7 papers
Efficient and Interpretable Transformer for Counterfactual Fairness
Panyi Dong, Zhiyu Quan
The growing reliance of machine learning models in high-stakes, highly regulated domains such as finance and insurance has created a growing tension between predictive performance,…
Starting Off on the Wrong Foot: Pitfalls in Data Preparation
Jiayi Guo, Panyi Dong, Zhiyu Quan
When working with real-world insurance data, practitioners often encounter challenges during the data preparation stage that can undermine the statistical validity and reliability…
Claim Automation using Large Language Model
Zhengda Mo, Zhiyu Quan, Eli O'Donohue +1
While Large Language Models (LLMs) have achieved strong performance on general-purpose language tasks, their deployment in regulated and data-sensitive domains, including insurance…
InsurTech innovation using natural language processing
Panyi Dong, Zhiyu Quan
With the rapid rise of InsurTech, traditional insurance companies are increasingly exploring alternative data sources and advanced technologies to sustain their competitive edge. T…
Entity-Specific Cyber Risk Assessment using InsurTech Empowered Risk Factors
Jiayi Guo, Zhiyu Quan, Linfeng Zhang
The lack of high-quality public cyber incident data limits empirical research and predictive modeling for cyber risk assessment. This challenge persists due to the reluctance of co…
Automated Machine Learning in Insurance
Panyi Dong, Zhiyu Quan
Machine Learning (ML) has gained popularity in actuarial research and insurance industrial applications. However, the performance of most ML tasks heavily depends on data preproces…