In insurance, risk – and the tools used to evaluate risk – are evolving into a divided model. Digital Insurance published “How Tech is Evolving Insurance Risk Analysis” by our insurance experts John Rodgers, Rajeev Aggarwal, and Brian Nordyke. The team looks at how the change will impact the industry and ultimately reward savvy carriers in the long term.

“In this series of articles, we have been examining digital trends that will shape the future of the insurance industry. The models emerging from these pivotal trends will continue to transform the industry over the next decade, transforming insurance into a fully digital universe.

In this installment, we look at how risks – and the tools used to evaluate those risks – are evolving into a bifurcated model. This change will ultimately reward carriers that can adapt and match its business model and cost structure to the characteristics of its portfolio.

Carriers, pressed by lower expense insurtech models that emphasize direct-to-consumer engagement and new, rich data sources, are beginning to encounter a bifurcation of risk and client characteristics. As the insurance evaluation and quoting landscape becomes more commoditized, sophisticated models utilizing new sources of data are pushing upmarket in both the personal and commercial insurance spaces.

Consequently, risk profiles are starting to follow a barbell distribution pattern – some risks are more measurable, more easily quantifiable, and therefore require less human intervention in pricing and evaluation. Other risks and client profiles, such as multinational policies in the commercial world, fall into a more complex profile and need a significant operational lift, requiring increasingly sophisticated and deep operational resourcing by carriers.

These divergent risk prediction profiles will accelerate hybrid human/AI models for risk prediction, claims handling, customer relationship management, and one-off major loss handling. The changing risk landscape will accelerate hybrid and AI technology adoption, while catastrophic loss measurements will continue to require deep human expertise.”

Read the full article here.