By Sanjeev Kumar, VP EMEA at Boost.ai
As industries of all shapes and sizes look to AI, we examine what role can it play in insurance
Artificial Intelligence (AI) is on track to change the face of industries worldwide, and insurance is no different. The pandemic may have kick-started the digitisation of operations, but recent developments in AI have made it clear that adopting a digital-first customer service strategy is a matter of when not if. In these times of financial uncertainty, businesses need to source solutions that achieve immediate customer service improvements whilst also positioning them for long-term growth.
Conversational AI (CAI) is one such solution. CAI can improve customer service by increasing efficiency without sacrificing a personalised approach. For insurance specifically, AI can accelerate the claims cycle and automate customer interactions whilst freeing up human agents to focus on more valuable tasks.
Claims are the bread and butter of any insurance broker but are amongst the most time-consuming responsibilities too. Many customers view the claims process as laborious and unwieldy, but CAI can change that. Modern CAI-powered virtual agents can be easily integrated into existing systems to improve resolution speed through enhanced self-service. Customers don’t want to be put on hold just to update their claims or personal information, and by using conversational AI, they won’t have to be.
It is with the most mundane tasks that AI can have the most significant impact, as these are often the most administratively heavy and time-intensive for human agents to deal with. CAI frees up the human agents to work on more high-touch tasks and can seamlessly hand over a customer for these enquiries. CAI’s integration with legacy platforms ensures that all customer information is accurately maintained across the organisation, addressing data silos that add unnecessary complexity to the claims process. Furthermore, the 24/7 availability of a virtual agent spreads the workload and gives customers access to critical services around the clock.
CAI also reduces the risk of errors and subsequent claims delays, identifying issues with customer policies or claims and providing personalised advice on resolving them – thus reducing the time between claim and payout and improving customer satisfaction.
CAI can use natural language processing (NLP) to automatically interpret customer service requests from either chat or voice channels to handle policy questions and claims enquiries. The CAI can then analyse this data to create more accurate and more personalised responses – the more it fulfils its role, the better at that role it becomes.
But virtual agents don’t have to be customer-facing only. For example, internal chatbots can act as ergonomic interfaces for employees to find relevant information and useful resources during employee onboarding. In this way, CAI can alleviate pressure on workers by automating simple tasks and becoming a trusted virtual colleague.
The benefits of automation go beyond enabling accuracy, efficiency, and reducing workloads within customer service centres. CAI can expand employees’ horizons and offer opportunities to train and improve the programmes internally. Virtual agents require oversight and monitoring to perform their roles correctly. Customer service staff know the customers better than anyone and are vital in optimising that digital-first experience.
Insurers must choose the right CAI solution for their specific needs and adopt CAI as part of a broader AI strategy. There is understandable scepticism amongst insurers about what role AI can play in an industry renowned for its complexity and regulatory minefields. However, with enough self-knowledge of the business, AI can navigate these complexities with ease.
Incorporating conversational AI as a frontline response to customer service extends the service capabilities of an institution and lays the groundwork for continued expansion. Typically, the assumption is that virtual agents are in some way reducing the need for human employees; however, the most effective use of conversational AI is one that strikes a balance between the two.
As the technology underpinning CAI evolves, insurers can provide a more personalised customer experience. Additionally, with the integration of nascent Generative AI models, these technologies will become even better at understanding user intent and pre-empting responses, leading to faster and more accurate answers.
Moreover, the longer that a conversational AI solution spends embedded in a business, the more it learns from the data, so insurers can use the gathered customer data to gain a deeper insight into customer behaviours and preferences, enabling them to better tailor policies for individual customers.
As AI continues to develop, it will become an increasingly integral part of the insurance industry, both internally and externally. Furthermore, new use cases and applications will appear with each technological advancement. Insurers cannot afford to sit on their hands with AI; the alternative is a lower customer service quality and customer base erosion.
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