Holland, FSA, MAAA
Director and Actuary
AIG Life & Retirement
Brian joined AIG in 2014. He is responsible for experience studies on life and A&H products. He has previously held responsibility for morbidity research on LTC and IDI at Munich Re and also a variety of valuation roles. Brian has chaired the council of the Predictive Analytics and Futurism Section of the SOA. Other current and past volunteer activities include the SOA’s Individual Life Experience Committee, Individual Disability Experience Committee, the sixth SOA LTC Intercompany Report, the AAA’s Individual Disability Table Working Group, and the AAA’s Life and Health Valuation Law Manual.
Talex Diede, MS
Talex is an actuarial analyst with the Life practice in Milliman's Seattle office, working primarily with the life and annuity predictive analytics group. She joined the firm in 2013. Since joining Milliman, Talex has primarily worked on predictive modeling, with a focus on policyholder behavior. She specializes in data analysis and data manipulation in addition to statistical modeling. She has experience with traditional statistical model building methods as well as newer machine learning methods. Recent projects include investigating uses of big data to improve predictions of policyholder behavior.
Vice President, Research & Development
Jean-Marc is VP, Actuarial R&D for Gen Re Life in Stamford, CT. He has over 25 years of experience in the life insurance industry and is a fellow of the SOA. He has extensive experience in many aspects of life and critical illness insurance product development. His more recent focus has been on mortality.
He is currently active in a number of SOA committees and Project Oversight Groups centering on mortality and underwriting. He is a newly elected member of the Reinsurance Section Council and an old timer on the SOA’s Longevity Advisory Group. He is the chair of the next Living to 100 Symposium taking place in Orlando in 2020.
He graduated from Whittier College in California.
Ben Johnson, MS
Ben is a quantitative analyst with Milliman’s Financial Risk Management Practice in Chicago, joining the firm in 2016. Ben works on the life and annuity predictive analytics team, where he applies predictive analytics to experience studies on policyholder behaviors such as lapse and life-time withdrawal benefit utilization for variable annuity contracts. His favored coding language is R, for both data analysis and for building interactive web applications using R Shiny.
Ben has an educational background in both theoretical and applied mathematics with a focus on statistical methods and predictive modeling. His experience includes working with generalized linear models, Bayesian point estimation, and nonlinear optimization techniques.
Prior to joining Milliman, Ben taught mathematics at the university level for two years.
Matthias Kullowatz, MS
Matthias Kullowatz is an Actuary and data scientist and works primarily on predictive modeling projects with Milliman’s Life and Annuity Predictive Analytics team (LAPA). He started with Milliman in 2015, and since has used his background in statistics to help guide the predictive modeling team in refining best practices and in improving communication with client stakeholders. He is involved in all stages of predictive modeling projects. In recent studies investigating the drivers of lapse and rider utilization behavior, this included data exploration and preparation, modeling, theory, and presenting results to a client audience which had a diverse familiarity with statistical concepts.
Before joining the actuarial profession, Matthias accumulated four years of experience teaching statistics to undergraduates in Portland, OR. While a professor, he focused on improving existing teaching methods. He wrote curriculum for teaching statistics using R, as well as a curriculum for teaching Calculus with a participatory, hands-on approach. On the side, Matthias devotes a healthy number of hours to raising his two young daughters, and an unhealthy number of hours to using statistics to make his fantasy baseball teams above average. He has six years of experience using R for all of his statistical endeavors.
Matthias graduated from Lewis and Clark College with a BA in mathematics, and from Portland State University with an MS in statistics.
Senior Manager, Risk Management – Model Development & Modernization
Marshall Lagani is a risk manager with a strong interest in financial engineering and data science, specifically in their application to computational models of insurance risk. Marshall has worked for Transamerica since 2009, working in functions related to hedge modeling and strategy, quantitative analytics, predictive modeling, and model development. Throughout this time, he has developed a deep passion for applying the data science toolkit to a wide array of problems in insurance risk management, particularly in behavioral assumption setting and financial modeling.
Marshall holds a Master’s degree in Mathematics from the University of Louisville.