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Weaponising your Sanctions Compliance Programme

How strategic use of data can address illicit shipping and maritime sanctions risk

 

In our previous post, we discussed OFAC’s advisory release in May 2020 entitled, “Guidance to Address Illicit Shipping and Sanctions Evasion Practices”. This advisory explained how certain “malign actors” have learned new ways to avoid sanctions in the maritime industry that include:

  • Manipulation of the Automatic Identification System (“AIS”) on vessels;
  • Irregular voyage routes and detours;
  • Ship-to-ship transfers;
  • Physically altering the vessel’s identification (“IDs”) and flags; and
  • Complicated vessel ownership structures.

To maintain effective compliance, operators in the industry should also consider current data analytic techniques to address these risks by employing a data focussed approach to sanctions compliance and KYV (Know Your Vessel) assessments.

What data is available to help identify and mitigate these risks?

AIS is an automated tracking system used on vessels around the globe, originally designed for collision avoidance and safety. AIS data includes vessel identifiers, such as the International Maritime Organisation (“IMO”) number and Maritime Mobile Service Identity (“MMSI”) number, and the vessel’s course, speed and heading. In the past decade, AIS data has become increasingly more available and abundant, and there are numerous public and private services and tools providing real time and historical vessel tracking.

In addition to AIS location data, supplementary vessel data including dimensions, draught (i.e. for benefit of those not involved in shipping, the vertical distance between the waterline and the bottom of the hull), call sign, vessel ownership and route details are also available to varying levels. This data, alongside AIS and sanctions list information, can be combined to provide insight on vessel activities and behaviours relating to possible sanction evading tactics.

What analysis can be applied?

Data-led approaches to maritime sanctions compliance can vary from sanctions list screening to more advanced anomaly detection and behavioural modelling. Sanctions evasion typologies can be modelled intelligently and outcomes enhanced by known instances of activities (like ship-to-ship transfers) to generate an intuitive risk view that can be used to identify possible hits that require further investigation.

A possible methodology is to consider both individual vessel perspectives and regional views for a basis of analysis to provide full insight. A vessel perspective will consider tracking movements, activities and behaviour, as well as identifying any ID manipulation of a vessel over time. This can include loitering (spending extended periods in areas at neither source nor destination of voyage), deviations of typical routes and AIS outage patterns as well as evidence of mid-voyage offloading of cargo from draught data.

A regional view of analysis can focus on areas of interest – sanctions risk areas or other local administrative regions and analysing the vessel IDs, patterns and behaviours within this area over a given period. This can cover areas of frequent loitering or ship proximity. Additionally one can gather ‘dark activity’ zones where AIS signals are frequently switched off or ship-to-ship transfers are common.

Challenges and conclusions

Although companies can use maritime AIS location data to generate intuitive sanctions-risk views of vessels and locations, there are a number of challenges with using this data, such as:

  • Inconsistent and noisy AIS data which is reliant on vessels’ equipment;
  • Integration of data sources and reliability of vessel information databases and AIS sources;
  • AIS switch off may require extensive investigation and human input to determine whether it is truly a sanctions evasion relation suspicious activity or not; and
  • Because of the high volume of data, the hosting and processing data efficiently will be a challenge.

As such, it is important to use the right reliable data feeds, analytical overlay and appropriate subject matter specialists who can help cut through the noise, assess potential false positives and help use this data in a meaningful way. Companies operating in the sectors outlined in OFAC’s advisory should begin to embrace data-focussed, insight-led approaches to combatting illicit shipping and sanctions avoidance practices. By applying these data analytic techniques on various relevant maritime data, companies can not only detect previous potential sanctions breaches, but also proactively reduce maritime sanctions risk on a business-as-usual basis.

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