The connected car: How data analytics is shaping the future of auto insurance
Article information and share options
In the last of a three-part webinar series, Swiss Re’s P&C Business Management team highlights the opportunities vehicle connectivity brings to auto insurers in Asia. The experts also discuss how data analytics can be applied to enhance the customer experience across the entire insurance value chain.
The automotive insurance industry is experiencing a transformation driven by shifting trends in consumer behaviour and the global push for electric vehicles (EVs), which Asia has enthusiastically embraced.
Perhaps the most significant trend of all is the rise of the connected car, which come equipped with enhanced automation capabilities and online linkages to the entire transport ecosystem through embedded systems and mobile apps. As modern vehicles begin to resemble smartphones in their digital footprint, they are generating large amounts of data on both the vehicle and the driver. Harnessing this wealth of information with artificial intelligence (AI)-driven analytics can enable insurers to optimise the claims process, offer new value-added solutions and deliver a better overall experience for the consumer.
"Traditional claims management processes are often very complex and time consuming. And they're subjective and prone to error because there are many people involved in the process. The data produced and collected by connected cars helps insurers address all of these issues by digitising the whole process," noted Pia Burghartz, Automotive & Mobility Solutions Manager, P&C Solutions, Swiss Re.
Digitising auto claims: A win-win proposition
Connected cars come equipped with telematics systems that collect critical data about vehicle usage and driver behaviour. Insurers are increasingly leveraging these systems with the help of AI-driven apps to receive automatic alerts. In the event of a mishap, the app sends images from the accident site to the insurer. The app’s claims evaluation component then reviews the information to recommend next steps to the driver for a straightforward path to resolve the claim.
As cars get smarter, the volume and granularity of data generated by them is only expected to go up. And with Asia Pacific’s (APAC) connected car market – which accounted for 42% of global market share in 2020 – set to grow further1, it will create fresh opportunities for digital innovation across the auto insurance value chain.
"Data growth, especially real-time data, is expected to accelerate between now and 2024. So understanding and interpreting real-time data is key," said Evangelos Avramakis, Head Digital Ecosystems R&D, Swiss Re Institute Research & Engagement, Swiss Re.
While simplifying matters for the consumer, AI-driven claims processes also deliver significant cost savings for insurers. One Swiss Re client, which manages more than 20,000 claims a year, has reported average savings of US$10-30 per claim after deploying machine learning to aid claims handling. Given the volume of claims insurers handle, these savings have a sizeable impact on overall profitability.
This is a big upside especially in Asia where insurers “face significant constraints in pricing adjustments because the markets are so competitive,” noted Calum Thornhill, P&C Analytics Solutions Manager, P&C Solutions, Swiss Re.
Putting the brakes on claims inflation
The growing availability of data and the power to analyse it are also helping insurers address major operational challenges. Key among those is claims inflation, which is the direct outcome of vehicles becoming more technologically advanced and featuring high-tech parts that can be expensive to replace.
Thornhill explained how this works in real life with a case study on how an automotive insurer used data analytics tools to predict scenarios from non-traditional information sources. The insurer built a parts inflation index based on the changing costs of spare parts and claims behaviour involving top car models, giving them a better understanding of the severity of claims inflation for each model – all in the span of just two months.
This information was used to develop a new price adjustment mechanism that accounts for inflated claims. This method of estimating claims is particularly useful for new insurers who do not have a rich claims history to work with. "Data has the power to really speak. It's just up to us to turn that into action," said Thornhill.
Developing value-added solutions
Besides improving the claims management process, data analytics helps insurers turn real-time data from connected cars into digital offerings that are gaining popularity among consumers.
A prime example of this trend is usage-based insurance2 (UBI), which helps insurers design flexible and personalised pricing options and encourage safe driving by rewarding lower-risk drivers with cheaper premiums, discounts and benefits.
UBI apps3 work by using a connected vehicle’s telematics system to collect information on driving patterns, such as commuting distance and trips taken as well as the propensity to speed and execute sharp maneuvers. The data is analysed to create a risk profile of each driver to help price premiums. Tips to improve vehicular safety and feedback on changes in driving habits, provided via the app’s interface, help increase driver awareness by allowing them to compare their driving behaviour over time or even with other drivers.
In a testament to its growing appeal, APAC drivers are expected to make up over 50%4 of an estimated 60 million UBI subscribers worldwide by 2025. With adoption rates growing rapidly across the region, the UBI market is forecast to reach US$13.57 billion in 20275.
As vehicles become smarter, more connected and automated, insurers are naturally shifting their attention from the driver to assessing the machines transporting them with the help of Advanced Drivers Assistance Systems (ADAS).
The data produced by these systems can be used to create risk-scoring solutions that help simultaneously improve road safety and insurance portfolio performance. They do so by showing how a vehicle’s ADAS equipment influences its safety performance and therefore its insurance risk profile, directly and/or indirectly helping to reduce the frequency and severity of insurance claims, Burghartz explained.
Sophisticated risk-scoring solutions consider a mix of manufacturer specifications, aggregated results from portfolio analyses, crash test data, and computer-simulated accident scenarios that assess the effectiveness of a vehicle’s ADAS. Each risk score generated reflects the current and prospective impact of ADAS on insurance claims, paving the way for a more profitable portfolio. In addition, the scores themselves can be refined and calibrated to the specific needs of each insurer’s portfolio based on their claims data.
"It doesn't matter whether you’re driving an Italian sports car or a Japanese family car, data analytics can be applied across the full spectrum of vehicle models," said Blake Dimitrijevic, Head P&C Business Management Asia, Swiss Re.
Start small, and early, for big results
There are various modular, end-to-end tools currently available to help insurers looking to kick off the digitalisation process. However, the sheer variety of solutions can pose a challenge to those who are unsure of where to begin.
According to Nelson Tham, eAdmin Expert Asia, P&C Business Management, Swiss Re: "Different organisations are in different phases of their digital transformation journey, with varying levels of maturity and capabilities. And there isn’t a one-size-fits-all solution that can be applied across all insurers."
The key then is to focus on a specific area of the value chain and start from there. "There is so much you can do with data. But you need to take a different approach, depending on whether you want to improve claims processing or create new products," explained Avramakis.
There is no doubt however that the ability to make data-driven decisions is critical for insurers keen to differentiate themselves from the competition. “It is important not to wait too long to make the necessary investments. Because it takes longer than you might think to acquire a data-driven mindset,” cautioned Burghartz.
Further, because automotive technology is advancing so quickly, companies that wait too long might find it a challenge to make up for lost time. "This is why starting small then scaling fast might be a good strategy," noted Avramakis.
This recommendation is particularly useful for small to medium-size insurers as digitalisation often involves significant costs, resources and commitment. "Whenever an SME thinks about digitalisation, it intimidates them. But it need not be the case if we start small," said Tham. "They can begin by reviewing their internal processes, see how data flows, turn that into structured data, then analyse this data for more meaningful insights."
Overall, harnessing data and AI-driven analytics can drive significant growth opportunities for auto insurers. And those that successfully mine the rich sources of information to improve the customer experience and their operational processes will see tremendous upside along the entire value chain, the panellists concurred.
As Burghartz noted: "Data is the new oil. It’s necessary to make use of the data at our disposal to thrive in the digital age. Our clients need to think about how to leverage data that comes from the car, and to use this in a way that makes sense."