In this episode of Streamlining Insurance, host Darren Bloomfield speaks with Zhiyu (Frank) Quan and Panyi Dong about bridging the gap between academic research and real-world insurance innovation. Together, they explore how actuarial science is evolving through automation, highlighting their open-source AutoML tool designed to help actuaries and insurance professionals leverage machine learning without sacrificing data privacy or interpretability. They discuss the growing need for tech fluency in the insurance industry, the importance of hands-on experience for students, and the role AI will play in future workflows.
Watch or Listen:
Zhiyu (Frank) Quan is an Assistant Professor at the Program for Actuarial and Risk Management Sciences of the University of Illinois Urbana-Champaign, a Brad and Karen Smith Professorial Scholar of the College of Liberal Arts and Sciences, and a Finance and Insurance Sector Lead for Discovery Partners Institute. He holds a Ph.D. in Actuarial Science from the University of Connecticut. Before joining Illinois, he worked in a cutting-edge Insurtech company as a R \& D data scientist developing data-driven solutions for major insurance companies. He has a broad spectrum of research interests in data science applications in insurance such as tree-based models, natural language processing, deep learning, and applies his actuarial expertise to build predictive models for claim research, rate making, etc. His research agenda is driven by real-life data and is inspired by collaborations with Insurtech and insurance companies. Besides, he is a director of the Illinois Risk Lab, which facilitates research activities that integrate academic training with practical problem-solving in real business settings. He has received the Arnold O. Beckman Research Award and has been awarded by the Society of Actuaries Research Institute and Casualty Actuarial Society.
Panyi Dong is a Ph.D. student in Actuarial and Risk Management Sciences at the University of Illinois Urbana-Champaign. His research focuses on leveraging machine learning for insurance applications, with particular interest in risk modeling, automation, and decision support systems. He co-authored “Automated Machine Learning in Insurance” (2024), highlighting how automation can transform workflows in actuarial and risk functions.
Darren Bloomfield is a graduate of Butler University, where he earned a Bachelor’s degree in Risk Management & Insurance and Finance. As a former underwriter turned SaaS professional, Darren is passionate about modernizing the insurance industry. He partners with carriers and brokers at Feathery to implement workflow automations that eliminate manual tasks and unlock growth. In Streamlining Insurance, Darren explores how insurance leaders are building the future of operations, distribution, and technology.
