Introduction to Machine Learning: Predictive Modeling in Insurance for Actuaries and their Stakeholders
In this presentation we’ll explore fundamental machine learning concepts tailored for actuaries. Topics range from machine learning theory, common algorithms such as GLMs and GBMs, and the basics of predictive modeling, equipping you with the knowledge to enhance your actuarial practices. In addition to junior modelers or modeling curious actuaries, this presentation also benefits stakeholders who are not building models but want to have a better understanding of what goes into them.
Learn more about the speakers
Max Martinelli
Max Martinelli is a Managing Director in the Insurance and Actuarial Advisory Services practice of EY, where he focuses on P&C pricing, actuarial data science, applied AI and external rating. He has over a decade of experience in actuarial and data science roles, primarily in predictive modeling for personal and commercial lines, and a background in machine learning and computational mathematics. A dedicated collaborator with the Casualty Actuarial Society, he co-designed and led the CAS AI Fast Track bootcamp and co-hosts Almost Nowhere, the CAS Institute podcast exploring AI and data science in insurance.
Parhaam Behnoudnia
Parhaam Behnoudnia is an Actuarial Data Scientist at Akur8, specializing in helping clients leverage advanced machine learning techniques to gain insights into their data and providing them with the best practices with Akur8's software. Prior to joining Akur8, Parhaam worked in the auto insurance sector focusing on building statistical models specializing in price optimization.
