Covering disruptive stories
Car insurance is about as dull as things can get, right? WRONG. In the dawn of artificial intelligence, machine learning and robotics, just about every industry is undergoing huge transformation - and the insurance industry is no different. For instance, auto-reminders are now in place so clients can have a peace of mind - one of the many ways technology affords us more convenience.
Today, we have cloud computing, the Internet of Things (IoT), predictive analytics, GPS, mobile phones, blockchain, smart contracts, and artificial intelligence (AI), we are awash in new technologies and new ways to measure risk, engage with customers, reduce costs, improve efficiency, and provide better solutions to insurance customers.
From apps that allow agents to quickly process claims, to AI being used to navigate the huge amounts of data involved in insurance schemes, tech is upending the world of insurance in general, but especially the car insurance industry.
Different types of transactions have become more efficient than we could ever imagine, autonomous vehicles have presented a major challenge to traditional auto insurance companies and telematic devices are changing the way insurance providers develop risk profiles for drivers.
Let’s start with this last one. I for one never imagined living at a time where, using predictive analytics and technology, companies would be capable of assessing drivers on their behavioural habits behind the wheel in order to develop risk profiles and thus, price insurance packages accordingly for those drivers. But it is happening. Telematics or “black box insurance” describes the technology used by modern insurance companies to identify high risk drivers, track stolen vehicles and improve driver safety overall. Telematics insurance however refers directly to the range of products that relate to telematics technology, in other words its ability to send, receive and collect information about a car’s movement and location.
Think of the problems this kind of technology could save… The question marks surrounding a driver’s ability, the likelihood of an incident or damage, the location of a stolen rental car, the list goes on. Most significantly, telematics can be used to develop extremely accurate risk profiles of drivers. With more detailed information about drivers at their disposal, telematics auto insurers are able to offer insurance rates that are fairer and far more accurate.
All the big companies are experimenting with this type of technology: Fleetmac Group, TomTom, KORE, and more. In the United States, the Allstate Drivewise program allows drivers to view their last 100 trips and see a breakdown of their driving behavior. On average, drivers can save about 10 to to 25 percent as a result on their insurance using Drivewise. Some smaller companies and regional insurers are also using telematics, and offering customers car insurance programs.
The use of telematics for fleet management in particular is showing huge promise. So much so that the global automotive telematics market is expected to reach $11.5 billion by 2021, growing at a CAGR of 18% during 2017 – 2021.
Next let’s explore machine learning - a technology that is rapidly changing the way companies interact with their customers. Machine learning enables computers to “learn” from data as they are exposed to it and told to identify emerging patterns. In this way, machine learning has the capacity to revolutionise the customer experience by identifying previous buying experiences, leveraging a giant pool of data to predict a customer’s likeliness to purchase a product, and customising the buying experience so that they might be more inclined to.
Since the car insurance industry is typically one with low customer interaction and slow tech adoption, it just won’t cut it with millennials unless it evolves to factor in this type of technology. Unless the buying experience is available immediately, highly digitalised, incredibly efficient and customised to the buyer, millennials will simply look elsewhere for insurance providers.
Machine learning may just have been adopted in the nick of time, in that case, with chatbots/AI assistants perhaps the best example of the technology in action. But machine learning is transforming the auto insurance industry in other ways, too. Machine learning algorithms are being used to interpret driver data in an effort to monitor market trends and identify business opportunities, and also to drive performance monitoring with clients.
Lastly, let’s take a brief look at blockchain - the decentralised ledger changing the way we bank, listen to music, buy property and receive healthcare - and see how it too is changing the world of insurance. With the ability to transfer smart contracts and ‘Know-Your-Customer’ data via blockchain, insurance companies can ease the painful verification processes required during the implementation of insurance policies by eliminating many of the timely processes traditionally involved.
Blockchain has the power to optimise the efficiency, security and transparency of the entire insurance industry, with its public ledgers and secure protocols. But the transformation certainly won’t come without its obstacles. There are countless regulatory and legal hurdles that must be overcome by insurance companies before they can fully embrace blockchain technology.
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