The recent OFAC advisory on maritime sanctions has detailed a new bar of expectations applicable to a wide range of organizations involved in maritime supply chain and transportation. To meet the new expectations, businesses must incorporate proactive screening measures to identify ships that display Deceptive Shipping Practices and may be involved in sanctions evasion.
In the maritime domain, however, the data used for sanction screening is extremely noisy and dynamic, resulting in numerous ‘false positives.’ This creates alerts that trigger more in-depth investigations, oftentimes wasting time, and resources unnecessarily. These false positives, if not handled properly, are prone to translate into lost business opportunities and costly operational structures. If companies examine every single red flag that appears in AIS data, and conduct a manual investigation for each case, it would require an army to sort through the noise.
False Positives are much more than a data problem – Investigations are costly and time-consuming, making false positives a serious operational challenge.
Mind the AIS gap – AIS data is extremely vulnerable to noise and manipulations, leading to large amounts of false positives that need to be resolved.
Focus investigations by reducing false positives – reducing false positives starts with data integrity and human expertise. The process can be accelerated by integrating artificial intelligence to automate behavior analysis and only flag cases that need an experienced human to examine.
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