INSURANCE
ADVANCING THE HYBRID WORKFORCE IN THE INSURANCE INDUSTRY AI is said to be redefining how customers interact with insurance providers, and according to research, this rings true. As far back as 2017, 80% of insurers in the UK and Ireland anticipated making moderate or extensive investments in deep learning, embedded AI solutions and machine learning over the next three years. While the UK has a way to go in catching up with the US and China when it comes to AI investment in insurance, it’s clear this is an area we can expect to grow rapidly. We know that excellent customer service lies at the heart of good insurance services, it’s not surprising companies wants to invest in new technologies that drive innovation for both customers and employees’ experiences. Today, amidst unprecedented and sudden challenges that have upended industries relying heavily on insurance, it is perhaps unsurprising that many are already looking to AI-powered digital employees and investing in cognitive solutions to upgrade and scale customer-facing processes.
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At the same time, given the nature of the insurance industry, licenced agents play a critical role in being able to legally perform certain functions – calling for a more blended AI-human solution, or a hybrid workforce. So, where can AI be implemented to transform processes and improve operational efficiency and customer service within insurance firms, and how does this affect how licenced experts employed in the insurance sector operate?
Streamlining the customer journey Insurance firms want to make the customer experience of their contact centres as seamless as possible. So, many have chosen to integrate AI at the beginning of the customer journey to help authenticate users and identify the intent of enquiries. For example, a digital employee can confirm the routine information, such as asking “What is your name and policy number?” or “In a few words, describe what we can help you with today?” and get the customer in front of the right agent from the outset.
This again allows human agents to avoid repetitive, information-gathering tasks, in turn improving the customer experience, saving them huge amounts of time, and helping better manage incoming calls routing.
Empowering your staff to take on more advanced roles Digital employees, such as Amelia, whose programming can be personalised to match the specific company she works with, use Natural Language Processing (NLP) to automate common customer requirements at scale, while securing backend integrations with an organisation’s specific data management systems. For example, a customer can get immediate answers to questions like, “When is my monthly premium due?” or “How much would it be to add my daughter onto my auto insurance policy?” and leave expert human agents to handle individualised customer needs.
