4 AI Predictions for the Insurance Industry in 2023

4 AI Predictions for the Insurance Industry in 2023

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2023 will be the year that artificial intelligence (AI) gains significant momentum in the insurance industry.  This is largely due to maturing technology advancements, the rising popularity, and familiarity of AI, as well as the greater availability of vast amounts of quality data.  Today’s emerging AI technologies are allowing insurance companies to realize quicker time to ROI as well as enter new geographies and new lines of business. In 2023, insurance companies will embrace AI to:

  1.  Expand Beyond Known Geographies and Industries 

To avoid increased risk, insurers tend to restrict the geographies they cover and the industries that they insure. As a result, each insurer chases fewer profitable clients, resulting in an increasingly competitive environment.  However, new AI offerings enable them to leverage large, federated databases with extensive claims and underwriting histories that span multiple geographies and industries. These databases also include extensive medical, health and demographic information. Therefore, insurers can now assess risk and price premiums more accurately, improve loss ratios and open new markets more effectively with AI. As the competition for business continues, insurers will embrace AI to make more informed and nuanced decisions as it relates to expanding their businesses.

  1. Bridge the Talent Gap by Preserving Institutional Knowledge

As mature workers retire and fewer young people enter the field, insurers are searching for ways to obtain talent resilience. Leveraging AI will be a key strategic initiative, as insurers look to capture seasoned professionals’ institutional knowledge, then transfer it to less experienced employees. AI can effectively serve as a co-pilot for newer employees dramatically decreasing their training time. As AI becomes more widely adopted, underwriters and adjusters will be able to amplify their capabilities, allowing them to process more policies and claims at a higher level of effectiveness. New workflows will emerge that leverage the combined strengths of AI and talented professionals.

  1. Maintain Profitable Loss Ratios while Delivering a Better Customer Experience 

In a tightening economic environment (or should we say “With a looming recession”?), insurers are searching for ways to maintain profitable loss ratios. To do so, they will use AI to assess and analyze millions of data points so that they can gain visibility into the most relevant risk factors for any given client. This will ultimately increase efficiency, maximize price competitiveness, reduce quote turnaround times, enable Straight Through Processing, and optimize claims processing. Most important, AI combined with skilled professionals improves customer experiences which can often lead to new business opportunities.

  1. Predict Disease, Injuries, and Accidents

Insurers are always searching for ways to get ahead of losses—to assess risk and take steps to mitigate or even prevent losses from happening at all.  With AI, health insurers and workers’ compensation insurers can now access more data, including pharmacy, medical and health data. This allows them to assess risk with greater precision and accuracy than ever before possible. As a result, AI will increasingly be used to predict:

  • Diseases within a population, enable insurers to proactively act on a patient’s behalf to improve health and outcomes. Disease prevention will become more prevalent as AI models become better predictors even in patients who have no early indication of disease.
  • Potential for workplace injury, leading companies to take preventive steps to keep the workplace safe, reducing the likelihood of injury and workers’ compensation claims
  • Likelihood of injury and accidents, such as finding patterns in geographies, demographics and work conditions that lead to commercial auto claims.  Companies can take steps to address risks before injuries and accidents happen, becoming preventative rather than reactive.

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