In the modern trading world, there’s new data constantly available. Traditional energy trading and risk management (ETRM) systems take time—usually overnight—to ingest and process data to produce key output for risk control, including position, exposure, and more advanced risk measures. IT investments have allowed some companies to enable real-time risk analytics, but with scalable computing power increasingly available on-premises and in the cloud, “real-time” analytics for energy trading and risk control is becoming a reality for more organizations.
But what is “real-time”? Real-time reporting is the ability to gather, capture, calculate and report every change in data as it happens for analysis. However, there’s a balance between value and cost necessary to fit an organization’s needs. Development and support costs start to increase dramatically as the time interval for updates shrinks. In most cases, having a near-time analytics approach produced at defined intervals will provide equivalent value as true real-time. These time intervals could be defined as minutes or hours, but nonetheless, result in a more valuable analytics capability as compared to traditional end-of-day reporting.
Traders will always want to see positions and exposures with the most up-to-date market and operational information to find opportunities in the market. Risk control needs to keep pace with trading to ensure that the organization is adhering to the trading policy, and sometimes a day later is too late for limit monitoring and other control processes. To encourage ETRM utilization and drive innovation, the solution must be able to deliver what users are currently doing within (and in many cases outside) the ETRM. This enablement isn’t easy and requires high synchronization between ETRM configuration teams, commercial decision-makers, and risk control.
Traders and risk control can have different perspectives on data assessment. Risk control has a requirement for a clean end-of-day and often needs to follow up with the rest of the organization to finalize that clean view of the day prior. Some portfolios will have frequent notional amount changes while others may be highly impacted by price or implied volatility changes. Understanding portfolio contents and sequencing portfolios will help prioritize candidates for near-time reporting earlier in the deployment and adoption lifecycle.
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Exposures
Limit Effectiveness
Just because you can, doesn’t mean you should—balancing the value and cost of real-time analytics requires coordination between the business and IT.
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Even in areas where real-time data is available, there can be a range of questions for the business to answer, such as:
When developing these advanced analytics, both risk and IT teams need to align on update intervals that will drive value, and what’s possible to deliver based on the business process and underlying technical capability. In many cases, risk control can provide examples of what they want to see as a result, but that doesn’t necessarily reflect all the business rules needed to transform the data into the desired output. Business and IT groups will need to work together to identify and document those rules, so they’re implemented correctly and clearly understood.
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The right update interval for each organization will depend on those considerations and benefits. For a group that typically trades a small number of large cargoes, batches, and ratable volumes, intraday reporting every two hours with increased update frequency near market close(s) may be sufficient. In a group that does a high number of trades with wider variation in traded volume based upon market conditions, an hourly update may fit the need better to keep up with the changing positions. In both cases, the business (trading and risk) will need some way to trigger a manual update because regardless of the analysis to determine the “right” interval there will always be exceptions.
In addition, if the expectations of real-time can’t be met in the current business and technical environment, the organization will need to work together to understand the bottlenecks. Sometimes they are technical and lie in optimizing analytic models, visualization of data to the user, or reducing network latency. Sometimes they lie in the business process for data entry or workflow approvals. Either way, the organization will need to work together to develop a business case for de-bottlenecking the analytics.
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During the development of a real-time position and exposure analytics capability, all stakeholders (business and IT) need to understand that it will be a marathon and not a sprint. The quickest path to delivering value to the business (i.e., a minimum viable product) will likely not meet all the business needs. The organization needs to align expectations with the budget and timeline. As it relates to real-time analytics, two adages will apply: don’t expect a Cadillac on a Pinto budget, and Rome wasn’t built in a day. However, with a thoughtful approach to delivery and principled design methodologies that include data, technology, and business process, the benefits of real-time analytics can be achieved.
Real-time position and exposure reporting sounds great and can deliver real value, but risk organizations need to be aligned on the requirements and limitations before heading down a potentially costly path. Deep experience working with trading and risk organizations, understanding the core processes, and developing technology capabilities to meet those needs are keys to long-term success. Opportune’s energy professionals have extensive experience in developing and delivering real-time solutions that fit unique client needs.
When you choose Opportune, you gain access to seasoned professionals who not only listen to your needs, but who will work hand in hand with you to achieve established goals. With a sense of urgency and a can-do mindset, we focus on taking the steps necessary to create a higher impact and achieve maximum results for your organization.
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