Accelerated Underwriting With Algos

Want more proof that software is eating the world? Accelerated Underwriting for life insurance replaces the invasive medical exams (testing of body fluids) with algorithm driven underwriting and modeling techniques, thereby greatly reducing the underwriting decision from weeks to hours. While all may not qualify and some will get better rates with a standard underwriting, this style of underwriting brings scale to the insurance portfolio like nothing else. No wonder that more and more insurance companies are adopting accelerated underwriting for life insurance.Is accelerated underwriting the only way to underwrite life insurance? Certainly not. Generally, insurance companies are only offering term life policies with this underwriting. This is a good example of how a rule-based underwriting engine can automate the risk pricing quickly and efficiently. Moreover, the algos can be tweaked (fine-tuned or altered) to balance the risk at any stage. That is, if the overall portfolio becomes skewed towards some risk classes, the algos can be tuned to shift the weightage to the desired direction.Not only does the tech savvy consumer love it, but this kind of underwriting also has several advantages. First off, it will attract younger clients. Ask an actuary what that means, and they will go to great lengths to inform you that selling life insurance to younger consumers is a dream come true as the long duration of premium paying clientele is what makes the life insurance pool profitable.

This underwriting is less costly and is more of a ‘standard’ as the decision is made by an algorithm, not by a human. It also removes any undue human bias from the equation.
So, you have a fast, efficient, less costly, equitable, inherently profitable workflow that your customers love.

Another benefit of this kind of underwriting is that even though the risk is priced by algorithms, one does not need big data to create these models. This is especially helpful to smaller insurance companies that do not have access to big data on their own.

Need something more? Go work on those algos, models and get that product going.