Data analytics set to fuel change in the oil market

Privileged data insight is no longer the sole preserve of the world’s oil conglomerates. Access to insightful analytics is providing a new competitive edge for smaller and mid-sized commercial and trading firms in the oil market, helping them navigate Covid-19-related volatility, carry out forward-looking analysis on products and prices and make better-informed decisions

Data analytics proved a valuable commodity for firms in the oil industry during volatility caused by the Covid-19 pandemic, and is becoming indispensable in the post-pandemic world as market conditions change.

The sudden drop in oil demand from April 2020 following worldwide lockdowns was largely driven by the sharp fall in transportation fuel consumption, from 100% to near zero. The result was extreme volatility in the oil market, with the US taking the unprecedented step of settling prices in negative values.

Large oil companies were forced to change their strategies, with Shell putting up seven of its 17 refineries for sale or shutting them down. BP shut its largest refinery in Australia with a capacity of 146,000 barrels per day.

Other longer-term factors are also prompting fundamental shifts in business operations. In China, three large private oil refiners diversified their businesses away from conventional refined products, such as diesel and petrochemical, largely due to the focus on climate change and the increasing use of electric vehicles.

“Covid-19 accelerated the change in strategy for these companies, but the market could have foreseen the disruption had the underlying data been carefully studied,” says Yan Chong Yaw, director of Refinitiv Oil Research in Asia, part of Refinitiv’s commodities research division.

For oil trading companies that take positions on future oil prices, changes in fundamentals are vital, he explains. As an example, a sudden increase in the number of vessels going into consuming countries such as China indicates that something has changed and why it has changed, Yaw says.

But obtaining fundamental data has always been a challenge for smaller trading firms, which do not have the luxury of support seen in large oil companies. They have to rely on their network of contacts to obtain such data, according to Yaw. The major oil companies often have their own global trading systems with vessel-tracking capabilities and teams of analysts to study the data and recommend trades to traders.

“We have combined vessel-level information with cargo-level information, including what is inside the cargo, what products are in the cargo and what grade of products are inside the vessels. That information replaces market sources, and we provide market analysis for the entire process,” Yaw says.

Large volumes of data

The availability of large volumes of data in the market has also contributed to the widespread use of data analytics in the commodities world, particularly in the global supply chain network, says Raj Melvani, sales director, corporates and commodities, Asia, at Refinitiv Singapore. Vessels, for example, are one area in which data volumes have increased exponentially, covering positioning information, contents and capacity.

Congestion analytics are now in great demand, particularly from oil traders that need to manage short-term supply-demand analytics for their trading positions, he adds.

Data analytics: a competitive edge

For Singapore-based oil trading company Rex Commodities, a wholly owned subsidiary of Century Commodities Solutions and one of the larger coal traders in China and the region, data analytics has played an important role in its foray into the oil trading space. Set up in 2020 in the thick of the Covid-19 pandemic, Rex relied on data analytics to provide a competitive edge in oil trading at a time when many companies were making an exit amid global lockdowns.

“The business in China was thriving towards the end of last year until early this year, despite the lockdowns in many countries,” says Tommy Wong, deputy general manager of Rex’s energy trading desk. That created enormous trading opportunities for the company.

“We were able to plug the gap between the lack of demand outside of China versus the very strong demand in China.”

Increasing market transparency

A long-time user of Refinitiv platforms, Wong says one of the key benefits is the transparency it brings to the market by allowing traders to see what they could not previously. For instance, information previously accessible only through relationship trading can now be obtained at the click of a button.

“It is no longer asymmetric information, especially for the oil market right now. It’s very hard to find something you think you know that nobody else knows,” Wong says. “All the major oil companies know that, if you do not have the analytics right now, you are at a disadvantage. It is no longer a competitive edge, it is a prerequisite. You need it to survive.”

Refinitiv’s services have also helped traders see where oil is moving around the world, according to Wong.

“It makes the world a smaller place. That’s probably bad for traders because we thrive on information. With the platform, everything is there. All I need to do is go to the trade views, select the product, and I can see what goods were loaded today, yesterday and the day before, or even two months earlier,” he says.

Remote access

Border closures and travel restrictions imposed at the peak of the pandemic created difficulties for oil traders who travel frequently for business development and to obtain market information. For Rex, that also slowed down its business activity considerably, but the Refinitiv platform and services have been able to plug the gap by offering the necessary data and information.

“The sheer size and coverage of various markets [is useful] because we don’t have people on the ground. Refinitiv data has allowed us to have some kind of insight into the market depth, which is helpful in our trading,” Wong says.

Wong and his team also relied on ship tracking and trade flow data to help them understand oil-flow patterns, as well as keeping track of new tenders coming to the market and those the company may have lost.

“This data is well covered on the platform. We use it quite diligently as our backbone in terms of tracking where the oil companies are moving the oil,” he says.

Rex also uses analytics to forecast the market for the following year. This helps the firm make better-informed decisions as to whether the market is going to be healthy, what kind of oil they should buy or sell and at what price.

Big data and AI

According to Wong, the growing importance of big data can be seen in the way major trading houses are hiring data scientists to write code to run the fundamental numbers available on many platforms.

“A lot of companies are trying to extract what the human mind is thinking into a code and use all these analysed numbers, be it from Refinitiv or other data providers, to form an institutionalised, proprietary view, which they can use to forecast the market, among other things, which is very important. The key motivation is not to build an artificial intelligence (AI), but more a war chest that can be accumulated over the years that is not dependent on traders,” Wong says.

Increasingly, trading firms are experimenting with big data and AI to carry out forward-looking analysis, such as predicting the price of crude oil and products, and oil complexes in general. This is an emerging trend that is changing the game for commercial and trading firms, says Melvani. But predictive analysis cannot be performed without first having the underlying data, which includes supply chain and digitised data, and putting it into a data lake so it can be used on a real-time basis from as many sources as possible.

While the biggest oil firms have made great strides in turning big data into usable data, it is much harder for the commodities industry to get this right, he adds.

“It is not just prices you are looking at, you are also looking at supply, demand and the supply chain. Compared to other financial asset classes, commodities is far more complex to bring all together in an AI decision-making tool. It’s going to take some time, but everyone knows that’s where this market is going. Everyone is starting to lay the foundation[s],” he explains.

Alternative data in the cloud

The availability of alternative data such as that derived from satellite imagery and digitised data is another important emerging trend, according to Melvani. Alternative data includes data on vessel tracking and storage, which is particularly important for the global supply chain and in helping the industry make decisions through the use of data analytics, he says.

Cloud computing – which has made it easier for the smaller trading firms to manage their costs, including IT infrastructure and management of spreadsheets – has made smaller to mid-sized trading firms more open to adopting data-driven insights, Melvani adds. Until about five years ago, there were barriers to having sufficient computing power to ingest all the new data and, even if data was available, the mid-sized trading firms were reluctant to invest in 100 servers or hire large teams of data scientists.

“Cloud computing has helped commercial and trading firms that have never invested in such technology in the past accelerate the roll-out of digital solutions,” Melvani says.

The affordability of computing power has not only augmented the power of data analytics, making it widely accessible to market players in the oil sector, but also made it a vital tool in times of challenging market conditions such as the pandemic. As the need for comprehensive, quality data increases, and as market conditions evolve, data analytics will offer oil market players the much-needed competitive edge and a critical tool for their survival.

 

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