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Chatbots Across the Insurance Lifecycle

by Niraj Choudhary

Rapid advancements in artificial intelligence (AI), machine learning (ML), natural language processing (NLP), and the increased use of messaging platforms are reshaping customer expectations. Approximately 40% of internet users worldwide report that they prefer communicating with virtual agents and chatbots compared to human interactions. Marketing inquiries, transaction processing, and payments are some of the fastest growing uses of chatbot technologies.  Recent research suggests that spending via chatbots will reach $142 billion by 2024, a significant increase from just $2.8 billion in 2019.

Chatbot Adoption in Insurance
According to the Global Consumer Insurance Insights Survey, insurance consumers worldwide have expressed a strong interest in engaging with insurers via digital channels. Insurers must develop and deploy new solutions to address these changing customer needs, leverage data effectively, and respond to industry trends in real-time, at scale, and across distribution channels. NLP chatbots are a great place to focus, as they allow for digital engagement, real-time communication, and can understand user intent and contextualize responses based on user queries. These chatbots can render a greater degree of personalization across varied customer touchpoints, including:

  • Answering frequently asked questions (FAQs)
  • Generating sales services and quotes
  • Receiving claims and updating policyholders
  • Providing account information
  • Facilitating customer feedback

AI and ML-based chatbot integrations are able to use massive datasets to streamline and personalize customer interactions, and can even learn and improve through user interactions, thereby improving the effectiveness and accuracy of future interactions. By integrating with AI-enabled digital customer service (DCS) tools, insurers can also optimize omnichannel engagement across the insurance lifecycle to augment claims and resolution processes.

Chatbot Implementation Across the Insurance Value Chain
Recent research suggests that AI-driven bots will drive 95% of customer service interactions by 2025. This represents a significant opportunity for insurance organizations to either implement a chatbot or upgrade an existing one.  These tools can play a vital role in acquiring, engaging, and serving customers as well as optimizing the customer journey across all purchase phases.

  • Pre-Purchase: At this stage customer traffic to chatbots is at its highest. Chatbots deployed at the pre-purchase stage must be adept at sourcing leads, educating customers, generating quotes, and recommending products or services. Basic chatbots work well at this stage, reducing the need for staff interaction in the pre-purchase phase, providing cost savings, and focusing on transactional needs rather than informational ones.
  • Purchase and Post-Purchase: In these stages the focus shifts to policy quotes, payments, documentation, policy endorsements, and customer service needs. More advanced chatbots are needed for these types of engagements – ones that can process documents, detect discrepancies, analyze images (or even videos) to determine liability, and perform damage assessments. These types of chatbots can also provide policyholders with information about their coverage, deductible, and premium information.
  • Claims: First Notice of Loss (FNOL), claims tracking, claims information, and education are all critical elements of the claims function, and advanced chatbots should be deployed to address policyholder needs at this stage. These chatbots can assess the nature of a submitted claim by interacting with the customer, source details from the insurer’s CRM system or a central database, ask the policyholder for additional information, and initiate the claims filing process. Advanced bots leverage NLP to allow insurers to derive maximum value from advanced claims processing capabilities.

Challenges to Effective Chatbot Implementation
AI, ML, and NLP-based technological solutions can transform the insurance industry, remove manual dependencies, and enhance the overall policyholder experience. However, insurers face several challenges when it comes to the successful implementation of these tools.

Data Silos and Lack of Quality Data: Organizations that retain data in silos will find it challenging to realize operational productivity, execution, and collaboration gains from chatbots. A survey conducted by Dataconomy found that training AI systems is more challenging with poor quality data. About 40% of failed AI implementations did so during the data training phase, suggesting that starting the process by building a strong foundation of data is critical.

Expertise and Technical Competence: Possessing the requisite skills for AI, ML, and NLP-based transformation is one of the major barriers to the successful implementation of these technologies. Insurers must consider vendors with proven expertise in the technologies being used to realize the full potential of chatbot assistants built on these platforms.

Ongoing Commitment: While chatbots can make effective interactions with policyholders, a poorly maintained or designed system can lead to bad experiences and loss of customer trust. Thus, it is important to analyze the customer journey to identify where chatbots can yield maximum benefits and invest in the maintenance and upgrading of the system to prevent issues.

The Future of Chatbots in Insurance
Investing in the deployment of front-end, customer-facing technology is key to improving sales, retention, customer experience, and cost management. As chatbots move to a higher level of maturity and can handle end-to-end complex and multifaceted interactions, insurers need to shift their approaches from reactive to proactive. Augmented situational awareness and integration with other new technologies will create new product categories. Additionally, there will be a greater emphasis on real-time service delivery, consistent pricing, and exponential improvement in customer experience. Collaborating with technology partners with extensive experience in the insurance industry, and the ability to create interactive, scalable, modern, and cost-effective chatbot solutions is key to driving operational efficiency across the insurance value chain.

Niraj Choudhary is a product manager in the Digital Transformation Unit.

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