What's a CIO's Take on AI in Insurance?

By Insurance CIO Outlook | Thursday, October 10, 2019

Insurance CIOs are continually exploring the potential applications of AI, which resonate with their business needs. 

FREMONT, CA: Artificial intelligence (AI) is proliferating, and its ability to explore massive data sets and extract significant insights from them makes it an essential technology in the current market space. Thus, it isn't a surprise that insurance firms are also keen to utilize AI. Sources suggest that CIOs in the insurance sector will continue investing in AI technology to drive growth, revenue, streamline business operations and serve the customers and distribution partners in a better way. However, the main consideration lies in figuring out how AI can best address their business requirements.

Insurance CIOs are looking for innovations that will foster self-service and front and back-office automation. Such innovations cannot be accomplished without exploring and analyzing volumes of data sets. And AI is by far the best fit for the above cause. The primary contributors to the data sets include insurers’ policy administration systems, social media, websites, wearables, digital voice assistants and other devices. AI can process data sets and offer insights that will allow insurance companies to create innovative insurance products and services.

With an aim to increasingly invest in AI for significant returns, insurance CIOs are keen on investing in AI-driven innovations, believing that AI technology will enable them to address complex customer and business needs. CIOs identify the potential benefits of AI in the light of their business requirements to make a clear, strategic decision in this aspect.

According to sources, more than a quarter of insurance businesses are planning pilot programs that encompass predictive analytics and big data. Predictive analytics, combined with AI capabilities, can unleash the hidden patterns in fraudulent insurance claims. Based on the insights, companies can further safeguard their policies and offset ever-increasing fraudulent claims. Further, AI-enabled predictive analytics will allow the insurance firms to identify customers and determine whether they pose a high or low risk to the company. Overall, predictive analytics enhances the efficiency of a company while resulting in better customer experience.

CIOs must consider the potential of AI to bag success in the long run. Identification of the key metrics that are crucial to the organization, followed by a comparison of pre-AI versus post-AI data, will not only enable the insurers to keep track of AI-driven profits but also encourage them to explore new use cases of AI within their processes.  

While the exact metrics may vary according to a particular organization’s goal, there are a few generic measurements that can be considered such as claims cycle time, workflow changes, field inspections, and customer satisfaction scores. Claims cycle time refers to the average time needed to settle a property and casualty insurance. The cycle encompasses the time the claim has been reported until it has been settled by the insurer. Traditionally, the workflow for claims processing required an adjuster to drive to the property and to inspect the damages. The adjuster was also expected to resolve and close the claim. But now, AI-driven automation promises to reduce the number of steps involved in the claim resolution phase. Moving on to field inspections, insurers need to track the overall cost and number of site visits over the course of time. AI can lower or even eliminate significant portions of field inspections. Maintaining a decent customer satisfaction (CSAT) score is as important as being able to process and close a claim. AI-enabled solutions can enable the insurers to close claims faster as well as more accurately in this regard.  

With all the goodness of AI, CIOs find numerous reasons to invest in AI-led solutions to optimize insurance operations and welcome higher ROI.

Check this out: Top Revenue Cycle Management Technology Companies

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