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Conversational AI in Insurance: Key Features, Benefits

Peiru Teo

Peiru Teo

Learn how a conversational AI in insurance can proactively engage prospects, process claims, provide personalized customer service and generate leads on autopilot.

It is common knowledge that conversational AI or ‘virtual assistant’ solutions help improve the customer experience by automating conversations. In the case of conversational AI in insurance, it is not just about automating direct communication with customers.  

Insurance providers today have many more stakeholders to manage than before. They also do not always sell directly to their customers. There are multiple distribution channels with various stakeholders, including 

  • Policyholders, who are individual end consumers 
  • Financial consultants or insurance agents who sell on behalf of the insurer, as well as agency management 
  • Independent brokers who sell multiple insurance products from different firms  
  • Bancassurance where banks and financial services providers sell insurance products 
  • Corporations and their HR teams who provide medical insurance to their employees 
  • Digital channelsE-offerings where they sell directly to consumers online through self-service 

conversational ai in insurance: insurance distribution channels

This creates several touch points and communication channels for the insurance provider to monitor conversations in, opening up opportunities for automation through conversational AIs. Here are some of how conversational AI can help insurance providers. 

Keeping Agents Informed and Updated

No matter how the agents are involved in the distribution of insurance products, they need the most accurate and up-to-date information from the insurance firms. Even the most experienced agent can be expected to need help in understanding the details and definition of products and terms before they can advise potential customers. Examples include the change of definition of critical illnesses in Singapore. Being precise and correct can be the difference betweea policyholder being covered or rejected. 

Hence, many forward-looking insurance companies are always exploring technologies that can improve the productivity of their agent workforce and conversational AI is ideally suited for this purpose.  

Conversational AI solutions can help insurance firms support their agents on various tasks such as 

  • High volume enquiries and transactions such as policy loan values, updating of particulars, upgrades/downgrades of plans, change of payment methods and policy status 
  • Notifications on updates to policy changes and definitions such as in the case of critical illness packages 
  • Clarifications on the latest updates and initiatives, or sudden ad-hoc issues like a temporary shutdown of agent portals for maintenance  
  • Complex products and their many versions and sensitive information like the nomination of beneficiaries 
  • Locating the right forms and help on how to fill up certain forms 
  • Finding the definitions of key terms 

Enabling Self-service for End Users

In some cases, insurance firms will look to decrease their reliance on the agents, for basic servicing tasks, or if some agents are less active in client servicingFirms can help strengthen the clients’ loyalty and engagement with the company, on top of the  relationship with the agents. This can help in client retention in the long run. 

Consumer expectations are also changing today. In the past, their first instinct might have been to approach an agent. But today, consumers are savvy enough to do their research online, compare quotes and know exactly what they want even before consulting and agent.  

This offers insurance firms the increased opportunity to deal directly with consumers through e-offeringsConversational AI solutions can form an integral part of these e-offerings as they are available 24/7 for policyholders who expect convenience and quick support.  

Such self-servicing through bots can help consumers and policy holders in a number of ways: 

  • Education and awareness of products: Due to the complexity of insurance products and the constant updates to clauses and riders, it is not uncommon for policy holders to be unsure of the exact details of the policies they have purchased. This situation can be avoided through an interactive Q&A through a conversational AI, where potential customers are educated on the products before they go ahead to purchase.
  • Policy recommendations personalised to individual profiles: When it comes to the purchase stage, conversational AI bots can also help customers do away with looking up menus and filling in forms to find the right product. Instead, they can be guided through a conversation to collect relevant info about their individual profiles and be shown a suitable product that fits their needs.  
  • Document upload and verification for claims processing: Bots can also accelerate claims processing by prompting users to upload their documents within the interface itself. The bots can analyse pdfs, photos, or videos to determine their validity and continue to processing. 
  • Redirection to their agent for further discussion: Often, the policy holders may be more comfortable dealing with agents or may need a second opinion from them. In these cases, bots can also help them remember their agents and connect the two together. Systems can also offer co-browsing options, where agents can guide customers in completing the purchase or claim process online.

Supporting Call Centre Operations and Customer Service

Large insurance firms often employ a team of customer service representatives in contact centres to support customers. With the volume of enquiries coming their way, from simple queries on opening hours and retrieval of policy information and end to end transactions, these contact centres can get overloaded.  

Conversational AI systems can automate more than 80% of these interactions and leave only the most pressing enquiries for the support teams to deal with. Intelligent bots allow insurance providers to handle the most common queries easily, pre-screen customers to enhance the efficiency of live agents and match the high priority cases to relevant business units for more personalised follow-ups. 

