Unleashing the Power of IoT on Marine Insurance Risk Assessment
IoT data streams provide marine insurers with renewed insight into customer behaviours and the opportunity to automate critical business processes. The UK-based insurance software company Concirrus is on the job.
The world is becoming ever more connected. Sensor technology and smart devices are increasingly connecting our homes, our workplaces and our cities, promising to make our leisure time more convenient, our work more productive and our cities more efficient.
Commonly known as the Internet of Things (IoT), this network of physical, connected devices can connect, collect and exchange data to monitor the health and actions of objects and machines. IoT enables mobile and connected devices to communicate and interact with each other and be remotely monitored and controlled for efficiency improvements and economic benefits.
The same benefits can be unlocked in the marine insurance sector. IoT offers constant data streams that insurers can tap into for improved insight on customer behaviour and associated risks.
IOT AND THE CHANGING CHARACTERISTICS OF MARINE INSURANCE
The marine insurance sector greatly relies on historical, static and demographic data to assess risks, such as vessel type, age, flag and tonnage. Today, however, marine insurers can leverage IoT to gain access to vast amounts of data to improve their understanding of the behavioural features of fleets and vessels.
One company that truly understands the value of IoT for the insurance industry is the insurance software company Concirrus. Having operated in the IoT space since 2012 and with the marine insurance sector since 2016, they are uniquely equipped to understand how connected technology is changing the industry climate. Their co-founder and CEO Andy Yeoman sees IoT changing three particular characteristics of marine insurance:
Behaviour added to rating factors: Marine policies have been rated on risk, using a standard set of rating factors, such as vessel type, place of build and so forth. Relying strictly on demographics, however, may not provide an accurate indicator of risk. For example, the same demographic pool of motor insurance policyholders may look similar on paper but reveal nothing about their differing driving styles. It is the same within marine insurance. Combining vast amounts of data with advanced analytics allows insurers to add behaviour to their rating factors to identify which behaviours correlate to claims and which behaviours cause the claims.
Fractional and zone-based policy types: Policies are global in nature, some being overpriced, and some being underpriced. Take war zone coverage as an example. This requires the customer to notify the broker, who then notifies the insurer that war coverage is needed. Through IoT, this process can be automated by placing sensor technology on the vessel to detect incursions into war zones. The Norwegian Shipowners’ Mutual War Risk Insurance Association (DNK) does this today. They have installed tracking equipment on their member organisations’ fleets, which transmits the ship’s position and automatically generates war coverage when a ship enters a pre-defined zone. You can read more about the project here.
Real-time placement for commercial risks: Placements are primarily managed via paper-based and manually intensive processes. Brokers use paper as their primary form of conveying risks and getting contracts and documents to and from customers. Conversely, real-time placement of commercial risks enables the insurance market to operate with greater visibility and speed, much like the stock market does today.
MERGING HISTORICAL DATA WITH BEHAVIOURAL DATA
IoT unlocks a wide array of new data streams that provide deeper insight into marine insurance risk assessment. By coupling historical claims information with previously unleveraged data sources, such as vessel statistics, movements, local weather, machinery information and traditional demographic data, insurers can glean new insights into the behaviours that correlate the claims.
This is what Concirrus aims to do with their Quest Marine product, a new way of looking at risk. Leveraging machine learning algorithms, their platform provides insurers with the following benefits:
- Portfolio segmentation and optimisation: Leveraging both historical, real-time and predictive rating factors based on operations, port activity and operator performance provides new insight into risks. This allows insurers to target their capital to the most profitable opportunities, correctly reflect the risk in their prices, keep the right reserves, reduce exposure and increase their overall profitability.
- Risk and opportunity identification: Portfolio segmentation allows insurers to find sources of risks and opportunities and allocate their capital accordingly. For instance, a marine insurer may delve into the data and understand which ports have the most claims, or which ports are low-risk, enabling them to price risk accurately.
- Offering differentiation: A deeper portfolio understanding allows insurers to offer targeted coverage that reflects what a vessel is doing at any given point in time. This presents insurers with easy access to the information they need and the ability to automate their manual processes, ultimately differentiating their offering and tailor it to a connected world.
IoT provides a plethora of new opportunities for marine insurers, and Concirrus is an optimal partner to help you harness its power.