Cognitive computing and AI help insurers’ contact center personnel succeed


Cognitive computing and artificial intelligence (AI) present a new set of possibilities throughout insurance organizations, and can provide clear benefits within contact centers. Cognitive computing and AI capabilities are breathing new life into existing applications, creating new applications to provide deep insights and enabling insurers to drive transformation and innovation while achieving better business results. In addition, insurers can leverage cognitive computing and AI to reduce time to value, improve customer service and achieve tangible results.

AI refers to a broad set of technologies that includes machine learning and deep learning, and approaches using these technologies are often targeted at delivering specific answers. Cognitive computing approaches use these same technologies as well as natural language processing and vision systems with a greater focus on extending and enhancing analyses and decisions made by human beings.

Cognitive computing and AI connect structured and unstructured data types, within and outside a insurer’s firewalls, to enable richer, more numerous, and unexpected insights, new business processes and improved workflows, at significantly less cost. The realized value can grow revenue, reduce operating costs, mitigate risk, boost customer retention and loyalty, and improve employee engagement.

What makes cognitive computing and AI systems different?

Our clients often ask us to explain how cognitive computing and AI differ from traditional programmed systems. In our experience, there are three main differences:

  • AI and cognitive capabilities can understand like humans do, and they can recognize nuances, language, the way we speak, and our intended meaning.
  • The technology is able to reason and can consider and infer ideas, form hypotheses, and look for proof or disproof.
  • AI and cognitive computing can use feedback to learn and improve, just like humans do when we get a pat on the back or constructive suggestions.

Cognitive Contact Centers

One great use case for transforming interaction with end clients focuses on the cognitive call center. Customer Service Representatives (CSRs) typically have several large screens on their desks, each with multiple windows that go to a different mainframe or green screen apps with cryptic codes. When a call comes in, customer service reps may key in a policy number into each window in order to pull up the relevant information to answer the question. The calls often take too long, affecting both the customer and employee experience and become costly for the insurer. What’s worse, customers may lack confidence that the rep is providing correct information or sense that their issue was not actually resolved, and they call back just to be sure. The customer receives poor service, and because calls are lengthy and/or repeated, per-call costs escalate.

One initial step in improving contact center effectiveness and efficiency is to help CSRs visualize the data to support the call workflow, including authenticating the caller, organizing the policy admin system’s data, initiating transactions, and closing out the call. This step can quickly equip CSRs with consistent and accurate information in order to resolve the caller’s issue quickly, improving customer satisfaction and reducing average call handling times.

A second step can leverage AI and cognitive computing capabilities to help customer service reps answer more policy and process questions from unstructured data sources, including policies and procedures documents. This functionality further reduces call handling time and improves customer satisfaction. AI and cognitive computing can enable customer service reps to ask questions in natural language, and then use the technology’s “smarts” to figure out intent of the question and then deliver the most probable answers to the CSRs.

A third area to improve contact center efficiency and effectiveness is to enable external customer self-service through chat, voice, and email channels. In this area, cognitive capabilities further extend natural language input and consistent and accurate answers to the external customer interaction style of choice. This results in a more favorable and flexible client experience and significant cost reductions.

Cognitive computing and AI have the potential to significantly improve the way insurers service their policyholders and dramatically improve the effectiveness and efficiency of the way customer service reps perform their jobs.

Evan SalopEvan Salop is the cognitive practice partner for DXC, where he works with clients and offering teams to drive business outcomes through extending and enhancing processes and applications with Cognitive, AI, and Machine Learning capabilities.  Evan is actively expanding cognitive initiatives in injured worker claims, cognitively enabling property and casualty claims, cognitive email automation, and the industrialization of an AI Chatbot to support Virtual Helpdesk.

Warren Hart headshotWarren Hart is a practice leader in DXC’s Enterprise & Cloud Applications team focused on helping clients create new value through digital transformation leveraging cognitive and AI. He has held multiple leadership roles in product management and sales around emerging technologies at both IBM and DXC.

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