Fasano Conference to Highlight Machine Learning Applications for Life Expectancy Underwriting

Fasano Conference to Highlight Machine Learning Applications for Life Expectancy Underwriting

The structured settlement demographic is very different than the life insurance/settlements population. As a consequence, the underwriting approach as well as the underlying data differ substantially. While ample medical information from physician and hospital reports typically is available for life settlement underwriting, clinical documentation for the structured settlement population is less consistent; and while medical information explains much of the mortality expectations for life insurance and life settlements, behavioral factors are more relevant for mortality in the structured settlement population.

To analyze the factors explaining and driving mortality in the structured settlement population, Dr. Bauer and his colleagues at the University of Wisconsin have taken underwriting reports from surveys, interviews, and criminal/drug history reports, and applied semi-supervised machine learning approaches to automatically discover meaningful features from the unstructured text data.

Said Mike Fasano: “This promises to be an extremely interesting presentation. Dani’s research is state-of-the-art, and we are hoping that it will shed light on statistically meaningfully features driving mortality in the structured settlement population.

The Fasano Conference is a time efficient, one-day event that covers the most current and relevant topics affecting the longevity markets it has been favored by the investment and financial community. Cocktails and dinner immediately follow the Conference. Register Now!