We have been in the era of big data for many years, but the value of shipping data is underestimated, and its true value is not only in shipping itself.
Usually, container shipping costs account for less than 1% of the value of the goods, while crude oil shipping costs about 3% of the value of the goods. Even for relatively low value dry bulk cargo, shipping costs are often lower than 10% of its value, which leads to trade owners being more willing to pay for the value brought by the data than shipping owners.
At present, the practical use of many shipping data is limited to the narrow field of shipping logistics. However, the application value that can be extracted from shipping data should be more embedded in the international business and trade served by shipping, and even in the financial services provided for international business and trade.

Shipping data has strong financial attributes

Shipping data covers a wide range, with the core being the three main entities of "ships, ports, and cargo". "Ship" refers to the information throughout the entire lifecycle of a ship, including design, construction, operation, trading, maintenance, supply, and dismantling, as well as information on ship navigation, navigation, engine room, and cargo carrying, all of which are included in shipping data; "Port" refers to data related to port operations, port services, collection and distribution, maritime transportation, etc., all of which are included in the scope of shipping data; "Cargo" refers to shipping data that runs through the international logistics chain along with goods, including operational status, spatial positioning, and cargo sensing information in various stages of end-to-end transportation of goods (or containers). It is an important component of the international logistics and supply chain information chain.
Shipping data naturally has strong financial attributes. Due to the huge amount of goods involved in international trade and the enormous value of ship assets, the information on large assets, bulk trade commodities, and industrial economic development contained in shipping data has great application value in the international financial and economic fields. Overall, the financial uses of shipping data mainly include the following aspects:
Shipping data is associated with large-scale financial settlement and insurance services for international commercial activities. In international trade activities, the delivery of goods is often based on different trade terms. Under different trade terms, the proportion and timing of fund payments are closely related to the progress of goods delivery, so whether it is trade payment or freight settlement, tracking data and relevant credentials of the goods are required for confirmation and verification. However, with a huge volume of sea freight, in addition to normal trade payments, the transportation insurance and vehicle insurance of goods are also closely related. When it comes to maritime claims and rescue, it is even more necessary to conduct a detailed evaluation of the value of the ship and the value of the goods. These insurances and claims require a large amount of shipping data support.
Shipping data is related to the spot and futures investment transactions of important bulk commodities. The large-scale and large-scale transportation of ships means that more spot goods will float on the ocean for a long time. And the arrival of these spot goods will directly affect the spot volume of a certain type of goods at the destination port, causing significant fluctuations in local market spot prices. The subsequent planned arrival of goods will also have a huge impact on the futures prices of local commodities. Therefore, many commodity futures investment analyses (such as crude oil, grain, iron ore, etc.) and industrial investment analyses (such as power industry, metallurgical industry, construction industry, etc.) are closely related to shipping data. Shipping data is even used in quantitative trading models of hedge funds.
Shipping data involves significant asset financing and asset lease price derivative finance. Shipping data is almost always linked to assets, especially ships and containers, which have established the position of shipping as a heavy asset industry. Ships belong to significant assets with a service life of over 30 years, and their new construction and second-hand transactions require financial support services; In addition, although the lifespan of containers is only 10 years, the quantity is extremely large and the degree of standardization is high. China's annual container production is maintained at over 100 million cubic meters, and the demand for financial services is also enormous. Therefore, there is a large demand for financing around the construction or purchase of heavy assets in the shipping industry, and ships, port machinery, and others are heavily using financing leasing services.
In addition, the index of ship rent and freight can also be used for futures derivative trading in corresponding markets, with the well-known FFA bulk carrier forward lease trading launched by the Baltic Exchange.
Shipping data includes information on the logistics process and property rights of goods. The impact on supply chain financial services is enormous. An important foundation of supply chain financial services is effective cargo control, and ships, docks, trucks, and warehouses are all nodes for property rights implementation, creating convenience for effective cargo control. The full process visualization of cargo transportation has been an important task in the digital transformation of shipping in recent years. These cargo tracking data have played a crucial role in financial institutions controlling cargo and evaluating the credit of financiers. For example, by verifying the weighing and transportation data of cargo loading and unloading ships, the bulk cargo stored in the yard can also effectively avoid "duplicate pledge". With the widespread legislative recognition of the "property rights" represented by electronic bills of lading, more financing services around freight and payment will become more mature.

