AI-powered chatbots will eventually emerge as a dominant digital channel through which customers interact with their insurer but the human touch remains critical in life insurance. Mr James Tan, CEO of Tokio Marine Life Singapore (TMLS), shares his thoughts on the hybrid advisory model.
Fuelled by an exponential increase in technology investments, Artificial Intelligence (AI) is accelerating change across the industry. There are several exciting innovations on the horizon today – a selfie that can predict a customer’s life expectancy in a few minutes, and an Internet of Things device that pairs with motion detectors to raise alerts when a person is at risk during their daily life.
One of the most exciting opportunities we envision is AI as an insurer’s digital ambassador to customers, agents, employees and business partners alike.
This was highlighted in a recent Accenture survey, and has been taking shape in Singapore’s insurance landscape. Recently, TMLS launched TOMI, the local industry’s first self-learning chatbot, which provides explanations of insurance terms and information on products. Our aim is for TOMI to simplify insurance for the public, and to prepare people for more meaningful discussions with their financial advisers. This will help empower them in making more well-informed decisions on their financial planning, and managing their life insurance coverage more independently.
TOMI represents our vision of the future of Singapore’s life insurance sector. This is a future in which customers continue to be at the core of the business – where intelligent AI-powered chatbots will eventually emerge as a dominant digital channel through which customers interact with their insurer. This is a natural evolution from the digital channel of websites and mobile applications, as customers become increasingly comfortable in their interaction with chatbots like Apple’s Siri and Amazon’s Alexa.
But the human touch remains critical in life insurance – as a benchmark, a large majority of wealth management customers still consider face-to-face interaction important. We are therefore seeing the emergence of a hybrid advisory model, where the chatbot acts as an initial digital touchpoint that helps to familiarise customers with their insurer. This helps lay the foundation for the next step in the advisory process – where customers can share their financial concerns with their advisers, and receive recommendations tailored to their needs and sentimental considerations.
There are several advantages to this hybrid advisory model. In the short run, chatbots address the issue of high-volume, high-frequency customer enquiries that can be easily answered. They are easily scalable, with the ability to help thousands of people at the same time. Depending on the technology used, this may be possible even when users pose complicated or grammatically inaccurate sentences. Technology such as Deep Learning for Natural Language Processing (Deep NLP) enables TOMI to understand and answer grammatically inaccurate questions, even if they are posed in Singlish. These advancements grant TOMI abilities beyond the usual chatbot, which relies on keyword recognition or requires grammatical accuracy.
The long-run advantages to the hybrid advisory model lie in the significant value-add of chatbots for customers and advisers alike. Chatbots like TOMI can help customers to focus on more complex discussions with their advisers, allowing for more relevant interactions in their conversations. This enables our frontline team to focus on pinpointing our customers’ most pressing concerns, and coming up with solutions for them.
The key challenge lies primarily in nurturing a seamless partnership between advisers and chatbots, to fully realise the advantages of the hybrid advisory model. While a large majority of insurance executives already agree that AI will revolutionise the way they gain information from and interact with customers, insurers must find the right balance between the adviser’s human touch and the chatbot’s abilities. They must also be ready to address any bias or privacy concerns, and train employees to optimise their resources. The potential gains are tremendous, be it in customer engagement, operational efficiency, or risk reduction.
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