According to a June 2020 McKinsey survey, 62% of respondents said they travel less now than they did before the onset of the COVID-19 pandemic. The same survey also found that car purchasing intent in the U.S. is 26% below pre-COVID-19 levels. It comes as no surprise that the current trajectory has had a significant impact on the car insurance industry.
A J.D. Power Insurance Intelligence report from June shows that with fewer drivers on the road, auto insurers have had to return $10 billion in rebates on premiums for policyholders. Given that consumer satisfaction is a key retention indicator for insurers, it is shocking that the same report found that consumers are, on average, 20% less satisfied with their insurer today, despite the rebates.
What does it take to improve consumer satisfaction and turn things around for the auto insurance industry during market downturns, especially those created by unforeseen global events?
COVID-19 has shifted consumer behavior, but most auto insurers have struggled to respond to those behaviors quickly enough. Moreover, providing consumers with the insurance bundle they need, at the time they need it and at a rate they can afford remains a long-lasting challenge for many insurers. For most, purchasing any insurance remains a negative experience, a testament to an increasing gap between consumers and insurers.
Insurers need personalized product offerings and competitive rates that are responsive to consumers’ financial needs and preferences. This can be achieved through an integrated real-time automated solution that uses proven analytical models, artificial intelligence, and machine learning, in a way that accelerates rate-execution. Automation can enable insurers to keep up with their customers' expectations, earn their trust and retain their business.
Tale Of Two Consumers
Let us take the case of two consumers who are in the process of re-evaluating their auto insurance options. The first consumer gets insurance from a company that has deployed an AI system to adapt product offerings to consumers’ needs in real time. In reality, to do that, an insurer must have sophisticated data analytics and machine learning models to run what-if simulations and real-time monitoring of prices and rates. Iterative deployment of such a capability is best done through a single integrated system, creating and providing analytics-based rates directly to the consumer. This insurer can offer the right rate, and the right insurance bundle, through the right channels, at a time when the consumer needs it and at a rate they can afford.
This consumer is already more likely to stay with their current auto insurer. One reason for that is improved and seamless customer experience as a result of spending less time deciding on the coverage and negotiating a rate. Personalized insurance coverage at rates that fit driving habits and financial circumstances are enough to begin earning consumers’ trust and make their insurance purchasing experience easy.
The second consumer works with an insurer who does not use solutions that are advanced enough to provide product personalization, analytically-driven rates, or identify a point in time at which to incorporate changing consumer needs and preferences into the insurance offering. This insurer provides some of the above, but not in an integrated way that allows the insurer to monitor shifts in consumers’ financial preferences and needs, detect their current insurance needs, or proactively offer them new products, rates, or premium relief.
An insurer that does not have advanced product personalization capabilities is more likely to provide consumers with an array of bundles to choose from because the product offering was not created based on what the consumer needs and can afford. This consumer is left to decide from several product bundles and is offered a rate that might as well be arbitrary.
With the digital nature of today's insurance market, consumers can easily compare rates and products on their own. If an insurer is not offering the best rate and product offering in real time, they are at serious risk of losing customers. It’s reasonable to think that the second consumer is more likely to shop around for rates and products. If they decide to stay with their insurer, they are probably more likely to be offered a rebate to make up for what is often an unsatisfactory experience. Both scenarios result in some loss for both the consumer and the insurer.
Bridging The Gap Between The Consumer And The Insurer
When evaluating data analytics systems to adopt, insurers should seek out technologies that assure fast, agile and automated deployment of pricing, rating and product personalization. Additionally, the analytical systems should continuously monitor performance, updating product and pricing strategies accordingly. Iterative deployment is of significant value because the software solution can begin to realize benefits faster. Advanced systems can also monitor market conditions, enabling auto insurers to provide consumers with highly personalized products that are updated as their needs evolve, not after the fact. Auto insurance companies can ensure the right product offering.
There is a need for flexible insurance offers and rates that can be adjusted on a monthly rather than a yearly basis. Insurers can achieve a flexible and agile approach through automation in both the rate-execution process as well as in monitoring changes that may affect rates.
Failing to adapt to the challenges that COVID-19 has uncovered can cost an insurer their business. Conversely, adopting a fully systemized, automated analytics solution can offer auto insurers the tools they need to better serve consumers during and beyond fluctuations in the market.
Udi Ziv is CEO of Earnix. Udi may be contacted at [email protected].
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