Using AI to Do Insurance Customer Care Right

To provide a positive experience at a stressful time requires insurers to rethink how they approach customer service and explore how AI can improve communications and accelerate claims handling.

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Loss of or damage to property creates stress and often strong emotions, so when a customer calls, ensuring a positive experience requires empathy and immediate answers. Whether filing a claim, seeking policy information or renewing a policy, customers expect service on-demand. Meeting those expectations requires insurers to rethink how they approach customer service and how artificial intelligence (AI) can help improve communications and accelerate claims handling.

Since call center operators are a customer’s first point of contact, having a sound contact strategy is key. How can operators add value to the process and solidify customer relationships? Employing AI and machine learning as part of your contact strategy will help operators to know customers better and ensure a customer-centric focus. In addition, better, more insightful customer data helps insurers tailor their marketing efforts to specific customer groups instead of using a one-size-fits-all approach. AI can also improve data quality across the enterprise, enhancing data governance and privacy by controlling access and preventing data breaches.

AI and machine learning can uncover unknown facts about customers by tapping external data and looking for similarities in internal data to produce a holistic customer profile. AI can analyze calls and identify call patterns that tell operators what types of customers are likely to call with specific questions or requests. For example, if a customer calls with a policy question, there may be a 60 percent chance the same customer will reach out again to the call center or through other channels for information on related topics. Having this information enables operators to proactively provide information, which can reduce call volume and save customer time.

Managing Call Volume

Insurers can address high call handling times for low-value calls using AI to redirect, minimize or prevent these calls to improve efficiency and reduce costs. In most contact centers 40-60 percent of all calls are inquiries that can be handled using chatbots or conversational AI solutions like Alexa or Google Assistant. For customers who lack the time or desire to get information via phone, pushing out content through various social channels or secure messaging platforms may be more appealing. However, it is important that all channels be connected end-to-end.

Understanding cost versus value will also help improve your contact strategy by measuring the returns on the amount of time, money and effort spent on calls. AI can provide transparency into how much of your call center’s time is spent addressing customer needs, adding value to customer interactions or creating value for your organization.

During the underwriting process, AI and machine learning can identify and evaluate past historical positions, capture and summarize relevant information and simplify research. Using AI to automate underwriting audits will catch discrepancies inherent in human decision-making that can significantly impact the bottom line. Predicting claim likelihood through AI and machine learning enables insurers to revise ratings or prove the worthiness of a risk at a certain price point. AI-driven drones and visual recognition can help manage claims and greatly improve the outcome for everyone by expediting the settlement process, improving customer satisfaction, and reducing costs.

It can be daunting to look at the cost of modernizing technology infrastructure in a traditional industry like insurance, since it’s not unusual for call center infrastructure to be decades old. AI does not require replacing infrastructure end-to-end; however, some upgrades are necessary to ensure your technology can support the intelligence needed to provide insights that enable proactive assistance. Rather than replacing an entire contact center system, infusing AI and real-time analytics can provide dashboards with information operators need to more effectively converse with customers and solve problems efficiently.

While AI is not the solution to every problem, it is a powerful tool that can elevate your call center processes, provide deep insights into your customer base, improve efficiency across the organization, and enhance customer experience and satisfaction.

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Bret Greenstein // Bret Greenstein is Global Vice-President and Head of Cognizant’s Digital Business AI Practice, focusing on technology and business strategy, go-to-market and innovation, helping clients realize their potential through digital transformation.

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