Cyber risks have been posing increasing concerns to both the public and private sectors, drawing significant attention to the research on these risks. The study of cyber risks inherently involves multiple disciplines and is thus approached from various angles, including actuarial science, information science, computer science, insurance economics, legislation and policymaking. While research from each […]
Machine learning techniques have revolutionized data analysis across various industries, including actuarial science. This project aims to explore and apply machine learning paradigms to actuarial problems using Python and pre-built packages. By leveraging these tools, students will gain practical experience in employing advanced computational methods to solve real-world actuarial challenges. Students will begin with comprehensive […]
The significant impact that extreme weather events have on the financial, insurance, and energy sectors is no longer news, prompting companies to prioritize physical and transition risks along with macroeconomic risk when managing their risk exposure. As climate change intensifies, it is important that companies develop their risk management tools, incorporating climate risk and existing […]
As data-driven decision-making becomes increasingly important in all fields, it is crucial to have a comprehensive understanding of the datasets at our disposal to facilitate research, analysis, and innovation across disciplines. The primary objective of this project is to conduct an extensive data discovery process within UIUC to identify and catalog various datasets that exist […]
Actuarial science and data science skills extend beyond traditional areas like insurance. In this project, we explore various data-driven models to enhance pharmaceutical company operations and guide business decision-making. For instance, we use risk control skills to create a sales order approval system, predictive modeling to forecast future sales, and optimization skills to automate logistics […]
This project engages students from the University of Illinois in a practical, hands-on experience with PCMI, a leader in software solutions for warranties. The project aims to explore new data product opportunities, develop a business case, and support the design and development of innovative data-driven products. Goals Expected Outcomes Deliverables Evaluation This project proposal offers […]
This R&D project explores the development and assessment of various data-driven financial cash models to manage RGA’s global financial service products including longevity swaps, asset-intensive transactions, and pension risk transfers. Transaction-specific data runs the spectrum from voluminous to sparse. Transactions typically range from $100 million to $10+ billion. Participants will apply actuarial science and data […]
As decentralized finance (DeFi) continues to attract investors globally, ensuring the safety and reliability of smart contracts and financial protocols becomes crucial. For insurers, understanding the inherent risks associated with these technologies is essential for developing new products, pricing, and claim processing. While smart contracts offer remarkable efficiency and reduce costs since these blockchain-based innovations […]
Artificial Intelligence (AI) or Machine Learning (ML) algorithms, in the past few years, have been widely implemented in various industrial applications. Sometimes, these ML algorithms exhibit significant bias, or referred as Algorithm Bias, to certain groups. By the definition, Algorithm Bias refers to the inequality brought by the application of algorithms regarding personal features like […]
Due to privacy and data confidentiality concerns, today’s insurance industry is rife with the protectionism of proprietary data, which has become a major roadblock that prevents the free flow of data and collaborations between data scientists and analysts. The inaccessibility of data across the boundaries of insurance firms or even business divisions within a corporation […]