In this edition of ReCent Medical News, Paul Edwards explains why health and fitness data captured through the use of wearables is potentially very meaningful for life insurance underwriting.
Digital point of sales solutions for life insurance continue to become more innovative.
PartnerRe Review of LexisNexis® Risk Classifier with Medical Data – Combined Model Indicates Greater Predictive Value
PartnerRe’s analytics experts evaluated the Life predictive model, LexisNexis® Risk Classifier with Medical Data. Here we present the results of our objective and detailed review of the model.
As insurers shift to incorporate new and alternative data sources, underwriters are taking on more specialized skills. In On the Risk, RGA data strategist Jordan Durlester and underwriter Jacqueline Waas join forces to discuss the value of collaboration in more effectively applying new evidence sources to underwrite new business.
Underwriting is a vital function that is ripe with opportunities for innovation. Every day, new sources of insurability data are being developed and vetted. In this post, we’ll examine a few examples, providing our perspectives on how these electronic sources of data can be leveraged in the underwriting process and where they are in the adoption lifecycle.
Simply stated, the law of large numbers in probability and statistics states that as a sample size grows, its mean gets closer to the average of the entire population.
Data analytics projects have become increasingly common across the insurance industry in the last few years and have really taken off in the Life sector. It’s a trend that requires the input of Medical Directors - and it gives the Directors a chance to shine.
Insurers were already welcoming technology and embracing ideas such as accelerated underwriting. But things move slowly in the insurance world. Then the COVID-19 pandemic hit and insurers no longer controlled those timelines.
One of the hardest challenges Life insurers encounter when adopting accelerated underwriting (AU) is figuring out how to compensate for the loss of information previously derived from blood and urine tests.