The automated insurer

In today’s competitive landscape, intelligent automation (IA) is a business imperative.

IA has the power to transform the insurance value chain, create powerful efficiencies, and help insurers respond to mounting market pressures. Yet despite these technologies’ powerful potential, most insurers have stalled in their IA journeys.

Top roadblocks to IA implementation:

  • The rate of technological change. In an industry buffeted by a storm of change, IA seems to add challenge and complexity to an already difficult transformation process. The result is a cautious approach to IA, with insurers investing only in proof-of-concept projects or small-scale implementations.
  • Failure to understand IA’s true value. Conversations surrounding IA too often focus on cost savings. IA delivers critical benefits over and above the creation of cost efficiencies, including boosting productivity and performance, improving quality and auditability, and generating greater employee satisfaction.
  • Myopic focus on niche use cases. With the emphasis on cost savings and automating specific repetitive processes, many insurers fail to see the forest for the trees. Instead, insurers need to develop a holistic approach to IA that can be scaled across the organization.

The first steps on the path forward:

  • Build the foundation for IA. Insurers must understand that IA is transformational, not just another technology implementation. This means insurers must create a transformational vision for the organization and maintain a broad perspective, while optimizing current processes before moving forward.
  • Start small, think big. Organizations need to plan proof of concept projects and early deployments strategically with scale in mind. This includes creating the organizational structures needed for the IA strategy to succeed, and anticipating impacts to people and processes.
  • Use a funnel concept for IA use cases. In order to maximize value and optimize cost on IA efforts, insurers must have an effective process to identify, assess, and prioritize automation use cases across the value chain.

KPMG’s Mike Adler on Intelligent Automation and AI


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