How insurance leaders can strategize for the post-digital era

How can insurance leaders create strategies for the post-digital era – a time when digital, like electricity, has become pervasive and no longer a differentiator in itself? How can they discern which emerging technology to invest in, and how to apply it? The latest Accenture Technology Vision for Insurance report provides several examples of insurance companies that are leading the post-digital shift.

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Insurers are often ill-prepared for ecosystem partnerships

Ecosystem partnerships offer insurers huge opportunities to strengthen their businesses and drive up profits during the next five years. By combining their operational expertise, technology resources and industry knowledge with strategic partners, insurance providers can capitalize on the digital disruption that is sweeping all sectors of business. They can increase their capacity to innovate, access new markets, reach additional customers and boost revenues.

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Improving the Wellness Value Chain: Using data to create better outcomes

Traditionally, treatments such as massage therapy, yoga classes, or even acupuncture, were rarely considered an important part of the wellness chain—and getting insurance providers or employers to pay for them as a preventative measure was difficult. In recent years, however, more understanding has emerged about the value of these types of wellness treatments, both in terms of injury prevention and claim avoidance.

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Data built for advanced analytics

Data is the lifeblood of insurance. But the enormous potential of this key resource is outstripping insurers’ current capabilities. It’s no longer just about prioritising data for management information (MI) and business intelligence (BI) applications. Of course, these remain vital functions. But it’s data’s role in machine learning that will increasingly define winners and losers in this industry – powering the prescriptive analytics that allows firms to pinpoint ‘next best actions’.

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Putting Predictions to Work: How Structured and Unstructured Data Come Together with AI

When we think about the vast amounts of patient health data, it tends to be in the abstract—a complex matrix of information that is difficult for a human to decipher in a short timeframe. It is simply too much information to consider. But with AI, there is an opportunity to combine several different sets of health data, from several different sources, then analyze them for trends or patterns that can drive improved return-to-health outcomes and help prevent claims.

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