Artificial intelligence is having a positive impact on the industry. There are substantial use cases in almost every part of the insurance business, from policy administration and claims to customer service.

Executive Summary

Use cases for AI are promising for P/C insurers, but what's most relevant in driving the industry forward for 2020 is the maturity and evolution of data analytics, asserts Insurity's Kirstin Marr, who advocates renewed focus on syncing data initiatives with overall business goals. As a first step, it's important that insurers become more agile and informed with leaders that represent both IT and business interests. Marr also recommends combining third-party data sources with in-house data to propel strategies around the sought-after small business market. And the next decade will focus on which insurers can better connect advanced analytics with business strategy. In addition, she says to monitor analytics at granular levels rather than aggregate views to assess what's working.

AI can improve fraud detection and claims processing without human intervention from reporting through capturing damage, audit and communication with the customer. For customer service, AI-based chatbots can assist with questions that traditionally required a call center or agent.

A 2017 Accenture report even found that 74 percent of insurance customers would be willing to receive computer-generated insurance advice about coverage options and recommendations.

Use cases for AI in underwriting are also promising but more challenging considering the regulatory environment. To date, machine learning has been used to develop predictive models that are black boxes and only show decision output. This is at odds with regulators that want to know what variables are influencing the decisions in order to avoid price optimization concerns. The technology has been scrutinized dating back to 2014, perhaps most notably surrounding Earnix’s growth in the area.

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