Maritime intelligence leader Pole Star Global has launched its Maritime Transparency Index (MTI) — a machine learning-powered risk scoring system that assigns vessels, voyages, and associated parties transparent scores from 0 (Hard Dark) to 5 (Transparent), distilling complex vessel histories, ownership structures, and behavioural anomalies into credit-style ratings that compliance teams, port authorities, and shipowners can act on immediately.
Similar to financial credit ratings, MTI aims to deliver intuitive risk assessment through a 0-5 scoring scale that compliance and financial teams immediately understand. The proprietary machine learning algorithm analyses 40,000+ vessels on a quarterly basis — representing 80% of the active commercial fleet.
Historical and structural risk indicators including vessel age, ownership transitions, flag changes, sanctions history, port detentions, and recorded deficiencies are evaluated. Analysis of reporting gaps and spoofing activity collected via a mesh of vessel position data including AIS are also studied. Behavioural anomalies including port call patterns, time in port, ship-to-ship transfers, slow steaming, unexplained delays, and geographic risk exposure are also taken into consideration.
Saleem Khan, chief data and analytics officer at Pole Star Global, commented: “The Maritime Transparency Index represents a fundamental shift in how the industry approaches vessel risk assessment. By combining machine learning and advanced analytics with 25 years of maritime intelligence expertise, we’ve created a tool that’s as powerful as it is simple to use.”
