Written by: Rajeev Batra, Managing Director – Insurance Practice, Synechron
Nilesh Tambe, Senior Director – Technology, Synechron
The pandemic accelerated the move to customer self-service, a trend that was already on the upswing. But a greater share of customers now expects the availability of 24/7 servicing and access to products, without exception. Artificial Intelligence-driven conversations with customers has similarly become a top business priority for many financial services enterprises, including the Property & Casualty insurance services sector.
Customer-to-Business conversations have evolved into the digital realm. With the help of today’s sophisticated artificial intelligence tools, digital chat platforms/interactions, intelligent chatbots, third-party messenger apps, and voice assistants have become a critical communications channel. Artificial Intelligence, Machine Learning solutions, and advanced Natural Language Processing tools have successfully been leveraged by big organizations and smaller, digital-first InsurTechs for conversational interfaces.
Faster, better service and responses
Similarly, insurance companies can now better understand the sentiment, intent, context, and highly specific request of a particular customer query. Granular data collected can be deeply analyzed and an exact pre-determination made as to what best response to offer based upon the query. Moreover, forward-thinking organizations can not only more appropriately respond with greatly tailored answers, highly specific next step directions and the best possible assistance, but also allow conversational bots to detect a strong dissatisfaction, problem, or concern from the ‘tone’ of a customer’s dialog and language. This necessary, but invisible to the customer, detectability allows a conversation to rapidly be elevated, and routed to a real person for human interaction and rapid remediation of a problem or situation. In some cases, the AI-led detectable tone of a customer’s query can proactively anticipate and predict next questions or deeper needs. This allows insurance businesses to better address a customer’s requirements and future needs, as well as provide cross-selling and up-selling opportunities. Such an early detection mechanism also allows for quick human intervention when needed to soothe anger, tackle frustration, and prevent unsatisfied customers from forever departing (and telling their entire universe about their dissatisfaction and departure).
Benefits on both sides of the AI-led chat
Of course, having enabled third-party, online automated chats is not exclusively for the benefit of the insurance customers. While these chatbots can greatly enhance the customer experience, they also benefit P&C insurance enterprises and enable an omnichannel strategy. At peak times of customer activity, such as after a storm or major incident, AI-enabled conversational bots can ease the burden on call centers, customer service lines and insurance agents. Furthermore, distanced, touchless communications due to the pandemic have allowed customers to test drive, use and quickly learn to enjoy the mobile/online automation feature as they discuss issues, requests, claims, new insurance, etc. Collectively, these can help lower the headcount costs for insurers, and translate into heightened operating efficiencies.
Smart Voice Assistants have also been deployed to answer policyholders’ standard questions or allow for certain use cases and making minor policy changes such as a change of address. P&C insurance providers have realized the benefits of enabling tools, such as Google Home, Amazon Alexa, and communications channels such as WhatsApp, to communicate one-to-one with customers in today’s 24-hour digital landscape. What’s more, some have embedded virtual assistants and video collaboration tools into mobile devices to allow for on-the-spot damages to be recorded and communicated, or communications to be initiated.
AI-enhanced conversational chat capabilities can also be deployed under a multi-cloud hybrid strategy which can offer an additional level of benefits, including ensuing being “always on”.
What you need to consider:
Considering implementing an AI-enhanced conversational chatbot for your P&C insurance company’s needs? Here’s what savvy CIOs and CTOs need to ponder:
- Set objectives for your Conversational AI chatbot — Decide if you wish to implement one or possibly two chatbots – one for external customers and a second for internal company-to-employee communications
- Determine your target customer demographics — Which segments/audiences/users do you wish to engage with, and identify the value proposition for each
- Define your overall Conversational AI chatbot concept – Decide if automated responses will be reactive or proactive (such as to suggest a product/service solution), the types of use cases to be handled, and what you want your customer journey to look and feel like
- Craft your chatbot channel strategy – Will you chatbot deployment kick in for a chat for calls or video, one for only searches, and will you own each chatbot channel or leverage a third-party platform? Will you offer an omnichannel approach that allows customers to continue a single chatbot conversation even if they switch to another appliance?
- Establish parameters and use cases early on – Will customers be allowed to make only certain changes to their policy data (i.e., change of address) and/or receive pre-determined best responses to pre-approved queries from an answer repository? It’s also key to define all situations identified as high priority items which will require human interaction and rapid transfer to a call center/agent
- Define your success metrics – What parameters will be used to determine your chatbot’s success – customer satisfaction, engagement/performance results, degree of personalization, reduced costs/positive financial impact?
- Recognize chatbot limitations – At the moment, voice- and language-based chatbots are not the most eloquent solution for businesses that cater to multi-lingual audiences. Requests, instructions, and issues can be misinterpreted or misunderstood due to accents and other linguistic variations and potentially trigger an incorrect transaction or response. Caution should also be taken where older/senior customers who are not as tech savvy interact with a chatbot. But the learning curve continues as solutions to these issues emerge.
- Encouraging customers to utilize quick and easy online channels
- Improved customer experience
- Reduced call volumes and operational costs
- Improved accuracy and consistency
- Extraction of customer insights that enable cross-selling across multiple business units