Companies are not making plans on a whim or a hunch. Results are providing a strong endorsement for participants’ proactive strategies, according to those already using predictive analytics. Over two-thirds report that predictive analytics have helped reduce issue/underwriting expenses, while 60% credit the additional insights for increases in sales and profitability (Figure 5).
Figure 5. How life insurers currently use predictive analytics to assess business performance
“Over two-thirds report that predictive analytics have helped reduce issue/underwriting expenses, while 60% credit the additional insights for increases in sales and profitability.”
This impressive showing is strengthening the will to explore new methodologies linked to predictive analytics. These include artificial intelligence (AI) and machine learning, which can support objectives already mentioned such as cost reduction, enhanced underwriting and fraud detection. The biggest application seen for these techniques over the next two years (60%) is the reduction of time spent by humans on repetitive tasks. Nearly half expect to augment the work of human underwriters in this time frame, and upward of 40% are working toward ways to improve organizational understanding of risk and apply this in risk models that support decision making.
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