Sprout.ai: Leveraging AI to improve the claims process

VP of Sales at Sprout.ai, Lawrence Buckler, says: "For insurers, it’s important to get the balance right between settling a claim quickly with AI, whilst also checking for cases of fraud and giving the all-important human touch at a time when insurance consumers are at their most vulnerable"
InsurTech Digital speaks to VP of Sales at Sprout.ai, Lawrence Buckler, about ways AI can be leveraged to improve customer journeys in the claims process

AI has dominated the way businesses across all sectors are solving problems. According to Atomico’s latest ‘State of Tech’ report, we are in an “AI supercycle” that will drive a golden age of innovation. The technology is undoubtedly shaking up industries, and insurance is no different. 

We speak to Lawrence Buckler, VP of Sales at Sprout.ai, who discusses how to find the right balance when applying AI to customers’ insurance claims processes. We ask how it is already being leveraged, and where specifically it should be used to improve consumer journeys. 

How is AI already being implemented in the insurance space? 

AI is undoubtedly revolutionising industries. Our recent report shows more than half (59%) of insurance companies are leveraging generative AI alone. 

Lemonade UK hit the headlines by breaking the world-record set by their mothership, Lemonade, by settling a claim for a stolen bike in 2 seconds – the fastest in insurance history. While this is an impressive feat, there’s more at stake to consider. 

For insurers, it’s important to get the balance right between settling a claim quickly with AI, whilst also checking for cases of fraud and giving the all-important human touch at a time when insurance consumers are at their most vulnerable.

How can AI improve efficiency?

During Lemonade’s record-breaking settlement process, AI Jim, the company’s advanced AI-powered chatbot, quickly assessed the claim, checked the policy conditions, and executed several anti-fraud algorithms. 

In an ideal world, this would be relatively straightforward, with all the necessary data at hand: clear images, obvious policy solutions, and watertight evidence. Undoubtedly impressive, this is a rare case; the average claim across insurance lines is far different. 

The legacy nature of the insurance and the claims process has made for the slow uptake of innovation in the industry. Providers have been hesitant to embrace AI because of its perceived overriding of human talent. 

However, AI enhances, rather than overtakes, human capabilities. Though an anomaly, Lemonade UK’s success is a case of this. 

However, the context of the claim itself should be assessed – was it a digital first-notice-of-loss, did Lemonade UK have access to all of the data required before processing the claim? Had the insurer made any assumptions as soon as the claimant made the claim, before collecting data?

How should AI be leveraged? What is the right approach to take? 

For many claims processed by AI, machine learning is a vital component that will improve the overall claims process by contextualising the data from unstructured forms with almost 100% accuracy, cross-checking it with policies and providing a recommendation to conclude a claim efficiently and accurately. 

By providing claims handlers with precise and immediate information, it allows them to spend more time with customers. And this last part is key – AI in itself isn’t always the answer; some claims, like complex health matters, will always require a human touch. 

It’s undeniable that AI brings huge benefits to complex processes like insurance claims, but customer service cannot be about speed and efficiency alone – the human touch is just as important.

Insurance professionals bring extensive and invaluable domain knowledge, experience, and judgement to the table. 

So, whilst AI technology can assist in processing huge volumes of data, identifying patterns and generating insights, human interpretation and decision-making are still required to contextualise and apply those insights effectively. AI is there to augment, not replace, human capabilities.

AI has been proven to successfully automate certain customer service tasks too, such as responding to basic inquiries or performing routine processes, but this does not eliminate the need for human interaction. 

Insurance is a highly complex industry that will often involve nuanced discussions, emotionally charged situations, and personalised outcomes. 

By providing relevant information and recommendations, AI can help claims handlers serve customers quicker, more efficiently and more empathetically. 

Human empathy, understanding and expertise are not ‘nice to haves’ when it comes to giving customers a positive experience – they are essential.

How can insurers strike to right balance between speed, trust and human empathy?

Speed and efficiency are important for insurers and their customers, but they are not the only factors that guarantee top customer service. 

Customer service is all about balance – in some cases, insurance claims cases will require more empathy and quality of care, but in all cases, speed and efficiency of resolution is a top priority for all involved. AI is invaluable to this.

The technology is here to stay, and if insurers aren’t using it to their benefit they risk falling behind the competition. 

It should be used to support the process, though, rather than overtake. Although AI is important for streamlining certain processes, it’s not a silver bullet. 

By bringing empathy, experience and support to customers, an insurance company’s people are – and always will be – equally important.


For more insights from InsurTech Digital, you can see our latest edition of the InsurTech Digital here, or you can follow us on LinkedIn and Twitter

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