in quarter hour increments. Attempts at systemic solutions to this problem end up in one of two untenable outcomes; the information can be processed intra-day, but at insufficient granularity to remove the need for post-day adjustments or the data is granular but the time to acquire, process and analyze the data is too long to allow it to be used same-day. For most trading organizations, it has not been possible to resolve these problems within a time and price range that reflects value. Indeed, for those that have been completed, many other attempts have failed or been prematurely abandoned due to the exorbitant expense or lack of demonstrable success.

The myth prevalent within many trading organizations is that these issues cannot be resolved without a massive IT investment. This leads trading organizations to believe there are only two possibilities; either repeated and increasingly expensive attempts to create tools to integrate these data or, to give up altogether and implement work-arounds or reduce risk limits to allow the enterprise to live with the existing problem. In reality, companies are simply trying to solve the problem with the wrong tools. Enterprise trading solutions (i.e. CTRM tools, back-office financial systems) are large and complex, requiring a significant investment of time and money, and cannot be quickly adapted as business needs evolve. While Excel-based tools are flexible, they lack both the ability to handle larger volumes of incoming data and the transparency and auditing ability needed to provide confidence at scale.

Solutions Lie beyond Trading Tools

In order to leverage the full range of supply and demand data on an intra-day basis, trading organizations must look outside of typical CTRM or BI tools. As an example, industries such as telecommunications and manufacturing make good use of process analytic tools in order to address analogous issues in their spaces. These process analytic tools have the elements needed to ensure that detailed data is quickly and granularly analyzed at speed. Specifically, they are data-architecture independent, allow business users to create and change analytics quickly and without a major IT engagement, and allow both logic and data to be modeled in the same tool. Equally important is that these solutions support an analytic methodology where discovery and analysis happen simultaneously -- with business users creating tools collaboratively even as they investigate the data. This combination of technology and methodology enables energy companies to enhance their risk reporting by integrating supply and demand data intra-day. When looking to acquire this type of technology, organizations should consider the following critical criteria and select a solution that:

• Enables you to access and apply data quickly in near real-time
• Provides you with sufficient data granularity to report position at quarter-hour increments
• Is able to analyze supply/demand data in the context of trading and contract logic
• Allows business teams to adapt analytics and explore new data sources quickly and easily
• Creates output that can be audited and tracked to provide controls and
• Delivers value within 3 to 6 months

By leveraging this class of tool, it is possible to create a solution that is managed within the process analytics team or the mid-office. This eliminates the risk and expense of a large-scale IT implementation but does so without sacrificing the ability to convert these analytics into standing operational controls.

Moving Forward

It is easy to ignore solutions from other industries when attempting to expand analytic capability. Heads of trading and IT management often raise objections, believing that trading is too complex and that only companies steeped in trading and risk management can provide effective solutions. However, these objections do not stand up to investigation. In telecommunications, these solutions are already in use, maximizing revenue for billion dollar industries and working with millions of records across multiple systems. Simply put, experience in other verticals has shown that complex analytics can be implemented quickly and efficiently by leveraging solid technology and expertise in process, logic and data.

In order to successfully adapt solutions from other industries, organizations should take an approach based on quick timelines and minimal risk. Big-bang solutions should be avoided and more attention focused on small systems that address core parts of the risk reporting process along with existing solutions; the integration of generation data, analyzing complex data, etc. Proofs of concept should be used to confirm a technology's ability to perform, and proofs of value to test logic, data and analytics. By keeping initial timelines and investments short, organizations will maintain flexibility to mix and match technologies and avoid becoming trapped in a substandard solution. Finally, when investigating technologies, organizations should pay attention to the ease in which they can be integrated into existing architectures and data models. After all, even the most simple, elegant tool can result in a blown budget due to integration costs.

Market, industry and organizational pressure all suggest that organizations which successfully improve the accuracy and timeliness of their risk reporting stand to benefit from improved margin, greater controls and the ability to more quickly move in the market. New tools from outside energy trading can provide the needed functionality to quickly and cost-effectively create this expanded analytic capability for any trading desk. With a little technological planning, the future will be very bright not only in terms of profits but also in lowered risk.

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