How Insurance AI Chatbots Are Improving Customer Experience
In 2016, AI Jim (Lemonade’s AI chatbot) set a world record for the fastest processing of an insurance claim - just under 3 seconds and with zero paperwork. By 2022, the global insurance chatbot industry generated an astounding $467.4 million. Insurance AI chatbots are an important part of the growing demand for automation in the industry. In 2023, a Salesforce survey showed that 23% of customer service companies were already using conversational AI. However, the big boom in generative AI in this last year has created greater interest. Will it see more adoption of insurance AI chatbots?
AI Chatbot market trends and forecasts
For most people, the nitty gritty of insurance products is quite difficult to understand. Customers often say that quotes, premiums, and riders are such a complex subject that even after the purchase they are not too sure of all they are covered for. Customer service chatbots that can guide them through the purchase journey and provide them with clear information will make them more loyal to their insurance providers. Not just that, insurance carriers will gain a competitive edge over those insurers who delay in switching from the traditional methods of customer acquisition and retention.
Here are a few market trends in the AI chatbot market:
Conversational AI use cases in insurance
What is an unbeatable marketing technique? Almost every marketing guru will agree that it is treating customers with the respect they need and that’s the reason customer-centric strategies are now taking center stage. Policyholders' and consumers’ expectations have undergone a dramatic change as the world has gone even more digital. Given the rising expectation for round-the-clock service and receiving information almost instantly, insurers are revamping their processes to improve their interactions with policyholders.
Digital marketing has made it possible to reach consumers through a variety of channels. What happens though if a potential customer’s query on any of these channels goes unanswered? The probability is that they will go searching elsewhere to get the information they need. This is why, as part of an overall digital transformation, insurance carriers are leveraging chatbots in their multichannel interfaces. When conversation AI is properly implemented it can provide an ideal environment for a comprehensive guided buyer experience. This can reduce customer friction and generate 5 times as many leads for an insurance provider. It does not stop there, automation is also providing faster claims administration. That’s a happy customer.
The most successful insurance chatbots will be the ones that will drive a conversation perfectly mimicking a human agent.
Here are 3 effective use cases for AI conversational chatbots that insurance providers are in the process of evaluating and implementing.
Automating repetitive queries
80% of inbound customer queries are routine and insurance chatbots can easily resolve these queries while redirecting the remaining 20% to human agents. It is not just customers, the diversity and complexity of insurance products can make it difficult to understand even for stakeholders who might need clarifications.
Most insurance carriers have large contact centers with hundreds of customer support employees. However, the massive amount of queries coming in is difficult to handle for even such a large call center. Tie this in with the fact that the average response time is directly related to customer satisfaction. This is why chatbots are gaining importance. Chatbots, initially can provide the first level of support and allow human agents to focus on value-added tasks.
However, Voice AI has still not reached the level of sophistication to take over completely. 60% of consumers think humans are able to understand their needs better than chatbots. In terms of bot maturity, 67% of chatbots are still at a basic maturity level, 20% are at a moderate level and only 13% are at an advanced maturity level. This data is not surprising given that chatbots are still evolving. It is important to understand that AI chatbots that are having a conversation with you are constantly running statistics to know what to say to you next. They need to keep learning from experience and from large volumes of data.
Chatbots are definitely more advanced than 10 years back and their ability to understand customer needs will keep getting more advanced. There is a caveat here, however human-like their responses may be, the customer must always be informed that they are conversing with a bot and not a human agent. AI chatbots are not sentient and cannot be expected to empathize like a human agent probably could.
Conversational AI as a partner to insurance agents
Tara, the interactive smart bot from SImpleSolve can prompt agents in real-time about high-risk concentrations just as the agent is quoting new business or she could alert that the NB the agent is quoting to was a prior insured with claims. Agents are expected to know it all - the specification of various insurance policies, their coverage, premiums, pricing, term limits, and renewal process. It is difficult for agents to keep up with product updates because there is other information that is coming in as well. They are expected to keep track of promotions, discounts, and new announcements. They often are bombarded with information from emails, portal notifications, and more. In this sea of noise, it can get challenging to find the information when they need it instantly.
Smart BOTS like Tara, can automate routine tasks and trigger transaction workflows with the Bot becoming the interactive display, assisting the agent with stats, show disclaimers relevant to a customer and upselling based on data in the insurance application.
Self-servicing through embedded chatbots on insurance portals
Geico uses a virtual assistant to greet customers and offer help with insurance products or policy questions. A customer service chatbot is a great tool to explain insurance plans. By asking qualifying questions, the virtual assistant can learn the customer’s needs and then recommend suitable plans. Many rule-based chatbots run on such prepared scripts. This is most effective for simpler plans like travel insurance and auto insurance where an embedded chatbot can take a customer through the entire insurance purchase journey themselves. Rule-based chatbots are easier to train and integrate well with legacy systems.
Intelligent chatbots are a more sophisticated cousin to rule-based chatbots and use natural language processing NLP, AI and ML - the same technology that forms the basis of voice recognition systems like Alexa and Siri. Although Voice AI can take longer to train and need large volumes of data to hone their skills, they save time in the long run. They keep learning from information gathered, understand patterns of behavior and have a broader range of decision-making skills.
For successful outcomes in these use cases, there is an underlying criterion. In insurance, a chatbot should ideally connect with all internal systems but that might be a tall order. Definitely, they need to connect with key systems to get the most value in bot-customer interactions. For example, they should integrate with document management tools, policy management software, CRM systems to track customer interactions and feed into sales pipelines. Finally, conversational AI bots will also need to connect with claims software.
This blog is the 4th in the series we are covering about 7 technology trends reshaping insurance in 2022 and beyond.
Topics: AI Chat Assistant