Navigating a perilous road
It’s a tough time to be in auto insurance. Historically, insurers have often struggled to turn a profit on auto insurance policies, but post-pandemic economic conditions have only further undermined combined operating ratios. Supply chain issues, sticky inflation, and the rising number of claims all continue to put upward pressure on operating costs. And premiums aren’t keeping pace. While motorist may have to live with premium increases of 16% or more this year, insurers aren’t daring to raise rates significantly due to the current cost-of-living crisis.
To add to the trouble, the industry’s very structure is changing. According to McKinsey projections, technological advancements are likely to significantly disrupt the auto insurance risk pool in the U.S. by 2030, leaving traditional insurers with a shrinking share of value. Already, new technologies, including AI-driven opportunities, are opening the door to competitors from outside the sector who are enticing customers with innovative new products. These include:
- Big Tech players with their native expertise in data and their relentless drive to offer seamless, integrated, and high-value services to customers
- Auto manufacturers and brands, which are already using sensor data and their network of dealerships (for repairs and parts) to build stronger lifetime relationships with drivers
- Neo-banks and other emerging fintech companies, such as Revolut in Ireland, which is offering discounted policies to safe drivers based on data collected from telematic devices
The race to innovate
The race to provide more personalized, flexible, and cost-effective policies is on. But so far, traditional insurers are slowly accelerating when they should be putting the pedal to the metal. On the positive side, they’ve recognized the need to offer differentiated, personalized services and add-ons to retain profitable customers. Recent research by industry analyst IDC found that 72% of firms surveyed are prioritizing digitalization, and over half are investing in products that engage drivers more frequently—everything from speed alerts to advice on crossing borders.
However, few firms have prioritized the real-time and contextual experiences that those in retail, automotive, and other sectors are deploying. Only a minority of leaders are creating consistent, automated engagements across channels that boost customer loyalty and are cost-effective to deliver. According to the IDC report, just a third of respondents said they’re developing products for the wider sharing economy—one of the most important drivers of growth in digital markets. Only one in five has current plans to share data across internal functions, let alone the wider ecosystem, and one in ten is prioritizing the segment of one in their marketing.
Clearly, insurers must adapt quickly, or they could find themselves disintermediated from direct customer relationships—and cut off from the sources of incremental revenue that make auto insurance commercially viable.
Opportunities under the hood
Modern vehicles are packed with sensors that not only provide continuous performance data but also offer insights into individual driver behavior. But the "black boxes" used by some insurers are becoming outdated in terms of the type and amount of data they can provide. There's already talk of vehicles self-reporting accidents direct to insurers. The opportunity—and the necessity—for insurers lies not only in using this data for personalized quotes and usage-based policies, but also in imagining a wide range of additional services tailored to customer segments of one.
Last year, McKinsey outlined a hypothetical journey for a U.S. auto insurance customer, envisioning real-time risk calculations and liability shifting among different insured parties based on autonomous and semi-autonomous driving, with second-by-second policy pricing. While these services aren't yet available, the technology to make them achievable already exists. Teradata is working with Volvo to integrate and analyze data from hundreds of sensors on tens of thousands of vehicles in real time to inform product development and customer service offers. There's no reason why similar data and techniques couldn't be applied to reshape auto insurance norms and create innovative products.
Pulling ahead with data in the driver’s seat
If traditional auto insurers want to compete with the innovative companies entering the market, they must quickly accelerate their use of data for automation, machine learning, and AI. By collecting and analyzing customer, telemetry, and mobility data and leveraging analytic insights from the broader ecosystem of partners, insurers can better understand customer behavior to improve customer engagement and create more value.
To survive and thrive in the AI-driven decade ahead, insurers must transition from the traditional annual renewal and customer contact cycle to “always-on,” real-time relationships, continuously offering new products and services that create digital bonds with individuals at their point of need. Achieving this requires cultivating a data culture and investing in an enterprise-wide cloud analytics and data platform for AI that offers the speed and scalability to analyse billions of data points in real time.
Teradata collaborates with leaders across industries to deploy AI-driven initiatives and advanced analytics that integrate and model data from multiple sources to accurately predict individual behaviors—and therefore risks. Our solutions empower companies in a wide range of industries, from retail and telecom to automotive and financial services, to harness their data to automate processes and deliver personalized products and services profitably at scale. Reach out to the EMEA Insurance Industry consulting team at Teradata to discuss how we can help your organization navigate today’s rapidly evolving landscape—with speed and confidence.
This is the third article in our miniseries on data and analytics and their crucial importance for the insurance sector. If you haven’t already, also check out the first two articles covering AI innovation and analytics and pricing climate risk.
