The industry has yet to tap the true potential of accelerated underwriting because the automation component has been missing.
The race to develop accelerated products has driven life insurers to cautiously embrace the next generation of data.
Kyobo Life Insurance announced on October 30 that its AI-based underwriting system, known as Best Analysis and Rapid Outcome (BARO), is now fully operational.
Life underwriting professionals are experiencing a paradigm shift in modus operandi, driven by the introduction of automation initiatives. Multiple consulting studies and analyses indicate that automation in underwriting is a valid business need. The coevolution of humans and technology must be supported by business strategies that focus on identifying necessary underwriting skill sets. The convergence of the art of underwriting and the science of technology presents many challenges. Insurers and reinsurers must plan accordingly.
Insurers seem to be chasing appearances, investing eye-watering sums of money into projects to improve the application process, but these sleek, web-based systems can mask a distressing reality: Underwriting technology underpinning the decision process is not attracting the same attention. RGA's Bruce Bosco calls for a greater emphasis on automated underwriting to improve the customer experience and help bridge the protection gap.
Underwriting in the US life insurance industry has had more change in the last five years than it has in the prior 30…and many underwriters are struggling to keep up with the pace. Terms like accelerated underwriting, automated underwriting, simplified issue, predictive models and big data are bounced around at industry meetings like ping pong balls. If you are confused by all the new terminology, you are not alone.
Previously reserved for the hard to insure, simplified issue products have evolved into fully underwritten simplified products. Backed by artificial intelligence, these products have become an alternative to traditional simplified issue products.
The underwriting automation engine has undoubtedly become a popular approach for many insurance organizations seeking to increase efficiencies and augment their workforces. While implementing this technology is likely vital to remain competitive, there is often a disconnect between the expectations and the reality of automation’s impact on underwriting operations.
Increasingly, computer templates are making binding underwriting decisions through information that is programmed in with final decisions virtually unappealable. It’s a frustrating situation that is taking the human element out of a very human situation of health and risk assessment.