Stop fixing blind: using AIS data to quantify TC-in performance risk in a high-bunker market

Over the past couple of months, we have seen a clear uptick in shipowners and operators using AIS-based speed analysis to manage TC-in exposure. As bunker prices push higher, the cost of underperformance has become impossible to absorb on faith, and charterers are no longer willing to price performance risk on CP specs and broker indications alone.

With VLSFO topping $1,000/mt in some ports, bunkers can represent up to 60% of total voyage costs. A vessel burning just 5% above CP spec creates exposure that shipowners and operators only discover after the fixture is done.

This article breaks down the financial impact of underperformance, shows how AIS data can identify the gap before you commit to hiring a TC vessel, and gives you a calculator to model the exposure for your own fleet.

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The hidden exposure in TC-in decisions

For most chartering teams, vessel selection still relies on CP specifications, class records, recent inspections, and broker-provided indications. Useful, but limited — none represent continuous, independently verified performance in operation.

Most TC-in decisions are still priced off CP specifications and recent perception rather than verified performance. CP specs reflect design intent, not current condition, and there is no obligation for owners to disclose gradual degradation between dry docks. Broker indications help frame the market but are not evidence of how a vessel is actually operating. In practice, two vessels fixing at similar levels can have materially different fuel consumption profiles, and that gap is rarely priced into the hire rate. The result is simple: the performance risk sits with the charterer, and the cost only becomes visible after the fixture is done.

A large share of vessels operate 5-15% above their warranted consumption, particularly as time from dry dock increases. At $800/mt VLSFO, a 10% performance gap costs $912k per vessel per year. Most of it is avoidable.

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Why traditional checks fall short

Pre-fixture due diligence typically combines three inputs, each with a structural weakness:

1. Class records: Reflect condition at the moment of inspection, not performance between surveys.

2. Noon reports: Self-reported, episodic, and often lacking operational context.

3. Broker indications: Not independently validated. Useful as a starting point, not as evidence.

None of these provide a longitudinal, weather-adjusted view of vessel behaviour across voyages. Because Kpler works closer to the raw VHF signal and owns its collection network, it resolves conflicts and retains more messages than third-party resellers, giving you the high-fidelity data required to prove technical underperformance.

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What you can actually do with this data

AIS gives you speed over ground at high frequency, with a precise position (latitude and longitude) for every data point. MarineTraffic combines positions with the weather conditions at that exact location and time, covering wind speed, wave height and current. The result is a single dataset that links vessel movement to the environmental conditions it was operating in. That is what makes it possible to separate what the vessel is doing from what the weather is doing to it.

With that combined dataset, you can set your own thresholds for what counts as "good weather" and filter out everything else. Once you can make that separation, four things become possible that were not possible with noon reports or class records alone:

1. Filter to calm weather and find the real gap

Set your own Beaufort threshold (e.g. <4) and look at speed over ground in those conditions only. If the vessel is consistently 0.5 kn below warranted speed in calm seas, that is hull fouling or engine degradation — not weather. You have isolated the technical problem.

2. Track degradation over months, not snapshots

Plot calm-weather speed across 6, 12, 18 months. You will see the fouling curve — performance declining steadily between dry docks. This tells you exactly where a vessel sits on its maintenance cycle before you commit to a fixture.

How far back you look depends on the question you are asking. The past two to four years shows the long-term fouling curve since the last dry dock, useful for understanding the vessel's trajectory over its full maintenance cycle. The last 12 months is essential for pre-fixture decisions: it shows where the vessel has been trading recently and how it is performing right now, which is what actually matters when you are about to commit to a fixture.

3. Compare candidates on the same route, same conditions

Two Panamax candidates on the same Brazil-China route in the same quarter. One holds 14.0 kn in calm weather, the other drops to 13.3 kn. That 0.7 kn gap translates into materially higher fuel burn at $800/mt. The data makes the choice obvious.

4. Assess fouling risk from trading region

By tracking historical positions, you can measure time spent in tropical and subtropical waters between 0 and 30 degrees latitude, where warm temperatures and high biological activity accelerate hull fouling. A vessel that has spent months trading in these regions is materially more likely to experience performance degradation than one operating in temperate or cold waters. This is not captured in charterparty terms, but it has a direct impact on speed and fuel consumption. When combined with weather data, AIS also allows you to separate temporary performance loss driven by routing or conditions from structural degradation linked to where the vessel has been trading.

5. Build a defensible position for claims and negotiations

AIS data is timestamped, independently collected, and not self-reported. If a vessel consistently underperforms its CP warranty in calm conditions, you have the evidence base for speed and consumption claims — before you need to involve arbitrators.

6. Layer in draft and ocean conditions to sharpen the speed comparison

Draft from AIS lets you separate laden from ballast voyages for a like-for-like speed comparison. Adding sea surface temperature and salinity tightens the fouling view further. A vessel that spent three months in the Gulf of Guinea is not the same risk as one at the same latitude in the South Atlantic.

The operational shift: reactive to proactive

Integrating AIS-based benchmarking shifts the technical team's role from investigating underperformance post-fixture to screening vessels pre-commitment.

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Why this matters for TC-in vetting

AIS network quality varies significantly. Many providers lose vessels for hours or even days, particularly in congested or remote areas.

If your AIS provider loses a vessel for 12 hours mid-voyage, your entire speed-over-ground profile is compromised.

With a denser, higher-frequency network, you get continuous data — enabling a defensible, data-driven view of vessel performance, not an approximation built on sparse signals.

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Sources & references

Bunker prices: Tideform.

Panamax speed and consumption reference: Baltic Exchange — Dry Services (Panamax vessel description).

Historical AIS data: MarineTraffic Historical Track API.

CP performance deviation ranges: industry literature from hull coating manufacturers and classification society guidance on hull fouling impact.

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