Is RPA Set to Streamline Commodity Trading Processes?

In terms of looking at possibly disruptive technologies across the commodity trading and risk management space, another area of potential is in the area of robotic process automation (RPA). At first sight, RPA doesn’t appear to have garnered significant interest in the space, however, our research did yield blog articles by ION OpenLink and Pioneer on the topic, as well as short articles by some of the consulting firms. But what is RPA? Investopedia[1] defines it as follows (and other definitions are largely consistent with this).

Robotic process automation (RPA) refers to software that can be easily programmed to do basic tasks across applications just as human workers do. The software robot can be taught a workflow with multiple steps and applications, such as taking received forms, sending a receipt message, checking the form for completeness, filing the form in a folder and updating a spreadsheet with the name of the form, the date filed, and so on. RPA software is designed to reduce the burden of repetitive, simple tasks on employees.

The ION OpenLink blog[2] also visits the definition of RPA and how it may be used generally before exploring some possible applications within the energy and broader commodity trading business functions. It highlights the broader potential benefits of utilizing RPA as follows,

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The benefits of RPA are especially important for companies relying on legacy software applications, many of which cannot be configured to coordinate well with other applications, in large part because trained support is no longer offered for the programs. Oftentimes in these situations, users are required to manually migrate information from one application to another, which is time-consuming, error-prone and hence costly. RPA can automate such transfers.

ION OpenLink point to many areas within energy trading where the deployment of such technologies might have application including areas like financial settlement, scheduling, risk management, and analytics and notes that “most companies involved in energy trading — indeed, most companies in all industries — have yet to capture even a significant fraction of the potential benefits that RPA can generate. To date, there’s no proven path for implementing RPA enterprise-wide in an energy trading firm,” before providing some useful guidance on how to identify specific areas for deployment.

Pioneer has also not just looked at the area of RPA but actually have had some involvement with it. Its blog article[3] focuses on the point that before robots can be deployed, the business area must have been digitized. “While legacy C/ETRM system has significantly automated the end-to-end process from deal entry and risk management to settlement, they were not conceived with the back-office as the starting point. As a result, most C/ETRM systems only provide the ability to settle/invoice STANDARD trades/contracts. Consequently, complex billing of NON-standard contracts is done outside those C/ETRM systems through manual processes. This is evidently, a costly, error-prone, and inefficient approach. And, not surprising given the market conditions they are facing, this is now getting attention within commodity/energy trading organizations,” and ultimately point to the settlement area as one that is ripe for RPA.

Pioneer also released a press announcement in late 2017[4] to announce that it had joined forces with its longstanding customer Essent, in a POC to apply RPA to settlement processes in the Retail Energy Management group. “Innogy’s Essent is focusing strongly on digitization in the energy transition. For REM we accomplished that task with TRMTracker and its automation enables us to now apply RPA, gain experience with the concept, and prove the added value for Essent Finance”, said Pim Flink, Senior Controller at Essent. “This is pioneering work, and our results have been very promising in how it will increase our operational excellence.” A follow up call with Hugo Stappers of Pioneer reveals that this is now implemented and in production at Essent in the areas of generating a settlement report and running calculations where it saves a lot of manual work and makes the users very happy as they are freed up to work on more creative activities, he told us.

nPower Case Study

RPA then is a technology that can be used to automate repetitive, boring work by deploying bots to do what was done by humans and knowing the commodity trading world well, there does seem to be remarkable scope for its deployment as there are innumerable areas that fit that bill. RPA is also the technology that can be used to automate workflow and perhaps help manage an employees work day more effectively. Here the robots are used to help the user with prioritized to-do lists and then to automate the logging and out of the various systems that the user needs to work with in order to effectively complete their activities.

Perhaps RPA still sounds very futuristic but actually, it has already found application across the business and is likely to be increasingly be deployed over the next few years. One such application is also with Innogy SE “where Innogy needed a solution that would handle a low volume of highly complex processes characterized by compound steps, multiple variables and access to fragmented systems.”[5] nPower’s main driver was not to reduce headcount but to increase the speed and agility of process completion and had considered offshoring and outsourcing prior to looking at RPA.

To help determine what to automate, nPower looked for processes that were,

  • Relatively labor-intensive, repetitive and prone to human error,
  • Required access to multiple legacy systems, slowing down processing speed,
  • Followed set business rules,
  • Were often assigned as seasonal/temporary work, and
  • Had short lead times and fast payback for quick success.

It rapidly identified areas such as invoice statement generation, emergency contact detail communication, and missed contract renewals. In the area of invoice statement generation, nPower were obliged to provide customers with a contract end date and renewal details on all invoices from a certain date and, rather than hiring a large number of temporary staff, it used automation instead. According to the case study, the data needed was housed across more than 50 systems ranging from old legacy to custom solutions. The data required was extracted from all of these systems and placed in one consolidated repository and then Blue Prism software robots deployed to complete the 50-60 steps that each process required. The result was fairly impressive. Processing times reduced from 20-minutes to second, 21 fewer FTEs to perform the activity and elimination of the risk of breaching a regulatory deadline. The results in the other two areas were equally impressive but the overall results demonstrate why RPA is set to take off in the industry;

  • 10 software robots in the first-year deployed to automate 17 processes,
  • Saved the equivalent of 40 FTE’s,
  • 8% productivity increase across the entire service organization,
  • 60% increase in speed over manual processes
  • Elimination of risks.

The potential in Commodity Trading?

Anyone who has ever worked in a commodity trading organization or business unit knows that there are many examples of highly repetitive and labor-intensive areas that could benefit from automation and ION OpenLink’s article certainly focused on a number of high-level examples. In our opinion, the area is ripe for automation and the widespread use of software robots. We also asked Matt Barrett, CEO of Adaptive, for his thoughts and he pointed to desktop interoperability as one area where his firm is working towards implementing RPA for clients in the space. “To benefit it is critical that the relevant business areas are fully digital. We are doing a considerable amount of work at the moment with some key clients to increase the levels of digitization within various business areas. They are doing this by solving the interoperability problem that you touch on with old applications no longer able to be integrated via their UIs – the term for this is desktop interoperability. Once a set of applications can interoperate (interop) on the desktop, driven by a human operator, the next step is RPA, which can learn from human actions and augment their abilities,” he told me.

The application of RPA then first requires the business process first be digitized as argued by both Pioneer and Adaptive. By looking for those highly repetitive and labor-intensive areas of the business process, opportunities for RPA can be identified and acted upon. While this may include specific trade office business processes, it can also be used to automate application interoperability at the desktop and other such activities.







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