Insurance is a way to share financial risk between the insurer and the insured; marine insurance is no different. Shipowners pay the insurer a fixed amount, and in exchange, the insurer takes on the risk of specified financial losses. Until recently, the only practical way to assess a marine insurance policy’s risk was to use proxies for risk, like the type, age and condition of the ship, operating area, and cargo type. The internet of things (IoT) has changed this.
What is the internet of things?
The internet of things connects blurs the line between computers and everything else. From toothbrushes to toilets, everything’s becoming connected. Is your IoT smart light bulb a computer? What about your baby’s smart nappies?
Because insurance companies’ primary focus is risk assessment and risk management, they didn’t take long to realise the potential of IoT data. Rather than relying on customers’ honesty in a questionnaire, insurers can track their behaviour. Rather than grouping customers with similar characteristics, insurers can use IoT to personalise individual risk assessments and insurance offerings.
How can IoT help in marine insurance?
IoT alone can’t help with marine insurance – but the data it generates can. IoT can facilitate loss prediction and prevention, risk monitoring, and simplified claims processing.
Loss prediction and prevention
Insurance is based on loss prediction. Insurers predict how many of their customers will suffer a loss. If customers’ premiums amount to more than the insurer’s payouts, the insurer stays in business. Some marine insurers, including protection and indemnity (P&I) clubs and cargo insurers, go a step further and help customers with loss prevention. Using IoT data to dynamically assess that customer’s risk makes sense. Providing data-based advice to help customers mitigate or prevent losses makes even more sense.
As ship managers turn to IoT to guide their decisions, insurers can use the same data to calculate premiums based on a more accurate assessment of each customer’s risk profile. Mark Phillips, the head of sales at Concirrus, explains, “Gaining insights from IoT data will give these insurers a way to quickly understand the risk in their portfolio at a granular level and begin to make plans for mitigating their risk… There is really no such thing as ‘bad’ risk; it is all about pricing accurately. So, with a deep understanding of the portfolio, insurers can price appropriately depending on the level of risk.”
IoT cargo monitoring for cargo insurance is a booming business. Continuous remote monitoring of physical parameters not only helps insurers understand the risks, it can help the cargo owner and the ship’s crew to prevent or minimise damage.
War risk insurance covers another dynamic risk. When a ship enters and leaves designated war risk zones, they report to their company and war risk insurer. DNK, a Norwegian war risk insurer, has automated the process.
All ships with DNK war risk insurance carry IoT tracking equipment. When a ship enters a designated high-risk or war zone, the ship’s war risk insurance comes into force. When the ship leaves the area, the reverse happens. All the reporting is automated. The reduced administrative workload allows the crew to focus on their primary role of managing the ship. This improves both safety and accuracy. Once the ship is out of the high-risk area, DNK’s system calculates the exact price of the war risk cover based on the ship’s location and the duration of the transit.
Insurance claims are always a headache. In the maritime industry, establishing the facts usually involves surveyors and an astounding amount of paperwork. The continuous stream of data from IoT sensors makes it easier to confirm the facts of the case. This cuts down on the paperwork and speeds up claims processing.
Considerations of IoT in insurance
As with any connected device, companies should consider privacy and security. Whether for the shipowner or the insurer, IoT devices can collect and transmit sensitive data. What could criminals do with up-to-date information on your ship’s position? Could thieves use detailed information about the location and condition of a particular shipping container? And if so, how can you secure the data? To address these problems, the Industrial Internet Consortium has issued a Security Framework for the Industrial Internet of Things.
Companies using IoT in marine insurance
Concirrus has proved that behavioural data is a better indicator of risk than traditional demographics. Their hull, cargo and P&I insurance offerings leverage the latest in digital techniques, including IoT, to gain a holistic view of vessel behaviour. This enables real-time asset management, predictive modelling and optimised connected insurance policies.
Parsyl offers technology-enabled cargo insurance. They aim to help companies minimise cargo losses by understanding the risk before it happens. Their compact, affordable IoT devices track physical data and position, making it easy to collect data across the entire supply chain.
Evertrace’s real-time track and trace device monitors physical data and location of cargo worldwide. Their machine learning-based platform provides notification and alerts, actionable prevention guidelines for all parties, and accountability and transparency of actions. It also enables one-click claim reporting based on full shipment report and stored documents.
Arviem’s automated container and cargo locating and sensing technology provides real-time data on the location and condition of cargo. They offer cargo monitoring as a fully managed service, including cargo monitoring devices, access to their data analytics platform, and device logistics and maintenance.
The future of IoT in marine insurance
As part of a wider strategy of digitization, IoT – or, more specifically, the data generated by IoT – is set to change the face of marine insurance. IoT enables better risk management, giving insurers more flexibility in their insurance offerings. But IoT alone is not enough. Only when it’s combined with technologies like big data, automation, and artificial intelligence (AI) or machine learning (ML) can IoT come close to fulfilling its potential.