Archives For Big Data

big_data

Historically, a customs officer’s “intuition” backed up by his/her knowledge and experience served as the means for effective risk management. In the old days (20 years ago and back) there wasn’t any need for all this ‘Big Data’ mumbo jumbo as the customs officer learnt his/her skill through painful, but real-life experience, often under bad and inhospitable conditions.

Today we are a lot more softer. The age of technology has superseded, rightly or wrongly, the human brain. Nonetheless, governments thrive on their big-spend technology budgets to ensure the safety of their economies and supply chains.

No less, the big multinational corporations whose ‘in-house’ business is no longer confined by national boundaries or continents are responsible for the generation of huge amounts of data which need to extend  to the limits of their operations. When the products of such business are required to traverse national boundaries and continents,  their logistics and transport intermediaries, financiers, and insurers become themselves tied up in the vicious cycle of data generation and transfer, also spanning national boundaries to ensure those products arrive at their intended destinations – intact, in time and fit for purpose. Hence we have what as become known as the international supply chain.

It does not end there. Besides the Customs authorities, what about the myriad of other government regulatory authorities who themselves have a plethora of forms and information requirements which must be administered and approved prior to departure and upon arrival of goods at their destination.

Inefficiencies along the supply chain culminate in delays with added cost which dictates the viability for sale and use of the product during delivery. These may constitute what is called non-tariff barriers (or NTBs) which negatively impact the suppliers credibility in international trade.

The bulk of this information is nowadays digitised in some for or other. It is obviously not all standardised and structured which makes it difficult to align, compare or assimilate. For Customs it poses a significant opportunity to tap into and utilise for verification or risk management purposes.

The term ‘Big Data’ embraces a broad category of data or datasets that, in order to be fully exploited, require advanced technologies to be used in parallel. Many big data applications have the potential to optimize organizations’ performance, (and here we have it) the optimal allocation of human or financial resources in a manner that maximizes outputs.

At this point, let me introduce one of the latest WCO research papers – “Implications of Big Data for Customs – How It Can Support Risk Management Capabilities” by Yotaro Okazaki.

The purpose of this paper is to discuss the implications of the aforementioned big data for Customs, particularly in terms of risk management. To ensure that better informed and smarter decisions are taken, some Customs administrations have already embarked on big data initiatives, leveraging the power of analytics, ensuring the quality of data (regarding cargos, shipments and conveyances), and widening the scope of data they could use for analytical purposes. This paper illustrates these initiatives based on the information shared by five Customs administrations: Canada Border Services Agency (CBSA); Customs and Excise Department, Hong Kong, China (‘Hong Kong China Customs); New Zealand Customs Service (‘New Zealand Customs’); Her Majesty’s Revenue and Customs (HMRC), the United Kingdom; and U.S. Customs and Border Protection (USCBP). Source: WCO

For thousands of years, maritime authorities have relied on tip-offs, patrols, investigations and random inspections to find smuggled goods. Today they have a variety of additional methods at their disposal, and one of the most promising is also the most intuitive: looking at every vessel’s historical behavior.

Israeli firm Windward was founded to collect, vet and analyze AIS, along with a variety of other commercial data sources on maritime traffic. Just having access to the massive quantity of data that the world’s fleet generates is not sufficient: it could take weeks for a human operator to sift through the records of just a few hundred ships, and law enforcement agencies need actionable intelligence in real time.

This is where Windward excels. Its system uses proprietary algorithms to find specific ships that may be involved in illicit activity based on a number of “red flag” behaviors. Loitering just off of a village or an uninhabited bay may be a sign that a vessel is engaged in tendering goods or passengers from shore. Similarly, when a ship turns off its AIS transmitter or changes its AIS reporting name near smuggling hotspots, it may be taking on contraband. And a ship with a well-established trading pattern that suddenly heads to a troubled region may be engaged in a new (and not entirely legitimate) line of business.

These behaviors are obvious when Ami Daniel, Windward’s CEO and co-founder, walks through a few examples in a live presentation. The novel development isn’t the signal pattern – it is the fact that his firm can automatically find it, without knowing which ships to examine in advance. It doesn’t matter if a vessel is operated by a reputable company or a known North Korean front – Windward’s system analyzes records for the entire fleet, and if a vessel looks suspicious, it gets flagged.

A few cases illustrate the potential of this approach. In Windward’s best-known example, a Cyprus-flagged reefer with a history of trading between Northern Europe and West Africa headed to a port in Ukraine – well outside its normal pattern. It returned towards the Strait of Gibraltar, but before passing through to the Atlantic, it lingered off of Algeria and Morocco for 12 days. It turned its AIS on and off multiple times in busy shipping lanes during this loitering period. Windward notes that this region is at high risk for the smuggling of arms and narcotics.

After passing through the Strait of Gibraltar, the vessel headed north towards Scotland, where it arrived on January 14. It loitered again for half a day in a small bay off the isle of Islay – an area without a port for a 4,200 dwt ship. Windward’s system flagged this behavior as a potential sign of a smuggling drop-off, though it is also possible that the ship anchored up to wait out foul weather or to time its arrival.

This particular case made headlines in the UK when Windward told media that hundreds of vessels with suspicious records entered British waters in the first two months of 2017. The story was picked up by the Global Mail, Sky News and the Daily Record, and Scottish politicians called on the authorities to look into the matter: “This requires investigation, certainly by the police and, I suspect, by the security authorities to clarify what’s going on,” said member of Scottish Parliament Mike Russell.

These results capture attention, and Daniel says that the firm is marketing the system’s abilities to multiple government agencies. The kind of smuggling/trafficking behavior that it can identify is often associated with organized crime and the financing of terrorism, so it has a great deal of appeal for intelligence applications as well as maritime security / maritime domain awareness. He suggests that for now, commercial users (traders, brokers and others) are not a target market, nor does he foresee branching out into similar offerings for trucking or air freight. Windward does one thing well – very well – and Daniel expects that it will invest in its core strength for some time to come. Original article published in The Maritime Executive.