Demystifying automation in insurance

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What truly makes a chatbot intelligent

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Since 2016, the masses as a whole have started to become familiar with chatbots. In many industries, including insurance, chatbots are employed to handle varied use cases and some of them, like Zurich UK, became success stories with tangible impact.

Now, living in a world that is comfortable with chatbots and recognises their value, insurance providers are inundated with options regarding the type of underlying technology chatbots leverage and the potential use cases they allow.

In one of our previous blogs “The mysterious link between Turing Machines and Spixii CPA”, we investigated the definition of intelligence in the context of conversational processes from a technical angle. In this blog, we are investigating intelligence at a more tangible and practical level by sharing the four essential requirements a chatbot must have to be considered “intelligent”.

The four ingredients of an intelligent chatbot

At the end of the day, a chatbot is a new digital interface that enables businesses to interact with their customers in a more efficient and personal way. However, only certain chatbots possessing all the below traits will be considered intelligent.

1. Emotional intelligence

First of all, as chatbots are available 365/7/24, they automatically remove the friction of waiting for ages on the phone or compiling a cumbersome web form. This means that by default, they improve the customer experience by avoiding negative emotions at the beginning of the process.

For more advanced emotional intelligence, we have to look at the analytics realm. Similar to a sage who is often pictured as an old experienced individual, so is the wise chatbot, the one that builds its knowledge on past conversations.

In particular, when leveraging infused analytics for real-time decisions, a chatbot will orchestrate the conversational flow according to the demographics of past customers and success rates.

As an example, after running some conversations, the chatbot will be able to select the best tone of voice or conversation flow for a 24-year old male looking to buy motor insurance against a 47-year old female looking to be insured during her travels.

2. Domain expertise

As opposed to emotional intelligence that emphasises customer knowledge, domain expertise is putting the accent on industry knowledge.

If, for instance, the chatbot is executing a quote & buy process for travel insurance, it will need to embed intricate business rules, and have mastery of insurance-specific jargon. 

This domain expertise is an integral part of intelligence since it is not enough for a chatbot to simply understand the customer and their needs as emphasised by emotional intelligence. It must, then, be able to cater to needs and solve problems since that is the true reason why a company employs a chatbot and a customer interacts with it.

Thus, no matter how broad or narrow a niche the chatbot serves, it must have a thorough knowledge of the domain and be able to pull up the relevant information when most needed.

3. Powerful automation

Within insurance, meaningful transactions between a business and its customers generally happen when chatbots are integrated with core systems.

For example, if a customer wants to renew its policy, the chatbot will need to connect with the policy system. Just like we wouldn’t define an operator as intelligent (or at least useful) when they answer with “I am sorry I am not able to help you straight with your query. I need to ask someone else”, so we wouldn’t define chatbots as ‘intelligent’ when they delegate simple tasks.

We, therefore, define the third ingredient of an intelligent chatbot as one that extends and expands its capabilities through meaningful automation of processes and tasks.

Additionally, we can also say that the higher the connectivity of the chatbot with simple automation configurations and with versatile outputs, the more intelligent the chatbot will be.

4. Continuous improvement

Finally, building on the picture of the sage man mentioned above, for a chatbot to be considered intelligent, it must be able to learn from experience. Or to put it in other words, it must be smart enough to become increasingly smarter.

In business terms, this means having a Conversational Process Automation (CPA) platform that enables continuous improvement aimed to enhance the process performance. 

CPA platforms add value by highlighting analytics-driven conversational insights and allowing businesses to quickly optimise their conversational flows. They have certain responsiveness that allows the chatbot to turn information into knowledge that is useful and creates a long-term profitable and positive impact for the business.

The crux of the matter

On the whole,

Intelligence is the ability to adapt to change

-Stephen Hawking

The truly intelligent chatbot will be able to expand the result of its abilities when the business requires it. In short, it will be elastic and scalable in nature. This adaptability is the defining trait of the intelligence of a chatbot. The four ingredients shared above simply enable adaptability and make it possible for a chatbot to keep learning in the right direction which, ultimately, leads the business to grow in the right direction.

Illustration of robot with light beam

Discover Conversational Process Automation

CPA allows end-to-end processing through chatbots and leverages advanced analytics to continuously improve both the underlying process and the conversation with the end-user.

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