International service providers seize the opportunity

It is precisely because of the high value of shipping data that it has become the object of competition for international business giants, and many international shipping data service providers have obvious first-hand advantages in this field. Global shipping, trade, and financial data giants, as well as global ship satellite trajectory data giants, have emerged one after another; Clarksons, the world's largest ship broker, has also attracted more capital attention, with Franklin Templeton from JPMorgan Chase, Bank of New York, and Citibank becoming the main investors in Clarksons.
In December 2020, S&P Global, a large financial data provider, acquired IHS Markit, a data analysis company in the shipping and trade sector, for $44 billion, making it the world's largest commercial acquisition of the year. S&P's acquisition of IHS Markit can unleash greater data synergy and further expand its advantages in areas such as financial information and services, ratings, indices, commodities and energy, transportation, and engineering. For example, IHS Markit provides global tracking data for tanker shipping, port inventory data, and trade logistics data, which will further enhance the accuracy and credibility of S&P's global Platts energy information, especially in the discourse power of financial derivatives markets such as credit default swaps (CDS) and collateralized debt obligations (CDO). S&P has become a global data giant in shipping, trade, and finance.
On September 14, 2021, less than a month after landing on NASDAQ, commercial aerospace company Spire announced the acquisition of Canadian company ExactEarth for a total price of $160 million. This acquisition completely changed the competitive landscape of commercial satellite AIS data service providers. After the merger, although the company did not completely monopolize the field, its satellite quantity and AIS data quality completely surpassed its competitor, Orbital Communications Company (ORBCOMM). According to Speer's estimation, this acquisition will increase 75% of customers, including over 150 new government and enterprise customers in 39 countries. The emergence of a global dominant enterprise in ship satellite trajectory data.
In addition, the Global Ship Asset Appraisal Leadership Platform has also been acquired. On April 11, 2023, Veson, a digital solutions provider for the US shipping industry, announced the acquisition of VesselsValue (VV), a globally renowned online ship valuation and shipping data service provider headquartered in the UK. VV has access to a database of over 81500 ships, and its ship valuation services are renowned in the shipping industry and serve as a benchmark in the ship trading market. Veson is committed to providing maritime freight management solutions, including maritime contract management, ship information management, and data analysis services. Previously, the company successfully acquired Oceanbolt, a commodity and maritime market information platform, as well as Q88, a well-known information management and software platform in the oil tanker industry.
European and American countries have taken the lead in the field of shipping data, and China's basic work on shipping data, as well as application research and financial innovation, require us to build it with a down-to-earth approach.

Quickly build a good ecosystem for China's shipping data

Facing the fierce competition in global shipping data, relying solely on the strength of China's shipping and port industries is difficult to build a good ecosystem for China's shipping data. China's energy, financial, and trade enterprises should also deeply realize the crucial role of air superiority in shipping data in participating in international economic and trade. Therefore, the author suggests:
Firstly, we need to accelerate the integration of financial demand and shipping data, forming a joint force to promote related applications. The port and shipping industry should engage in sufficient exchanges and explorations with the financial and industrial sectors on how shipping data can empower financing leasing, bulk futures quantitative trading, stock quantitative trading (profit freight capacity turnover), supply chain finance, insurance product design, shipping freight derivative trading, and actively promote the establishment of relevant innovative consortia and the research and development of related applications.
Secondly, China's capital should quickly lay out the shipping data industry. Focusing on energy, media, exchanges, securities firms, and investment banks, it is necessary to plan the acquisition of domestic and foreign data firm assets. For example, refer to the acquisition of research firm Refinitiv by the London Stock Exchange Group Plc. At the same time, various industries should increase their cultivation and support for local data service providers. For example, "My Steel Network" started with steel trading and has now become an important data service provider for global iron ore trade.
Thirdly, establish China's own big data platform in the field of commercial supply chain. Against the backdrop of the global data industry's widespread adoption of resource acquisition and integration, as a manufacturing powerhouse, China needs to integrate supply chain logistics data serving various industries on a unified platform, provide public basic services, and build a "China Digital Technology Group". But this platform is just a digital base, and more application scenarios need to be fully utilized to provide innovative vitality and fully explore the value hidden behind the data.
Fourthly, improve the commercial application of shipping data in China. The value extraction of data requires the support of rules and ecology. If data is not collected, cleaned, desensitized, stored, transmitted, traded or shared according to standards, the value it can create will inevitably be limited. Only by establishing standard rules and a business ecosystem for data can the true value of data be discovered. The establishment of the Shanghai Data Exchange has brought new hope for the new commercial application of data in China. It is necessary to actively establish relevant data trading platforms to promote the circulation of data elements, release digital dividends, and promote data development, attracting more market entities to participate.
Fifth, accelerate the construction of China's shipping data standard system. To completely transform passivity into initiative, it is necessary to change the existing standard formulation model, systematically and proactively design the standard system for shipping data, adopt a model of first formulating standards, striving for rapid popularization of standards, and improving standards during use to promote standard construction, and encourage enterprises and groups to accelerate standard formulation. The government selectively accepts standards after market inspection.
Sixth, conduct in-depth research on antitrust mechanisms in the field of data. Compared to monopolies in the manufacturing industry, there is not a monopoly in the data field, but it is difficult to judge due to strong professionalism. In the acquisition of IHS Markit by S&P, antitrust agencies in the United States and Europe have become key influencing factors. And this time, the antitrust agencies in the United States and Europe did not oppose S&P's acquisition of IHS Markit like the EU regulatory agencies did before to prevent Nvidia from acquiring ARM. Instead, they took a side by divesting some assets to make this acquisition successful. This also shows the hesitation of European and American authorities in data antitrust and their deep desire to encourage related companies to grow and strengthen as soon as possible. It is also necessary for our country to initiate relevant research to avoid being constrained in this track that all countries covet.
Seventh, do a good job in popularizing shipping data, and encourage more applications while balancing safety. At the beginning of 2022, some people said that "the epidemic prevention policy has caused congestion of Chinese coastal ships and prevented them from entering the port", and accompanied a picture showing the dense number of coastal waiting ships. This news was believed by many people. In fact, this message is incorrect because the image maker not only intentionally used the difference in ship size ratio and map ratio to create a visual illusion, but also displayed all things related to water transportation on the map, even buoys, local ships carrying cement along the river, fishing boats, etc., to create an atmosphere. The reason why this news has a market is because the popularization of shipping data is not sufficient, and many Chinese people know very little about the shipping industry. Therefore, we need to increase the popularization of shipping data knowledge. At the same time, it is also necessary to vigorously cultivate big data enterprises and encourage data application innovation with greater efforts while balancing security.

(Author's affiliation: Shanghai International Shipping Research Center, Shanghai Maritime University)