The technological landscape is shifting. No industry is immune to the so-called “disruptive innovation” transforming how we conduct businesses in this generation of constantly evolving technologies.
So how does this affect us now?
The new digital ecosystem allows people to easily get a good deal on their insurance whilst on the go. Access to the internet from wherever you are means that you can shop for insurance and browse deals online without ever having to step inside a broker’s. Apps are available to make insurance shopping even easier, with new fintech startups aiming to make managing your finances just as simple and convenient as updating your Facebook status.
With many of these new apps, auto insurance can be purchased for hourly or daily cover, as and when you need it. If you need to insure yourself on a friend or family member’s car from anywhere between an hour to just a couple of days for a road trip, you can do so from a smartphone app wherever you are, and save you from purchasing an annual premium when you only plan to drive the car for a short period.
But fintech in the insurance industry goes beyond just mobile apps. Usage-based insurance, for example, allows for granular based premiums based on accurate data of individuals’ behaviour. As an emerging market, this has so far only reached popularity in auto insurance where insurers are able to price their insurance using the client’s actual driving data via a “black box” device installed in their car (hence why it’s popularly referred to as “black box insurance”. Telematics and usage based insurance opens up opportunities for two new pricing models: Pay As You Drive (PAYD) and Pay How You Drive (PHYD). Customers can be charged insurance more accurately based on their actual aggregated driving data rather than statistical profiles of their general demographic, taking into account things like the times of day that they drive, routes they take and driving behaviour including acceleration and deceleration.
Eventually when driverless lorries and cars become common on UK roads, we may even see these self-driving vehicles being quoted with cheaper prices if they are proven to be safer on the roads than vehicles driven by humans.
The Future of Insurance
As IoT (Internet of Things) becomes more commonly used in both households and business premises, accurate data can be mined from each household (or each business) to better calculate individual risks, or even prevent claims (such as fire or flood) from occurring. Various home monitoring devices and other behaviour-based products could detect things like property security issues, with customers who lock all their doors and actively take security precautions benefiting from cheaper prices due to the reduced risks of burglary.
According to Accenture Research, 82% of insurers are already investing in embedded artificial intelligence solutions. By being forward-thinking and investing in the future of the industry, traditional insurers stand a stronger chance of surviving the inevitable changes still to come.
Big data is getting even bigger. And insurers can reap the benefits of collecting (or having access to) this large amount of data available to analyse the information for improved predictive modeling and identify actionable opportunities to maximise their business. And as new technologies become available within the Internet of Things, the aforementioned usage-based insurance will be applicable to more than just auto insurance. Predictive modeling can be used to cross-sell insurance products to consumers and optimise pricing based on better risk quality assessment.
In addition to allowing for more granular, accurate product pricing, the Internet of Things also creates new opportunities for better fraud detection and smoother, more efficient claims processing. This enables insurers to reduce premium prices for the consumer, due to the lower operational costs. According to the Association of British Insurers, the typical honest UK policyholder is thought to be paying an additional £50 on top of their annual insurance bill to cover the costs of insurance fraud. Better detection would dramatically lower the costs of the honest customer.