This piece by Vicky Wills, Chief Technology Officer, Zego, looks at how technology can help build insurance brands, let the customer feel that shared data has a reward and make the roads safer by offering real-time alerts to drivers.
It goes without saying that technology plays an important role within many businesses across many industries. However, it is how these businesses use technology that makes them stand out from their competitors. There are two main reasons why companies would adopt and develop technology. Firstly, to optimise or improve a process or function and secondly to innovate; to fundamentally change the way something is done. The best way to apply this second approach in any industry is to target the very core of the product offering that will result in the biggest change and therefore differentiate from the competition.
We’ve seen other industries undergo significant technological change in the last two decades, such as Commerce (web changed the way people shop) and advertising (targeting and tracking fundamentally shifted). Insurance is still very early on in its technical journey. When it comes to motor insurance, the core of the product offering is undoubtedly pricing, and therefore the understanding of risk. The traditional motor insurance industry is often still perceived as relatively outdated, particularly in terms of how it prices policies for customers. Conventionally, pricing models are heavily based on age and gender of the driver, alongside other factors, such as where they live and even occupation.
However, the option of new and improved technology and access to far more data because of this, is allowing insurance companies to provide fairer and more affordable pricing to customers based also on factors such as driver behaviour. In other words, with advances in technology and data the insurance industry is poised to deploy a far more sophisticated view of driver risk.
Understanding risk to price fairer
As recently as five years ago, major insurers were pricing solely on this traditional model (also known as a Generalised Linear Model). This model, as the name suggests, makes generalisations about the risk profile of a particular characteristic, i.e., age or gender, rather than looking into the true risk a driver takes when on the road. It’s also fair to say that the majority of factors used in traditional models are a proxy for risk rather than a true representation: whilst your age and driving style might be correlated, your age isn’t the reason you drive as you do.
A driver in their 20s could be paying high insurance costs simply because of their age when in fact they are a safe driver and take less risks on the road than someone 20 years older. With a traditional pricing model, this driver will usually have a fixed-cost annual policy. Once implemented they will have little or no control over potentially reducing this cost until their renewal.
By adopting and developing new technology, insurers can gather real-time data from vehicles and other contextual sources that will show their true driving behaviour and risk on the road. Recently at Zego, we have acquired a telematics company to accelerate our work in this area. With every new technology or data integration, we add an additional layer of contextual data to our pricing model, such as real-time analysis of accident hotspots.
In this example, the new additional layer of data allows us to assess the most common routes drivers take and the associated risks with those routes and certain areas. In the future, this opens up the potential for Zego to share designated routes with drivers, so they can make safer, more informed journeys, while avoiding accident hotspots where possible. Combining this data with the more traditional factors, drivers could reduce the cost of their insurance by avoiding certain routes.
Giving drivers the ability to manage risk
Not only can technology directly help insurers price policies more fairly by helping them as a company understand risk, it can also allow drivers themselves to manage their own driving behaviour and mitigate their own risk, through a driver dashboard that provides valuable insights from the data collected.
Drivers can have their very own ‘risk profile’ which details driving patterns such as routes taken, time of travel and speed. If the insurer identifies specific risks that could be rectified, then they can even go as far as sending actionable steps on how to improve driving performance and ultimately reduce insurance costs. Technology provides instant communication channels with drivers such as text or in-app notifications, so they can quickly and easily make changes to their driving behaviour. Insurance companies have the option to incentivise good driving by not only reducing costs, but with further benefits and rewards, such as partner incentives, an obvious candidate being discounted vehicle servicing.
The future of technology for insurance
The insurance industry will continue to see a lot of change in the coming years with the adoption of technology, how it assesses driving risk and then ultimately how it helps alter the way insurance is priced. The companies that will come out on top are those that manage to apply technology to drive innovation, not just optimise their current processes. Although this article focuses on the opportunities related to data capture, it is also vital to understand user behaviour. Insurers will rely on building products that allow for this data to be shared and inspire positive change in risky behaviours identified – neither are trivial problems.
Over the next decade, we may even see personalised pricing and fairer premiums eventually eclipse the traditional insurance model. If risky parties are reliably identified, they could be priced out of the market as the lower risk customers will no longer be subsidising the losses.
Insurance companies need to obsess about how their products will benefit their customers – fairer pricing is within reach with a personalised view on risk through telematics data, but attention should also be paid to how technology can help customers to mitigate risk to lower their own premiums.
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