Larry Baeder
Data Scientist
San Francisco, CA, US
Larry Baeder is a data scientist with the Property and Casualty Practice in Milliman's San Francisco office. He joined the firm in 2018.
Experience
Larry's areas of expertise include:
- Developing commercial auto telematics pricing scores using machine learning
- Developing machine learning and data science solutions for rate development, underwriting, territory development, and claims analysis
- Developing traditional predictive models for standard pricing and non-pricing such as underwriting, conversion, and retention
- Developing countrywide flood insurance rating plans
- Developing software for competitive analysis and API
Publications and Presentations
Larry has presented on the applications of big data for insurance, interpretable machine learning techniques, and flood insurance take-up rate modeling. He has published a survey of interpretable machine learning techniques applied to insurance and a study on flood insurance take-up rates.
Education
- MS, Statistics - Texas A&M University
- BS, Computer Science and Communication Arts - University of Wisconsin, Madison
Publications
Read their latest work
Article
Statistical methods for imputing race and ethnicity
29 April 2024 - by Larry Baeder, Erica S. Baird (formerly, Erica Rode), Peggy Brinkmann, Joe Long, Caleb Stracke, Kweweli Togba-Doya, Gabriele Usan, Meseret Woldeyes
Imputation is a powerful tool for studying the disproportionate impact of race and ethnicity on insurance, so we discuss some uses and limitations.
Article
Estimating undisclosed flood risk in real estate transactions
01 August 2022 - by David D. Evans, Larry Baeder
This report studied the potential amount of undisclosed flood risk in New Jersey, New York, and North Carolina by estimating the total number of homes damaged by prior flooding.
Article
Health and hurricanes, studying disparate health impact of extreme climate events, 2017-2020
03 March 2022 - by Cody Webb, Melody Craff, Molly Barth, Larry Baeder, Dale Skinner, Thomas Pu
Carbon dioxide poisoning found consistently among populations affected by four hurricanes points to how climate events can have other health effects.
Article
Insights into consumer demand for flood insurance: Trends in take-up
29 September 2021 - by Larry Baeder, David D. Evans
Utilizing available data, Milliman has developed a take-up rate model that can help private insurers better understand how to test their products, acquire new business, and grow their written premium.
Article
Insights into consumer demand for flood insurance: Trends in take-up
29 September 2021 - by Larry Baeder, David D. Evans
Utilizing available data, Milliman has developed a take-up rate model that can help private insurers better understand how to test their products, acquire new business, and grow their written premium.
Article
Interpretable machine learning for insurance
02 April 2021 - by Larry Baeder, Peggy Brinkmann, Eric J Xu
Machine learning algorithms fit models based on patterns identified in data and can be very complex.