How data-driven brokers are winning better terms for their clients

A good broker has always known their client's fleet. The best brokers today can prove it with data before a single figure is discussed.

That distinction is becoming one of the defining competitive differentiators in marine broking. As the insurance market moves toward analytics-driven underwriting, the quality of a broker's submission has a direct bearing on the quality of terms their client receives. Anecdote and relationship still matter. But they are no longer enough on their own.

‍

Why the submission is now a strategic document

For decades, renewal submissions in marine insurance followed a relatively standardised format: vessel particulars, trading limits, cargo types, claims history, and a covering note. The underwriter would apply their own judgement, consult their models, and respond with terms.

That dynamic is changing. The marine insurance industry is undergoing a structural shift toward analytics-driven risk management, with leading insurers sharpening their focus on data as a decisive competitive advantage. As underwriters invest in their own data capabilities — AIS feeds, behavioural scoring, Port State Control integration — the information asymmetry between broker and underwriter is narrowing. A submission that does not speak the same data language risks being underread.

The implication for brokers is significant. If your underwriter is already looking at your client's vessels through a behavioural lens, your submission should address that lens directly, on your terms, not theirs.

In the current market, good loss records are worth 2.5 to 5 percentage point premium reductions on hull accounts, with 18 to 24-month policy periods being offered as an additional incentive. The brokers who are consistently securing those reductions are not simply presenting loss records. They are telling a coherent story about fleet quality, and substantiating it with data that underwriters cannot easily dispute.

‍

Translating operational data into underwriting evidence

The most effective use of maritime intelligence in a broking context is not to generate more reports. It is to translate operational behaviour into the specific metrics that underwriters use to price risk.

Vessel conduct scoring and AIS-based benchmarking

Underwriters are increasingly interested in how vessels behave in practice, not just how they are registered or classified. Loitering frequency, deviation from established trade routes, unexplained AIS gaps, and port call patterns in high-risk jurisdictions are all signals that feed into behavioural risk models on the underwriting side.

Brokers who have access to the same data can use it proactively. If a client's fleet has operated with consistently clean AIS records — minimal dark events, no unexplained loitering, no calls at sanctioned or high-risk ports — that is material underwriting evidence. Quantifying it as a comparison against peer fleet behaviour (for example, significantly fewer loitering hours than the global average for the same vessel class) converts an operational record into a negotiating position.

This is evidence-based premium advocacy: presenting time-stamped, third-party behavioural data in the submission to make the case that the risk is better than the market's default pricing assumption.

Port State Control records integrated with operational history

Port State Control inspection data is public, but it is operationally fragmented and difficult to interpret without context. Despite PSC data being publicly available, it is operationally fragmented, making it difficult for industry users to access and interpret quickly. Brokers who integrate PSC records — detention history, deficiency patterns, inspection frequency — with live AIS data can build a more complete picture of fleet quality than either dataset provides alone.

For a client with a strong PSC record, this integrated view is a competitive asset at renewal. Vessels that have sailed through Paris MoU and Tokyo MoU inspections with low deficiency rates, and whose AIS history confirms consistent, compliant trading, represent a measurably lower risk than the class average. That difference should be reflected in the terms offered, and it is the broker's job to make that case with evidence.

For any fleet, PSC benchmarking also enables the broker to identify outlier vessels before an underwriter does. A vessel with a deteriorating deficiency trend or a recent detention is going to attract scrutiny. Surfacing that proactively — and presenting a remediation plan alongside the renewal — is better risk management than hoping it goes unnoticed.

‍

Portfolio-level advocacy: Benchmarking the fleet against the market

One of the most underutilised tools in broking is fleet-level benchmarking. Individual vessel assessments are necessary, but underwriters ultimately price portfolios. A submission that benchmarks the client's fleet against industry peers on the metrics that matter to underwriters creates a different kind of conversation.

Relevant benchmarking dimensions include: utilisation rates relative to vessel class averages; average fleet age versus peer operators in the same trading segment; PSC deficiency rates compared to flag state and class averages; frequency and duration of calls at high-risk ports; and AIS transmission continuity compared to the wider market.

In 2024, IACS-classed vessels significantly outperformed non-IACS classed vessels, with average Deficiencies Per Inspection of 1.78 versus 5.66 for non-classed vessels. For a broker representing a fleet classed with a major IACS member and with DPI figures tracking below the global average, that differential is a concrete underwriting argument, not a soft claim about fleet quality.

The goal is to shift the underwriter's frame of reference from the aggregate market book to the specific risk being presented. A fleet that compares favourably against peers on every material metric is a better risk than the market rate implies. Proving that is the broker's value-add.

‍