Weekly Seminars on
Risk Management and Actuarial Science
The weekly seminar series is a venue for international scholars in risk management and actuarial science to discuss research advances and exchange ideas. Junior researchers are the most encouraged to present their recent work, including on-going projects. The list of current and past speakers includes scholars from Canada, US, China, Japan, Australia, Switzerland, UK, Italy, Germany and France.
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To volunteer yourself or propose a speaker for a research presentation, please contact the organizers by email.
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We will send out weekly reminders via a mailing list, usually on the day before the presentation. Papers and presentation slides will be circulated among participants via the mailing list. If you would like to be included in the list, please contact the organizers.
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In this year of 2024, most seminars are held in person at the University of Waterloo.
Student Organizers
Zachary John Van Oosten (University of Waterloo): zjvanoosten@uwaterloo.ca
Faculty Mentor
Prof. Ruodu Wang (University of Waterloo)
Upcoming Events
MarMar 14: Christopher Blier-Wong (University of Waterloo)
Title: A representation-learning approach for insurance pricing with images
Speaker: Christopher Blier-Wong (Postdoc Fellow, University of Waterloo)
Time: 15:00 - 16:00, Mar 14, 2024 (Thu)
Location: M3 3127
Abstract: Unstructured data are a promising new source of information that insurance companies may use to understand their risk portfolio better and improve the customer experience. However, these novel data sources are difficult to incorporate into existing ratemaking frameworks due to the size and format of the unstructured data. This paper proposes a framework to use street view imagery within a generalized linear model. To do so, we use representation learning to extract an embedding vector containing useful information from the image. This embedding is dense and low-dimensional, making it appropriate to use within existing ratemaking models. We find that there is useful information included in street view imagery to predict the frequency of claims for certain types of perils. This model can be used as-is in a ratemaking framework but also opens the door to future empirical research on attempting to extract which characteristics within the image leads to increased or decreased predicted claim frequencies. Throughout, we discuss the practical difficulties (technical and social) of using this type of data for insurance pricing.
Past Events
November, 2023Nov 30, 2023: Qinyu Wu (University of Waterloo)
Title: Model Aggregation for Risk Evaluation and Robust Optimization
Speaker: Qinyu Wu (Postdoc Fellow, University of Waterloo)
Time: 14:00 - 15:30 pm, Nov 30, 2023 (Thu)
Location: M3 3127
Abstract: We introduce a new approach for prudent risk evaluation based on stochastic dominance, which will be called the model aggregation (MA) approach. In contrast to the classic worst-case risk (WR) approach, the MA approach produces not only a robust value of risk evaluation but also a robust distributional model, independent of any specific risk measure. The MA risk evaluation can be computed through explicit formulas in the lattice theory of stochastic dominance, and under some standard assumptions, the MA robust optimization admits a convex-program reformulation. The MA approach for Wasserstein and mean-variance uncertainty sets admits explicit formulas for the obtained robust models. Via an equivalence property between the MA and the WR approaches, new axiomatic characterizations are obtained for the Value-at-Risk (VaR) and the Expected Shortfall (ES, also known as CVaR). The new approach is illustrated with various risk measures and examples from portfolio optimization.