Concordia researcher applies statistical thinking to non-life insurance
When it comes to insurance, many people, including car owners, feel like they are paying too much for insufficient coverage.
Applied mathematics might not be the first thing that comes to mind on this topic. Yet for Yang Lu, assistant professor of mathematics and statistics at Concordia’s Faculty of Arts and Science, there is a natural connection.
Lu, whose research focuses on non-life insurance, is part of her department’s new quantitative finance and insurance minor.
his paper, “Wishart-gamma random effects models with applications to non-life insurance,” tackles the problem, with specific takeaways regarding car insurance.
“My research explores how insurers can incentivize people to drive safely”
What attracted you to the field of non-life insurance?
Yang Lu: I was a young undergraduate student looking for practical applications of mathematics and statistics. Insurance, particularly non-life insurance, was one of the most popular areas of specialization among students seeking an internship in the industry. I did a doctorate in actuarial science, I did an internship in some companies and I ended up becoming a researcher in this field.
Describe your study.
YL: Recently, I worked on the development of new techniques for modeling cyber risk, an emerging risk that has become increasingly important in recent years.
What do you think people might be surprised to learn?
YL: Take car insurance, for example. Because it affects so many of us, the way pricing is practiced is certainly of interest to a wide audience.
My research explores how insurers can best use each policyholder’s past claim experiences to improve pricing on an individual basis and incentivize people to drive safely.
Finally, what’s next for you?
YL: One of the most fascinating aspects of our work is that our research interests constantly evolve to reflect the needs of industry and society.
For example, due to climate change, many industry reports suggest that natural disasters have become more frequent and/or more costly. Using statistical tools such as time series analysis, I try to characterize this trend and quantify the uncertainty surrounding it.
Learn more Concordia Minor in Quantitative Finance and Insurance.