Transforming Maritime Insurance Through Advanced Risk Assessment

Leveraging data analytics presents us with the opportunity to charter a new course in maritime insurance, by harnessing the power of data to evolve traditional risk assessment.

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In the maritime industry, where uncertainty can be as vast as the open ocean, risk assessment is the cornerstone of effective insurance. As the number of risks to the supply chain grows, we are seeing a greater need to harness the power of data to revolutionize how risk is evaluated and mitigated in maritime operations. In this article, we will delve into how Insurtech companies are leveraging data for precise risk assessment, infusing Machine Learning (ML) and Artificial Intelligence (AI) technologies to tailor policies to the maritime sector, and showcase the impactful results this can achieve in this dynamic domain.

1. Data-Driven Risk Assessment: Illuminating the Depths of Uncertainty

Put yourself in the role of a Marine Cargo Underwriter, tasked with assessing insurance quotes for two seemingly similar cargo shipments by the same cargo owner, both originating from the UK and destined for the US East Coast via sea transport. At first glance, the risks may appear quite comparable.

However, a deeper examination reveals a stark contrast. The first shipment entails transporting plastic products to New York in April, benefiting from favourable weather conditions and aboard a state-of-the-art vessel operated by a highly reputable container-line, which experiences rare claims incidents over the course of decades. Meanwhile, the second shipment is scheduled to arrive in Miami during hurricane season, carrying high-value pharmaceutical products aboard a 25-year-old vessel under the ownership of a more claim-prone shipping company.

Consider, then, the wealth of additional information at your disposal when making a decision and determining the premium rate to present to your client. Does this newfound insight alter the overall risk assessment?

In the maritime insurance realm, traditional risk assessment models often relied on historical data and generalized assumptions for the future. But we are seeing a real need to embrace a data-driven approach that taps into a wealth of information from various sources, from direct cargo owners and freight forwarders’ data to external third-party maritime data providers. Vessel specifications, navigation patterns, port congestion, cargo details, and even container and vessel real-time tracking are among the data points that feed into a comprehensive risk management approach and evaluation process.

Analyzing these diverse datasets allows you to gain a holistic view of the potential hazards faced by each shipment – enabling insurance policies to be tailored to the specific risks associated with different supply chain operations, resulting in more accurate underwriting and better alignment with the needs of a forwarder or logistics company.

2. Maritime Innovations: Pioneering Tailored Solutions

By leveraging data from supply chain operations, container tracking, and vessel behavioral patterns, cargo certificates that adapt premiums based on individual shipment risk profiles can be created. This innovative approach not only promotes supply chain risk management investments (e.g. more sophisticated packaging), but also provides personalized pricing, ultimately fostering a win-win scenario for both the freight forwarder or logistics company and the wider industry.

3. Machine Learning and AI: Navigating the Future of Maritime Insurance

This data-driven approach goes hand in hand with cutting-edge technologies like Machine Learning (ML) and Artificial Intelligence (AI). ML algorithms analyse historical data from vessel maritime incidents to identify patterns and predict potential risks for containers onboard containerships, as well as port congestion patterns resulting in risky cargo (over-)accumulation and delays in deliveries. This enables insurance providers to proactively recommend safety measures to supply chain operators, thus reducing the likelihood of supply chain disruptions and pure cargo claims.

4. Clear Skies Ahead: Delivering Tangible Results

The integration of data, ML, and AI has already yielded encouraging outcomes in the supply chain insurance landscape. With tailored insurance policies, cargo owners willing to cover their shipments will experience reduced insurance costs that better align with the real risks they face. Quoting and binding experiences are massively improved thanks to data integration with supply chain players, reducing the overall time necessary to finalize the process and download the final insurance certificate. Claims processing can be expedited, with claims notified in a few seconds.

Pioneering a Safer Maritime Future

In contrast to conventional risk assessment methods, which may end up with two very similar prices for the scenarios above, a data-driven approach incorporates novel variables, considering not just industry-standard factors but also behavioral aspects historically overlooked in risk analysis. This approach recognizes the inherent differences in the two risks, aiming to provide more equitable pricing that accurately reflects underlying risk profiles. This strategy supports freight forwarders and logistics companies, while fostering sustainability and profitability in the wider insurance industry.

Leveraging data analytics presents us with the opportunity to charter a new course in maritime insurance, by harnessing the power of data to evolve traditional risk assessment. Insurtech's are already using data-driven insights, innovative supply chain products, and the infusion of ML and AI technologies, to make waves in an industry that strives for data visibility, risk quantification and sustainable results.

As supply chain operations evolve, it’s imperative to remain dedicated to navigating the seas of risk with innovation and data as our guiding stars.