Conversational AI Booms In Local Insurance Sector
Conversational artificial intelligence is fast becoming ubiquitous. In fact, global research and advisory firm Gartner predicted that 85 per cent of customer interactions will be managed without humans by 2021. There are many benefits to this: consumers can get instant service; companies can reduce costs; and human agents can spend their time solving more important issues. But despite the global industry moving in a digitised direction for some time, South Africa was slow to adapt, resulting in an industry that was still heavily reliant on call centres to complete sales and provide customer service. That was until the COVID-19 crisis hit.
With the national lockdown forcing greater and more rapid digital adoption in South Africa, companies are seeing AI technology being widely validated by demand from both end consumers and insurers alike.
Matt Kloos, CFO of CompariSure, says the company’s proprietary chatbot technology, which leverages popular platforms like Facebook Messenger and WhatsApp, has enabled traditional heavyweight industry players like Sanlam, Old Mutual and Momentum Metropolitan to have automated, highly personalised conversations with consumers – at scale.
“Not only have sales levels more than doubled since lockdown began, but we have also had a surge in demand from insurers looking to partner with us, and to license and use our conversational AI technology,” says Kloos. “Over the years, our team has perfected the art of partnering human empathy with machine learning to enable financial institutions to seamlessly integrate conversational AI into their service offering.”
Kloos points to two key advantages that the technology offers insurers. “On the one side, customised white-labelled chatbot solutions enable for our insurance partners to have automated ‘chat’ engagements directly with consumers, for either sales or customer service. On the other side, insurers can also sell their products on CompariSure’s e-marketplace, where they gain access to our team’s digital marketing expertise.”
Underpinning chatbot technology is deep analysis of reams of data being generated via authentic conversations. “To date, we’ve had over 8 million touchpoints with end-users,” says Kloos, “with every conversation point and path being analysed so as to improve the customer experience.”
Kloos gives the example of education level to demonstrate how chatbots are getting “smarter”. “As part of our life insurance quoting process, the chatbot asks users, ‘What is your highest level of education?’, with the reply options being: ‘No Matric’, ‘Matric’, ‘Diploma’ or ‘Degree’. Many users, however, respond by simply saying how far they got in school – ‘Std 9’, for example. Initially the chatbot did not understand the term, but after observing this pattern repeatedly, it eventually asked our internal chatbot manager: ‘The user said Std 9. I think they meant No Matric. Am I correct?’”
While this is a relatively simple example of pattern recognition, the impact on society of conversational technology, combined with scientific data sciences, will be vast and profound, says Kloos. “We see this technology as being an enabler and providing a win-win solution for each stakeholder. End users can access a broad range of quality products in the most natural way possible – via a simple ‘chat’ – and insurers can interact with a broader segment of society at a lower cost than before, while also freeing up human agents to focus on more value-added tasks.”
Author link: Matt Kloos
Resources: chatbot technology