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The Hidden Challenge Lurking Beneath Energy Trading’s Bumper Profits

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By Ami Katschinski, CEO and co-founder, Sphere.

Sky-high trading profits earlier this year reignited the age-old debate of how, during market turbulence, some energy firms emerge as victors while others find themselves on the loss-making side of the trade. Geopolitical conflict has, and always will, create a frenzy of noise and opportunity for massive profits.

Unfortunately, the noise is getting louder and subsequently distracting from a more fundamental question of how exactly energy traders and brokers create a lasting competitive edge when prices are not so volatile.

Trading, though, is at the heart of the energy industry. Behind all the hype and hyperbole around oil prices following crude falling back to the low $90s per barrel and then up again this week, sits a plethora of trading activity that shapes how commodities move around the world.  For large commodity trading houses, producing and transporting energy often overshadows the trading side of their business, but their ability to understand markets often separates success from failure. Yet despite the importance of trading, much of the infrastructure supporting it remains fragmented.

Broker networks have liquidity scattered all over the place; price discovery workflows are still largely traditional and involve copious amounts of voice conversations going on, and that’s all before someone tries to unravel all the dialogue across the various chat messaging platforms everyone now uses. The unintended consequence is that valuable insights are sitting everywhere and nowhere at once. Traders and brokers may be generating intelligence constantly, but it is no good if these insights remain stuck inside workflows that were never designed to be connected with one another.

Let’s be very clear though, these workflows exist for very good reasons and have evolved over many years. Voice markets remain because relationships, judgement and expertise still matter. The real problem though is that energy markets have become more complicated and the tools available to understand them have simply not kept pace.

Over the decades, the prevailing response has been to try to alter behaviour. A huge amount of effort has gone into things like moving trading activity onto centralised platforms, standardising processes, and in some cases even encouraging traders to work differently. While this has sometimes worked, more often than not it has struggled because markets rarely conform neatly to the assumptions built into technology.

Until now, everyone has been trying to build tech that practically rejects the accepted reality of how energy markets function. However, rather than forcing market participants into new workflows, a more pragmatic approach would be to tap into the information already flowing through existing processes. After all, surely trying to enhance trading behaviour is better than trying to replace it?

This is where artificial intelligence (AI) has the potential to move this longstanding debate in a more meaningful direction. Today, most AI discourse focuses on doing more with fewer people. Far less attention is given to how AI can help firms empower their people with new capabilities: tools that adapt to their workflows, give them a genuine competitive edge, and expand the overall market.

There is no logical reason for some of the most valuable energy market intelligence to reside inside chats and sporadic phone conversations. We live in a world where insights can be organised and raised in ways that support more informed trading decisions without relying on synthetic intelligence. This is about empowering people to become more effective at the jobs because they are better informed.

Sporadic bouts of extreme price volatility will always be part of global energy markets. But longer term sustainable advantages are rarely built on extraordinary events. The firms that gain the greatest edge in the years ahead may not be those with the largest trading books. They may simply be the ones that are best able to unlock the intelligence already sitting within their organisations.

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