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A combination of human skill and AI-powered tools will likely be in store for years to come when it comes to achieving the best outcomes in freight trading, finds Mads Frank Markussen, the head of research and market intelligence at Danish shipowner and freight trader Navi Merchants, part of Copenhagen Merchants Group. The industry has been exploring AI-driven models to generate trade recommendations, and while their effectiveness can vary widely, AI's current limitations shouldn't overshadow the fact that humans also have their limitations. The freight trading sector is undergoing a transformative shift, driven by technological advancements. The role of digital platforms and machine learning is not just to automate tasks, Markussen points out, but to enrich the strategic toolkit of traders. “The metaphor I like to use,” he says, “is that what we are witnessing is the ‘Deep Blue’ moment from chess where Garry Kasparov was beaten, and machine stood triumphant. However, this is not chess with set fixed rules, so I do not think we should pit man versus machine, but focus on how amazing it would be if we could get DeepBlue and Kasparov to work together - could they beat a Magnus Carlsen?” It's crucial to acknowledge the limitations of current AI models in handling complex, real-world scenarios While top traders excel, not every freight trader consistently makes profits, Markussen tells Splash Extra but notes that given the inelastic price nature of ships pricing models often break down – performing better in market regimes with low volatility. The days of low volatility lie behind us, Markussen claims, geopolitics, higher oil prices and regulation will translate into more volatility than in the five years the industry had leading up to covid. Markussen, who has worked as a freight trader for 10 years, with stints at Norden and Louis Dreyfus in Switzerland, reckons man is still ahead of machines and does not expect that to change for the best traders; however, although probabilistic, machine learning has excelled much better at certain things than every trader relying on the rule of thumb. “When thinking about freight, we need to keep in mind it is a transportation service and not just a trading game, costing millions of dollars to move stuff for many months from one end of the world to another,” he says, adding: "Machine learning works well with physical problems and there are many successful use cases, such as prediction of a vessels fuel consumption based on its design, engine type and weather. Prediction of lost time at sea. Prediction of anticipated weather delays in cargo operations. Prediction of port costs." Markussen is also on the board of a software company called CM Navigator, where a team of experts, including programmers, economists and mathematicians is building a one-stop shop for price discovery and market intelligence within freight and grain markets. “We realised that advantages in computing technology meant that what had previously been done by hand could now be done exponentially faster by computers,” he explains. CM Navigator started as an internal tool within the Copenhagen Merchants Group to service its grain brokers and biomass traders and evolved into a subscription platform with supply and demand analysis, trade flows, physical prices, and dry bulk freight rates. Its freight calculator runs 360,000 freight rates, updated daily, comprising about 30,000 voyages 12 months forward as part of a larger ecosystem that includes Copenhagen Merchants and Navi Merchants feeding data into the algorithms. “The magic though is really in what we can do that no one else can: As we are physically present in both freight and grain markets day to day, we can also feed the machine with what is actually happening in the spot markets,” he claims. In terms of how this impacts freight traders, Markussen points out that the tool is built for commodity traders – but that he doesn’t expect the machines to take over any freight trader’s job any time soon. “It's crucial to acknowledge the limitations of current AI models in handling complex, real-world scenarios, such as the unpredictable elements of ship fixing in spot markets,” Markussen advises. In general, the Dane views technology as an enabler, which will help the best traders up their game in the trading world “from being right six out of 10 times to seven out of 10 times”. Where AI could make a significant impact on market dynamics will probably be in the impact of the speed the markets will be able to react to disruptive events where sudden opportunities appear. Such opportunities will be caught much faster than today for those who can monitor and analyse the world market movements, weather patterns and geopolitical events. Markussen finds that as the future landscape of freight trading is rapidly evolving, a new type of talent in the sector is needed to be able to synthesise all the information coming at them into trading strategies. For him, this will require the usual skillset with strong analytical and mathematical skills, legal understanding and negotiation skills. But it will also require the capacity to analyse complex data, utilise sophisticated analytical tools, and make strategic decisions. “In essence, the advancement of the freight trading sector will demand a blend of technical knowledge, analytical prowess, and soft skills. Talent who can synergise these abilities, adapting to and driving forward the digital transformation of the industry, will thrive in the coming years,” Markussen concludes.

Shipping’s Deep Blue moment?

Can human beings keep up with computers when calculating freight rates? Mads Frank Markussen, head of research at Danish shipowner and freight trader Navi Merchants, has some strong opinions on the matter

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