7 ways conversational AI can transform customer experience in insurance industry

The pandemic hit many industries in very different ways and insurance is among them. On one hand, COVID-19 brought excessive deaths among policyholders causing claims to reach a staggering $5.5 billion in the first nine months of 2021. On the other hand, insurers jumped in on the digitisation race: the 2020 KPMG CEO Outlook surveyed insurance executives and 85% stated that due to the pandemic, they invested more effort to create a seamless digital customer experience.

However, the digital world poses new challenges that businesses need to address to stay competitive. For example, insurance products and policies can often be complex for customers to figure out on their own. So, to make them more accessible, insurers need to simplify their digital customer experience.

Personalisation of digital CX is yet another business necessity — according to McKinsey, “more than 70% of consumers now consider a basic expectation.” Therefore, insurers must invest in technology and processes that enable them to analyse customer data and deliver personalised experiences at scale.

At the same time, given data breaches and privacy concerns, customers often reluctantly share personal online. This means businesses need to look for new ways to build trust and engage with customers online.

To address these hurdles, many insurers turned to conversational AI and AI-powered messaging options, because they help create safe and transparent space for personalised business-to-customer interactions. Statistics say that four out of five customers are comfortable using chatbots to make insurance claims and prefer them for insurance applications. In this piece, I’d like to explore different use cases for insurers to unitise conversational AI solutions for better customer experience:

Answering policyholder queries

It’s only natural for new customers to ask questions: they need guidance through various products and policies to find the best option for them. Here an AI-powered chatbot can act as the first-line-support agent and answer policyholders’ questions. This spares agents from rudimentary tasks and saves their resources for more challenging ones. For example, chatbot Nauta by Spanish health insurance provider DKV, helps users search for information and instantly answer across its main online channels.

Getting personalised quotes

Even when customers decide to purchase policies, there’s still a lot of matching to be done. Since requirements usually differ greatly from case to case, the insurance industry relies on customisation. So, before agents can recommend options bets fitted to customer needs, they take a while to study their profile and purchase history. However, AI chatbots are irreplaceable when personalisation is key. Powered by Using Natural Language Understanding (NLU), bots can interview customers about their situation and offer insurance products that would suit them best. Thus, Tokio Marine Insurance Company launched Tokio the chatbot to help customers get quotes over WhatsApp, Messenger and the web 24/7 and without human agents' involvement.

Detecting Fraud

Yet another common problem in the insurance industry is fraud. Orepelled by the rising number of cyber attacks, the fraud detection market is expected to reach $12 billion by 2026. Here AI-powered bots can also play an important role. Assisting in checking and analysis, bots can dramatically accelerate claims processing. This way, bots guide customers through the first notice of loss (FNOL) submission. By instructing consumers to take pictures and videos of the damage and then cross-checking the data, bots eliminate potential fraudsters.

Receiving and Processing Claims

However, arguably the most critical insurance processes remain some of the most frustrating ones. Receiving and processing claims is time- and resource-consuming, as policyholders have to reach their insurance provider, fill out necessary forms and file documents. As a rule, to process claims insurance representatives have to collect customer data from multiple sources and manually transfer it to the system. Since human agent expertise is hard to scale, insurers seek to automate claims receiving and processing with conversational AI solutions. For example, Oman Insurance Company relies on an AI-powered chatbot to assist customers in making claims, purchasing insurance plans and renewing policies on WhatsApp and the company’s website.

Fostering up-sells and cross-sells

AI assistants can also augment the capabilities of insurance agents when it comes to upselling and cross-selling services and policies. When integrated with the CRM, an AI-powered assistant can access customer profiles and purchase histories to recommend the policies customers are likely to buy. Thus, businesses can provide personalised information and quotes along with custom recommendations for every product based on product interests and purchase history.

Offering customer support

Current policyholders usually ask questions different from those of new applicants. They may inquire about premium deadlines, renewals and company processes, and expect timely assistance. And account support is yet another great use for an AI insurance chatbot. Paired with the company’s internal systems, bots can easily identify customers and fetch answers based on their account information. Just like chatbot Meli by PFI Mega Life Insurance, which uses an OTP-based validation protocol to verify user ID and help them download necessary documents. When chatbots struggle to find the information customers need, they can always transfer the query to a human agent.

Collecting feedback

Businesses depend on genuine feedback which is often challenging to collect: reaching out to customers and trying to persuade them to answer questions is a tedious task for agents. That’s why insurers often opt for Conversational AI to collect it. For example, voice bots can make multiple simultaneous calls and ask for customer feedback in a friendly manner. Insurance chatbots can gently ask for feedback after the chat. They are more likely to succeed when features like reaction buttons or short questionnaires.

For more information please contact Tovie AI.