Behavioral Analytics

What Is Behavioral Analytics? 

Behavioral analytics is the process of analyzing patterns in behavior to identify anomalies, predict actions, or improve outcomes. In maritime shipping, behavioral analytics helps detect deceptive shipping practices (DSPs), optimize port calls, and enhance operational safety by analyzing how vessels move, communicate, and interact over time. By comparing real-time activity against historical norms, maritime stakeholders can make faster, data-backed decisions.

How Does Behavioral Analytics Work in Maritime Operations?

Behavioral analytics uses algorithms to model the expected behavior of ships, fleets, and crews under various conditions. This includes analyzing AIS data, route patterns, loitering behavior, and port arrival and departure timelines. When deviations from typical behavior are detected, such as unusual transshipment activity or sudden course changes near sanctioned zones, the system raises alerts. 

This form of analytics doesn’t just look at what happened; it focuses on why and how, enabling deeper risk assessment and proactive responses. Windward’s platform, for example, uses behavioral analytics to detect identity tampering, dark activity, and ship-to-ship transfers that might indicate illicit activity.

What Are the Benefits of Using Behavioral Analytics in Maritime Shipping?

Behavioral analytics allows maritime organizations to move beyond static, rule-based alerts toward a dynamic, pattern-driven approach to safety and compliance. Here’s how that translates into business value:

• Early threat detection: spot anomalies before they escalate into major incidents
• Regulatory compliance: detect behaviors that may breach sanctions or emissions rules
• Operational efficiency: identify recurring delays or inefficiencies in port calls
• Insurance & underwriting support: provide risk scores based on behavioral histories
• Supply chain integrity: spot behaviors that could signal fraud or unauthorized rerouting
  

By adopting behavioral analytics, shipping companies can transition from reactive monitoring to continuous behavioral oversight.

How Does Behavioral Analytics Help Detect Deceptive Shipping Practices?

Deceptive shipping practices, such as AIS spoofing, are increasingly being used by vessels seeking to evade sanctions, conceal illicit cargo transfers, or obscure their true origins and destinations. These tactics are notoriously difficult to identify using traditional tracking methods. When a ship deliberately manipulates its AIS signal or goes dark entirely, conventional systems lose visibility, leaving authorities and compliance teams in the dark.

Behavioral analytics overcomes these limitations by continuously analyzing each vessel’s movements and comparing them to established behavioral baselines. The system creates a unique profile for every ship by analyzing historical patterns, including common routes, average speeds, port calls, and interaction habits with other vessels. It also monitors real-time activity to detect deviations from this “normal” behavior.

When a vessel turns off its AIS transponder, for example, the system doesn’t go blind. It uses the vessel’s last known position, heading, and speed to predict its likely course during the dark period. If the ship reappears far off its expected trajectory, with no legitimate reason for the detour, those discrepancies are flagged. Additional clues, such as proximity to high-risk zones or suspicious interactions with other ships, strengthen the alert.

Behavioral analytics doesn’t look at each anomaly in isolation. Instead, it correlates multiple suspicious behaviors to identify known DSP patterns. The system then assigns a risk score, helping compliance teams prioritize which incidents to investigate or escalate to authorities.

What Types of Maritime Data Are Used in Behavioral Analytics?

Behavioral analytics relies on both historical and real-time data to build and refine models. Common sources include:

How Does Behavioral Analytics Improve Maritime Compliance?

Behavioral analytics supports compliance by detecting subtle signals that may precede a violation. For example, if a vessel slows down near a sanctioned area but doesn’t transmit a full AIS gap, it might still be flagged for suspicious behavior.

Earlier this year, Windward reported an approximate 75% reduction in false positives for deceptive shipping practices alerts after incorporating behavioral models into its platform. This allowed compliance teams to focus on high-risk vessels rather than manually sifting through large volumes of benign alerts.

What Is the Role of Behavioral Analytics in Port Call Optimization?

Behavioral data can reveal inefficiencies in how vessels approach and spend time at ports. By analyzing arrival patterns, anchorage durations, and turnaround times, port authorities and operators can:

• Predict congestion and adjust schedules proactively
• Detect vessels at risk of detention based on historical behavior
• Reduce turnaround times through early coordination

AI consulting firm AIQURIS reports that AI-powered behavioral analytics can help shippers cut fuel consumption by up to 15%, partially by optimizing time spent in port. This not only leads to millions in cost savings through improved operational efficiency, but also significantly lowers carbon emissions.

What’s Next for Behavioral Analytics in Maritime AI?

As more vessels become digitally connected, behavioral analytics is moving toward predictive coordination, where systems not only identify risk but also suggest optimal actions. We’re seeing early adoption of multi-agent collaboration, where one vessel’s behavior informs another’s in shared waters.Windward is pioneering this next phase by embedding behavioral intelligence into its risk engines, helping fleets prioritize inspections, improve transparency, and enhance ESG reporting. As regulatory bodies demand more proactive risk management, behavioral analytics will become a compliance must-have for organizations within the maritime industry.