Digitising maritime insurance risk

Advancements in technology and data analysis provide significant opportunities for the maritime shipping insurance industry. By utilising AI and large datasets, insurance companies can better understand, predict, and mitigate risks, ultimately leading to safer maritime operations and more cost-effective insurance policies.

Maritime shipping, a cornerstone of global trade, inherently involves risks. These risks have historically been managed through a combination of experiential judgment and basic statistical analysis. However, the emergence of AI and big data technologies offers unprecedented opportunities to revolutionise the maritime insurance sector.

As chairman of Insurwave, I've been really impressed how new technologies developed by a team of high quality product engineers can fundamentally change the "pre-bind" commercial insurance processes. Listening to feedback from global shipping companies in how they are leveraging this new tech to deliver sustainable long term value for their businesses is heartwarming - especially given we're talking about insurance.

Maritime data sources being used to price insurance and monitor claims

The maritime sector generates massive amounts of data from sources like:

• Vessel Tracking Systems: AIS (Automatic Identification System) data provides real-time locations of ships.
• Weather Databases: Weather conditions are crucial in maritime operations.
• Port and Cargo Records: Give insights into vessel and crew behaviour.
• Ship Maintenance Records: Provide data on vessel conditions.

Generative AI models for risk assessment

• Predictive Analytics: AI models, trained on historical data, can predict the likelihood of incidents based on current conditions. For example, predicting potential collisions by analysing ship movements in busy routes.
• Pattern Recognition: Advanced algorithms can identify abnormal patterns or anomalies, such as a vessel diverting from its planned route, which might indicate potential piracy or mechanical failure.
• Simulation and Forecasting: AI can simulate various scenarios (e.g., storms, mechanical failures) and their impact on ships, thus helping insurers to prepare for such eventualities.

Real-time risk management

• Real-time Monitoring: AI can analyse data from multiple sources in real-time, providing insurers with immediate insights into risk conditions.
• Automated Alerts: Automated systems can send alerts about hazardous weather conditions, geopolitical events, or other risks.

Improved underwriting

• Tailored Policies: With deeper insights into ship operations and behavior, insurers can offer customised policies based on actual risk profiles.
• Fairer Pricing: More accurate risk assessment means more accurate pricing, benefiting both insurers and insured parties.

Claims processing

• Automated Claims Processing: AI can automate much of the claims process, speeding up payouts and reducing administrative costs.
• Fraud Detection: Advanced algorithms can identify patterns consistent with fraudulent claims, thus saving insurers money

Training and behavioural analysis

• Crew Behaviour: By analysing crew behaviour data, AI can identify risky behaviours and suggest training or interventions to reduce these risks.
• Safety Training Modules: AI can be used to develop virtual reality-based training modules that simulate real-life scenarios, providing crew with practical training experiences.

Carbon capture, utilisation, and storage (CCUS) has gained traction as one of the pivotal solutions to reduce greenhouse gas (GHG) emissions and mitigate the adverse effects of climate change. As the maritime sector is a significant contributor to global carbon emissions, integrating carbon capture technology on ships can help achieve international sustainability goals. For maritime insurance providers, monitoring these systems becomes crucial to assess risks and ensure the vessel's safe operation.

The cost of capital associated with the traditional marine insurance model is excessive but necessary given the rapidly increasing complexity and business risk facing shippers. Insurance premiums are heavily weighted with the costs of capital and claims often just paid out with minimum challenge given a lack of accessible evidence. Imagine the possibility of lower compliance hurdles and solvency requirements once regulators can be convinced that risk assessment models have much greater accuracy and authenticity?

1. Collaboration: Encourage collaboration between maritime organisations, tech companies, and insurers to ensure that technology solutions are relevant and effective.
2. Continuous Learning: Regularly update AI models to reflect new data and changing conditions.
3. Regulatory Engagement: Engage with regulators to ensure that AI and data-driven solutions meet industry standards and compliance requirements but also help Regulators feel comfortable that these new technologies can genuinely enable the capital requirements to decrease.
4. Tech incubators: IncubEx will also be looking to integrate the sustainable goals of shippers with their insurance policies.
5. London Market Digital Transformation: Along with the new Core Data Record and Blueprint 2 "post bind" market digitisation due in Summer 2024, the next big opportunity will be to enable data flow from "pre to post bind" and truly digitise the whole insurance model start to finish. Now that will be something.

The integration of new technologies and new client supplied data sources can profoundly transform the maritime shipping insurance industry by redefining risk assessment models and policy structures, leading to better risk management, improved safety, and cost savings.

Embracing these technologies is essential for modern insurers aiming to remain competitive and provide the best service to their clients and drive the maritime sector towards a more sustainable and accountable future.