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Q3 2026

Global maritime, cargo and logistics insurance market trends report

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The third quarter of 2026 continues to reveal evolving shifts in the global marine insurance market. 

While rate declines have slowed compared to earlier quarters, competition remain strong and underwriters are increasingly selective in their underwriting approach. For risk managers, staying close to these market shifts is essential to identifying opportunities and getting the most value from coverage. 

Use this report to help you:

  1. Understand how rate movements have moderated while competitive capacity continues to expand.
  2. Discover underwriter selectivity trends focused on loss records, risk management, and emerging exposures.
  3. Assess how commercial terms are evolving, including opportunities for broader coverage with well-managed accounts.
  4. Navigate emerging risks including cyber exposures, supply chain vulnerabilities, and geopolitical impacts.
  5. Identify regional market variations to inform placement strategies and negotiate optimally.

Global maritime, cargo and logistics insurance market trends report – Q3 2026

Gain the clarity and data to help you capitalise on favourable market conditions and optimise your coverage strategy.

Download the report

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This publication is not intended to be taken as advice regarding any individual situation and should not be relied upon as such. The information contained herein is based on sources we believe reliable, but we make no representation or warranty as to its accuracy. Marsh shall have no obligation to update this publication and shall have no liability to you or any other party arising out of this publication or any matter contained herein. Any statements concerning actuarial, tax, accounting, or legal matters are based solely on our experience as insurance brokers and risk consultants and are not to be relied upon as actuarial, accounting, tax, or legal advice, for which you should consult your own professional advisors. Any modelling, analytics, or projections are subject to inherent uncertainty, and any analysis could be materially affected if any underlying assumptions, conditions, information, or factors are inaccurate or incomplete or should change. 

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