The insurance industry has paid lip service to AI and machine learning for some time. However, adoption has been underwhelming. As firms come under intense pressure to meet changing customer demands, could this instigate more rapid AI adoption?
Insurers and InsurTechs are taking a long, hard look at the customer experiences they provide. FinTech Global recently spoke to industry executives on how better experiences can be delivered, and the importance of meeting customers’ higher expectations.
One tool in the toolbox is the use of AI and machine learning. Although not new, its adoption in the insurance industry has been somewhat sluggish in some areas. With consumers’ rising expectations for speedy and seamless experiences however, could this provide firms with the motivation they previously lacked to adopt such technologies across the board?
Christopher Sanders, head of customer intelligence solutions at Quantexa said that as more companies provide slick and convenient user experiences, naturally customers are expecting the same level of service elsewhere. “They (rightly) do not understand or care that there might be certain factors holding insurers back from delivering these experiences that don’t apply to the likes of Netflix, Amazon or Deliveroo.”
Jamie McDonnell, sales manager at Novidea, agreed that insurance customer expectations have significantly shifted. “[This is] due to the proliferation of digital retailers like Amazon and progress made with online banking, which has been very successful in providing digital services, via apps, and straight-through processing.”
In fact, Novidea has seen demand for its AI technology take off as of late, particularly since early 2020, since Covid-19 increased insurers’ demand for more remote solutions that can be both efficient and accurate. The company said that in some areas, such as auto damage assessment, AI is being adopted globally, but other areas, such as underwriting, are still falling behind.
Mcdonnell added that it is far easier for firms to adopt such technologies when core systems are based in the cloud, but very few traditional insurers, brokers, and MGAs are in this situation. He added this is why firms look to leverage Novidea’s born-in-the-cloud insurance platform, which provides an end-to-end solution and self-service portals to enhance customer service.
What is the value of AI and machine learning in improving customer experiences?
Udi Ziv, CEO of Earnix said AI, machine learning, and analytics will continue to drive business. “Consumers see only benefits, in getting the exact right offer delivered to them when they need it most. To them, it is synonymous with a great customer experience, if the price and value align alongside great post-sales customer service.”
Possibly the most undisputed advantage of such technologies, is that they can free up human resources, which has positive knock-on effects for the customer experience. According to Ruth Fisk, vice president of strategy, insurance, at Smart Communications, automation, natural language processing and machine learning can be used to make humans more efficient, therefore giving back more time to focus on the customer experience.
“These technologies therefore compliment an insurers effort to streamline processes, automatically identify when a “human in the loop” is needed, combine that with a modern conversation platform that can handle channel shift to meet customers where they are and how they want to be interacted with will provide a dramatic improvement in the customer experience journey,” she said.
Max Stratmann, chief revenue officer, at Scanbot, agreed that AI and machine learning could mean human work for repetitive tasks will become obsolete. “These technologies… will help customers feel treated better because their concerns are taken care of much faster. And the best thing about it is that, given these repetitive tasks can be automated, employees can focus on what really matters: the consumer!”
Jimmy Spears, head of automotive at Tractable, said this capability to “free up humans” means they can be where they need to be in the customer interaction process to help handle escalated incidents, leaving automation to handle more routine tasks. “It means customers are much more satisfied and also that employees can use higher decision-making skills to resolve their customers’ issues more fully and help restore their lives,” he said.
In addition, Ian Jeffrey, CEO of Breathe Life, an SE2 company, said that automation and machine learning enables insurers to be more attentive to a consumers. “Automation and machine learning allows us to be more agile and responsive to the needs of the consumer. It empowers advisors to do their jobs more efficiently, helping them to better understand their customers and serve them better. For instance, advisors can follow customers through their life cycle and see when they may need more insurance protection or a different solution.”
Oliver Bath, head of customer success at Sentiance said these technologies can be used to provide hyper-personalisation at scale. “This is far more effective and efficient than a human, not to mention the right use of technology brings down the cost of premiums to the end consumer.”
A threat to the human touch?
A key concern raised over the use of automation and machine learning, however, is that it takes the human, and therefore personal element, out of the customer experience. When considering that one of the key interactions a customer will have with their insurer is when they are making a claim, and this is likely to be a critical time of high emotions, a human and empathetic interaction may be vital.
However, Quantexa’s Sanders argued that it is not an either-or situation, the aim should be to balance the benefits of automation and machine learning in terms of cost reduction and efficiency with any impact on customer experience. “It’s important to note that in many cases automation and machine learning will improve customer experience, reducing friction in processes and enabling greater personalisation. But there will still be moments where customers need the reassurance of the human touch, for example when they are involved in a catastrophic event. In these cases it’s critical for insurers to get the balance right and ensure the right processes are in place to break out into human interactions.”
Similarly, Scanbot’s Stratman said, “I believe there will always be human customer service for personal concerns that cannot be solved with the help of modern technologies and it is also super important that there is that form of personal contact as when you have to deal with your insurance, most likely, something bad happened to or around you.”
In an upcoming feature, FinTech Global will further explore the role of AI and machine learning in the insurance industry.
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