Energy firms revisit CTRM systems as tech advances

Rapid advances in commodities technology over the past three to four years have led growing numbers of energy firms to re-evaluate their commodity trading and risk management (CTRM) software set-up. 

New technologies, and in particular artificial intelligence, are now being routinely leveraged by software developers and energy firms to solve some of the specific pain points encountered by firms that produce, sell and trade energy. AI-powered workflow automation is replacing time-consuming manual processes, while AI-powered data and analytics are tracking global supply and demand. From algorithms that deliver market-moving news, to automated hedging contracts that execute when prices reach pre-defined levels, energy executives are keen to tap into the explosion of new tech offerings entering the commodity space.

Working out which products to use, which functionalities to target first and how best to incorporate it all into the CTRM ecosystem is not easy, and every decision is likely to involve a trade-off. In fact, many firms, especially larger ones with legacy systems, face something of a catch-22 situation. The traditional CTRM systems developed 15 to 20 years ago were not built with today’s modern architecture in mind and are not able to leverage it in the same way as newer fintech offerings. As a result, many firms are considering ‘upgrading’ by implementing best-of-breed products around the CTRM that provide enhanced functionality in certain market segments.    

However, it’s not always easy to connect these stand-alone products to the core CTRM. In fact, many energy firms are hitting a roadblock not just in connecting applications to the CTRM, but in setting up a data flow that allows AI-powered products to work properly. Without good data, AI is limited in what it can do. 

For firms with strong growth plans that want to be able to support expansion plans, sticking with a legacy CTRM system and building around it could be the best option

Therefore, some firms are considering whether to replace legacy CTRM systems with ones built on modern architecture. However, most of the newer systems lack the enormous breadth of functionality of the large, well-established CTRM systems, leaving energy companies with a tricky decision – either they move to a new, modern system, sacrifice functionality and do workarounds where needed, or stay with a legacy system and build new capabilities around it based on advanced technologies and AI.

The decision will be heavily influenced by budget but should also be dictated by wider strategy and involve good communication between the risk team and the chief technology officer. Crucially, any systems review should start with a clear understanding of a firm’s business needs and future business growth plans to ensure that systems can scale where needed.

For firms with strong growth plans that want to be able to support expansion plans, sticking with a legacy CTRM system and building around it could be the best option, while for firms that operate in only a handful of markets, the preference might be choosing a modern system that’s easy to install and cheaper.

Increasingly, firms are experimenting, running small proof-of-concept projects on the side of their existing systems to test the potential of modernising particular functionalities. However, working tactically, one function at a time, has its pitfalls, a major one being that it is less likely to result in a system that can scale in the future.

Carrying out a review of systems holistically, provides huge benefits. An implementation specialist that is vendor-agnostic and has experience across a gamut of different providers, can add a lot of value here. In terms of the wider business plan they will be a neutral presence with no internal biases, able to challenge assumptions, highlight blind spots and keep the focus on outcomes rather than preferences or promises. In terms of the systems review, they will be able to help firms identify capability gaps and also have the knowledge to point to the right software product for each challenge, giving insight into the limitations of products, which vendors are unlikely to highlight.

The final target of any CTRM system should be to create the flexibility needed to operate in the dynamic energy sector where operations and prices can be affected overnight by unpredictable events, such as severe weather, geopolitical upheaval and regulatory changes.

Additionally, while the CTRM system may be the core component, firms need to consider the entire ecosystem around it. What complementary products may be needed to achieve flexibility in the future? For example, a firm might choose to implement a traditional CTRM system but knows it has very complex risk models that will need to operate outside the CTRM system. If this has been identified up front, it gives some extra flexibility around CTRM system selection as the core CTRM won’t need to have complex risk modelling functionality.

Similarly, when considering where to use AI, rather than thinking about single use cases, it’s far better to establish a clear idea at the start as to what needs to be achieved by AI across the business. Then firms can look at how this will affect their systems and what will need to be put in place around the CTRM to make sure data can be leveraged from all systems.

Carrying out regular reviews before a firm reaches the point that its IT infrastructure is creaking is good practice. It doesn’t need to be a long process, but it’s better to do it before something crops up and needs to be addressed in haste

Yefreed Ditta

Once the data is available, the potential for AI is huge, but almost certainly some additional work will be needed around the CTRM to enable the functionality to work. For example, several firms have now implemented some AI-powered automation around credit processes, such as carrying out credit checks and onboarding clients. Thought needs to be given not only to where the information is stored but to what happens, for example, once the credit letter is approved. Who needs to know, which different systems does it need to flag up in? Just analysing the one credit functionality is not enough. Firms need to think through the life cycle of the function and use additional workflow tools to support follow-up operations. 

The upfront work can be onerous. Value Creed recently supported a global energy trading company that expanded into European power and gas and found that its new trading activities couldn’t be managed satisfactorily with its existing systems and manual workflows. Dependence on spreadsheets created data inconsistencies and limited real-time risk visibility, while decision-making slowed as volumes increased. At the same time, rising regulatory requirements and an inflexible technology landscape made it difficult to scale efficiently.

Value Creed carried out a huge amount of upfront business and system assessment advisory, before a full vendor selection process was put in place. This involved 14 cross-functional workshops, evaluating and shortlisting three vendors and validating 12 end-to-end business scenarios. The scenarios pertained to real-world examples and covered, for instance, everything required to buy gas in the Netherlands and deliver it in Italy. This scenario considered all the transactions needed, the counterparties, invoices, scheduling requirements, expected PnL and so on. The vendors could then show how those scenarios would run on their systems.

Security concerns

Another major influence on systems selection is cyber security. While the fast pace of change in energy markets – high volatility, rising geopolitical risk, frequent regulatory change – build the case for modernising CTRMs and using increased AI, the energy business itself tends to move slowly when it comes to technology. Traditionally, risk-averse industry management will prefer to sacrifice technology advances and speed for security. This could slow the process of system selection, especially around software-as-a-service where firms effectively give their data to tech vendors, so extra checks may be required.

The rise of systems reviews being triggered by advances in technology is encouraging. Historically, reviews of CTRM systems were usually triggered by major problems with the system, or a change of events, such as a firm moving into new markets. Carrying out regular reviews before a firm reaches the point that its IT infrastructure is creaking is good practice. It doesn’t need to be a long process, but it’s better to do it before something crops up and needs to be addressed in haste.

Underpinning every review should be a clear understanding of the company’s future business goals so that, even when things do crop up that need to be addressed tactically, this can be done in a way that achieves the wider strategic goal.