About
Think digital transformation sounds expensive? What about the long-term cost of the status quo? There is no doubt that change is an intimidating prospect. From shifting generational expectations in the buying experience, to scaling your accelerated underwriting programs without compromising accuracy to managing expense pressures, many life insurers are trying to find ways to balance it all. Innovative information analytics can be the answer that yields benefits for insurers and consumers alike. 

In this webinar, we will explore: 

• A live demo of a visualization dashboard created on a dataset that allows for medical impairments to be crossed with non-medical scores for better segmentation.

•  How a carrier can conduct a study on their book of business to get an idea of the quantifiable impact of this data. 

•  Best practices when conducting post-issue assessments and how to leverage combined data to find true gaps in accelerated programs and create a robust analytical foundation.

•  The future of analytics with AI-based mortality models and how to leverage them to capture complex relationships in medical and non-medical life events.
Presenters
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Patrick Sugent
Vice President of Data Science
Patrick Sugent is vice president of data science for LexisNexis® Risk Solutions. In this role, Patrick is responsible for the effective application of leading-edge analytics technologies for the insurance industry. He is a frequent industry speaker on the use of data and advanced analytics for life insurance and claims as well as emerging technologies, predictive modeling testing and regulatory transparency. Patrick has developed and implemented new data and analytics solutions for property and claims, health care claims and life insurance. Prior to joining LexisNexis Risk Solutions in 2000, Patrick led an analytics team as a member of senior management for a small start-up that grew to more than 150 employees. Patrick holds a master’s degree in predictive analytics from DePaul University and a bachelor’s degree in economics, specializing in econometrics, from the University of Chicago.
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Matthew Stull
Senior Director of Data Science
Matthew Stull, director of data science for LexisNexis Risk Solutions, leads an analytics team focused on applying advanced predictive analytics techniques in the P&C and Life Insurance industry. He directs a team of highly skilled LexisNexis Data Scientists who build predictive models for life insurance underwriting products. His team uses a variety of AI/ML/Statistical methods such as GBM, GLM, and survival modeling. Most importantly he educates both internal and external customers on data sources, statistical techniques, and helps define a practical approach to deploying predictive models and analytics in the life insurance market. He has over 15 years of experience developing and deploying predictive analytics in the insurance industry. He has degrees in Mathematics and Literature from La Salle University and has completed graduate work at DePaul University in Statistics.
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