Munich Re Life US evaluated LexisNexis Risk Classifier with Medical Data, a predictive modeling tool developed and owned by LexisNexis® Risk Solutions in collaboration with ExamOne. It assesses mortality risk by combining an individual’s behavioral and credit attributes and medical data, including prescription history, clinical laboratory results, and medical claims.
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.
Ethical Standards are an Integral and Critical Consideration for Predictive Model Developers and Users
Dr. Tom Fletcher, VP Data Analytics, North America Life, shares his perspective on the component strands necessary to build and maintain ethical standards in predictive modeling.
The center questions the use of factors such as employment class and education level in marketing, underwriting and pricing.
Munich Re assessed the effectiveness of Milliman Irix® Risk Score 2.2 in stratifying the mortality for the U.S. insurance applicant population.
Predictive models are an incredibly powerful tool with the potential to drive the life insurance industry forward in ways that are good for both consumers (improving their purchasing experience by removing intrusive requirements and long delays) and carriers (increasing taken rates and persistency, and increasing the accuracy of mortality assessments).
Underwriting practices today are a world away from those commonplace 20 years ago, but the biggest evolution is yet to come.
The race to develop accelerated products has driven life insurers to cautiously embrace the next generation of data.
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.
The cutting edge of the insurance industry involves adjusting premiums and policies based on new forms of surveillance.