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Commodities: A Market Ripe for Digitization

Stan Guzik, Chief Technology & Innovation Officer, S&P Global Platts
Stan Guzik, Chief Technology & Innovation Officer, S&P Global Platts

Stan Guzik, Chief Technology & Innovation Officer, S&P Global Platts

It’s often impossible to think about science fiction without thinking of the future. After all, it’s not so much fiction as it is an apt (and sometimes uncanny) predictor of the technological advances that are to come. Take The Matrix, a 22-year-old film that is cited time and again for its references to virtual reality and artificial intelligence. While these are now considered ubiquitous innovations, in 1999, could most people really have imagined a reality of interconnected, intelligent machines that can speak to both humans and other machines?  

As it turns out, today’s world doesn’t look wildly different than the realities imagined and laid out in many works of science fiction, including The Matrix. With the availability of 5G broadband and the proliferation of sensors on physical objects, the digitization of the physical is well underway. These IoT devices are doing a lot more than collecting and sharing data; combined with cloud computing and AI algorithms connected by APIs, a global network of smart computing is seeing rapid growth. These physical assets essentially have a heartbeat and a brain enabling them to communicate with humans and with each other.

While digitization has permeated virtually all industries over the years, including the financial markets (and especially the equity market), the commodities market has lagged behind in embracing digitization.  One reason for this is that physical commodities like Oil and LNG (Liquefied Natural Gas) are traded on the spot market, which is very different from trading equities on the secondary markets. In the spot market, you are trading large volumes of a physical commodity that needs to be financed, insured, stored, transported and received. As such, there is inherent pricing volatility and risk across the commodity supply chain.

  With the availability of 5G broadband and the proliferation of sensors on physical objects, the digitization of the physical is well underway 

S&P Global Platts has long seen a ripe opportunity to digitize the physical and analog commodities sector – and build out the commodities matrix, so to speak. We, like others, have been hot on the trail. For example, it was 14 years ago that collaboration with Intercontinental Exchange, brought about digitalization of spot market trading information with the Editorial Window (eWindow) communications tool for our Market-on-Close (MOC) price assessment process in physical oil markets. Today, advanced data visualizations of real-time bids, offers and trades data comes to life, through technologies available through such companies as Kensho. Thus, market participants can now watch spot market trading activity as if they’re watching actions unfold in a video game. By being exposed to this data in real time with visualizations, market participants are able to make better-informed trading decisions as they see the live interactions between buyers and sellers via conversion charts.

Data processing is another area that’s benefitted from digitization. Gone are the archaic days of batch processing and FTP data feeds that could take hours or days before the data is made available and shared; this type of data processing and sharing dates back to the days of the 28.8 modem. Today with data streaming technology, data is processed and shared on the wire, and we are well on our way in creating taxonomies, ontologies and knowledge graphs for the commodity markets. This allows for intelligently tagging all datasets, which now makes them intelligent and gives them meaning to customers. This intelligent data is delivered in real time to machines via Machine-to-Machine Delivery platforms, as well as to people via Web and Mobile platforms. In the never-ending search for alpha, AI and machine learning algorithms process this data to provide market participants with actionable data as it happens.

Although the commodities world is increasingly becoming digital, there is a natural technology adoption lag that occurs as market participants need to evolve their systems to take advantage of intelligent information and act in real time. We saw an example of this need last April when the NYMEX WTI Crude Oil benchmark was trading at negative $37 dollars per barrel, which meant sellers were paying buyers to take their oil.

These negative oil prices were a result of oversupply and a lack of space at Cushing, Oklahoma, to store the oil at the futures contract expiry – and on top of this, there was severely decreased demand due to the COVID-19 pandemic. Since then, there have been widespread calls for an alternative to the Cushing based benchmark.

Matters were further complicated with many market participants relying on legacy analog systems that require significant investment in order to consume real-time commodity data and to turn this data into actionable insight with machine learning and AI.

Taking heed are companies, like us, that track global commodity supply and demand, storage capacity, refining capacity and transportation of commodities. Every day, this data is now being digitized and made available via APIs to market participants so they have the data at their fingertips and are able to make decisions with conviction.

Unlike Keanu Reeves in The Matrix, as the commodity matrix evolves and the analog world rapidly heads toward obsolescence, market participants need the matrix to survive. Technological evolution is inevitable as the physical and digital realms continue to merge. As a result, market participants will need to invest in building or buying machines that consume APIs in order to apply machine learning and AI to more effectively navigate these volatile and changing commodities markets. With access to trusted real-time data and the technology platforms to turn that data into action, market participants will be well positioned to not just survive, but thrive, in the commodity matrix.

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