Compared to phone calls where agents can only talk to one customer at each time, when handling live chats, an agent can easily handle two to four sessions concurrently. This could increase productivity by 200-400%. Adding onto the 70-80% of queries that the conversation AI agent can handle, the team of human agents and the AI agent can potentially increase overall handling volume by 20 times or more.

Ensure a Seamless Omni-channel Experience

In addition to phone calls to call centres, an insurance provider may also keep other channels open for consumers. Email, social media channels, messaging apps like WhatsApp are common ways that consumers use to communicate with their providers. Many providers still rely on physical mail letters for communications and sending of policy documents 

But if these channels are distinct and their management siloed, it can lead to a bad customer experience. For example, consider a common scenario of someone trying to get help in updating their particulars with an insurance firm and renewing their policy. They might first ask about the procedure through a social media channel and be directed to the web page for submitting the request through a form.  

They fill up the form with their details but let us assume they do not receive a confirmation email. They try dialling the customer service representative to check if everything was in order and in the phone call they are asked to repeat their personal particulars for verification. Depending on the number of attempts to resolve the ticket, they might have to repeat their identifying information a few times. 

This does not make for a good customer experience overall, even if each stage of the communication did what was expected. A true omni-channel experience occurs when all the channels operate based on a single source of ground truth regarding the customer’s profile. Conversational AI solutions have the potential to facilitate this by unifying conversations and collecting customer data through one channel, analysing it, and making it available across the entire organisation.

Automate the Purchase Journey End to End

Aside from the obvious benefits in enhancing customer experience, conversational AI can also impact the entire buyer’s journey – from pre-purchase to purchase, post-purchase and in claims processing.   

This is more applicable for scenarios where the products are more homogenous or clearly segmented, such as general insurance products like travel, motor, home coverages. For many of these products, consumers are able and used to going through the purchase cycle online end to end.  

As it is, many insurers spend huge advertising budgets to drive traffic to their purchase sites. Every percentage increase in conversion counts and brings higher ROI to the advertising spend. Every objection, query, or concern that you can help the customer  address, would result in a win win situation for both the customer and the firm. 


We covered how bots can help providers educate consumers, recommend personalised products and support them in their channels as they do their research. In addition to this, conversational AI can also be used for lead generation and upselling or cross-selling from the providers’ perspective. The user data collected through the bot interface can be used by the sales and marketing teams to devise lead generation campaigns and nurturing them down the funnel towards conversion.


Document submission, policy information retrieval and payment transactions can all be carried out through conversational AI. Underwriting is another common use case in this stage, where conversational AI is employed.


Once a customer has been acquired, the scope of the bot becomes more about policy serving. During this stage, the key tasks automated involve responding to general queries, policy renewals, payments and refunds, enquiries about agents and sending alerts and reminders. 

Beyond this stage, conversational AI is applicable during the claims management process. Claims of the first notice of notice (FNOL), validation and assessment are tasks which can be automated through virtual assistants.

Future-proofing the CX journey

Most large insurance providers today are exploring their digital transformation journeys. One of the big initiatives we find among insurance firms is the drive towards modernising their customer experience journey. With the multitude of channels available, resources employed to oversee the channels, and contact centres to manage everything, the cost of servicing can mount quite quickly, compromising ROI.  

PRO TIP: Start off with listing down all the current servicing channels, their pros and cons, cost of servicing and percentage volume you are serving right now. Extrapolate that out by 3, 5 and 10 years. What would you like these metrics to be by then? How would the servicing mix then look like? What are you assumptions and what capabilities will you need to acquire to make that happen? 

Here are some tables that can be used to guide your planning: 

Servicing Channel Unit Cost of Servicing Pros Cons Assumptions and Actions Required 
Facebook messenger     
Website Livechat     
Volume Served and % 
Servicing Channel 

Year 0 

(Current State) 

Year 1 Year 2 Year 5 Year 10 
Facebook messenger      
Website Livechat      

With conversational AI solutions, insurance providers can take the first steps towards future-proofing their customer experience. By automating most of the low dexterity tasks, they can bring down the effective volume in the various communication channels. Some providers are already aiming to go paperless in the near term, while gradually shifting from even phone calls and emails towards conversations in the next 3 to 5 years 

Talk to our expert to learn more about KeyReply’s experience implementing conversational AI solutions in the insurance sector. 

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