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Smarter share accommodation insurance offerings deliver better experiences for owners and renters alike

Βy the numbers, there are currently 4 million share accommodation rentals around the world and 2 million occupants on any given night. And while thread count and square footage are top-of-mind, rental insurance is largely overlooked. In the current landscape, landlords often over insure their properties while hosting out-of-towners. They’ll take out a 12-month policy with their general insurer and then double up on insurance via their home-booking platform while their property is leased out. Unbeknownst to homeowners, they’re double insured for the duration that their home is occupied.

Turns out that the global incumbents don’t have the technical or operational capabilities to offer products that would pause a landlord’s policy when their property is insured by a hospitality service. More often than not, they’ll offer a one-size-fits-none approach to general home insurance.

Why the oversight? Incumbent insurers aren’t incented to create tailored policies as they’re effectively being paid premiums without having to provide the product for the entire period. There’s an opportunity to both provide a better solution and to innovate via policies and distribution to ensure that the share accommodation market has a sufficient level of insurance.

Tapping into insurtech capabilities enables homeowners to take out customized policies that suit their specific needs and rental schedule. Tailored policies have the capacity to scan the dates of stay and provide a coverage period that aligns with precisely when renters inhabit the dwelling. More so, they can add additional relevant coverages based on data. There are also opportunities to integrate extras into the pricing of the product. For example, taking into account a landlords’ parked car that isn’t being driven for the duration that the house is occupied by renters.

It all sounds great. But how are customized plans created? AI technology can automatically bundle policies based on data inputs, either from data collected directly from distribution partners or by integrating independent, third party data sources. We’re talking input about the trip itself, how much the vacation costs, the travel history of the individual in question, etc. We don’t always know where valuable insights will crop up – and that’s where machine learning techniques come in.

We have access to an endless amount of data, which is great. It’s only when applying machine learning techniques that we can connect the dots. The ability to apply machine learning techniques to gain inference from data is what helps insurers create new products and get better at pricing the underlying insurance.

When we look at where the insurance industry is heading, it’s really about examining independent, seemingly unrelated data sources to improve pricing and customization. In the shared accommodation market, in particular, insurtech companies are actively looking to create products for the home sharing industry that work in tandem with landlords’ home policies, ensuring that renters have exactly the right amount of coverage at all times, whether a host or a traveler. No one wants to be overpaying or under-covered.

There’s power in the ability to personalize and market to an “audience of one.” Moving forward, it’s vital that homeowners’ team up with smart, AI-equipped, customer-obsessed partners to create personalized plans. It comes down to creating policies that are customized to the property owner in question. Undoubtedly, landlords will begin to see definitive cost benefits by adopting the right insurance policy for their property.

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