We are living in an era where technology is impacting all the industries and helping us perform tasks easier than ever before. Insurance industry is also not left behind when it comes to receiving these benefits. Startups had been coming up with new ways of solving the challenges faced by the insurance industry.

One of the main pillars of the insurance business is underwriting which involves assessing the riskiness of the asset/person the insurer is insuring. When it comes to Property & Casualty (P&C) insurance we have seen some great improvements in the underwriting processes of property insurance in the last two decades. Geocoding helps pinpoint the exact location of a property beyond which advancements in seismology and meteorology have helped develop catastrophe models which can simulate the natural perils risks (earthquake, cyclone, bushfires etc.) faced by the property. This whole process gives a lot of confidence in assessing the risk profile of the property and also helps price it better.

When it comes to moving risks (like Motor or Marine), the challenges become more complicated as the risk profile is impacted by constantly changing factors. For example, unlike property a car is a moving risk and the risks faced can depend on the way the driver drives it, age of the driver, time of the day they drive, path they take, weather conditions etc. Telematics have helped a great deal in providing a solution to underwrite Motor risks. Marine insurance, however, to date is still underwritten in a traditional way i.e. using the demographic data like age of the vessel, size, type etc. As with Motor, Marine is a moving risk and the risks are dynamically changing. The infographic above proposes one method to assess and underwrite Marine Hull risks better.

Unlike Motor where devices are needed to be installed on cars to record Telematics data, Marine data is already captured and available easily on the internet. Sites like Marine Traffic, FleetMon and many others provide real-time and historical tracking data of vessels. The problem here is not the lack of data, it is about transforming that data into a meaningful format that can help insurers when it comes to underwriting Marine Hull risk.

One way we suggest doing that is to break down different areas of the ocean into risk zones (high, moderate, low risk). This can be determined with the help of experts and considering factors that pose risk to a vessel on its journey (pirates, terrorism, capsizing, storm etc.). Historical vessel traffic data can then be used to determine the percentage of time spent by a given vessel in different zones which can then be used to determine the overall riskiness of a vessel being underwritten. This can be done for each vessel in your portfolio to determine the overall riskiness of the portfolio. This then also helps in visualizing your risks and how spread they are in the different zones in the sea over the course of a year.

We can argue over the accuracy of the assessment from this method; however, this provides a good steppingstone for further developments and innovations and certainly should be more effective than the existing demographic based underwriting.

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