IRisk Lab Fall 2023 Projects

Cyber risks have been posing increasing concerns to both public and private sectors. While cyber insurance has naturally emerged as a market solution to mitigate cyber risk in the recent decade, its development is still in an early stage. The underdevelopment of cyber insurance market is attributable to the complex yet unknown nature of cyber risks. One major challenge is the potential dependence among cyber risks. Due to the cyber nature, the dependence could widely exist among a large scale of cyber risks regardless of locations. This poses substantial insolvency risk to insurance providers and thus discourages their participation. To make it worse, there is yet no sufficient historical data to uncover the dependence structure.

In this project, we aim to tackle this challenge from a physical simulation approach. That is, to employ cyber engineering techniques to generate reliable data and identify the root cause of dependence, and thus better capture the dependence characteristics. In a later stage, we anticipate utilizing the data and dependence characteristics to develop interactive actuarial models for pricing and risk management, with the aim to promote healthy development of the cyber insurance market and enhance the overall social welfare for all stake holders.

Supervisors: Wei Wei
Graduate Supervisor: TBA

A DAO is an innovative organization structure that has emerged with blockchain technology. It allows like-minded individuals from around the world to collaborate with each other without having to rely on the leadership of a central authority. The project is intended to study the history and the evolution of DAOs in blockchain ecosystems and beyond.

Supervisors: Runhuan Feng
Graduate Supervisor: Peixin Liu

Leveraging the blockchain technology, decentralized insurance has recently gained significant attention due to its advantages in energy efficiency, transparency, and scalability. In contrast to traditional insurance where the insurance company serves as the central entity, decentralized insurance utilizes the Proof-of-Stake (PoS) consensus for risk and claim assessment purposes.

In this project, we will explore the current decentralized insurance market, with an emphasis on the pricing and claim assessment mechanisms employed by the leading firms in the industry. The utilization of blockchain technology has facilitated the availability of public data for decentralized insurance platforms and cryptocurrency transactions, which provides us with unique research opportunities. By analyzing transaction data, we will investigate the behavioral patterns of these decentralized insurers, as well as the dynamics of demand and supply within the network.

Supervisors: Xiaochen Jing
Graduate Supervisor: Zhonghe Wan

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 across different units, research centers, and government entities. By consolidating these datasets into a centralized repository, we can provide researchers, students, and faculty members with a unified platform to access a wide range of data for their projects and initiatives. We anticipate that this project will require dedicated personnel, access to relevant systems, perform data visualization, creating a relational database.

Supervisors: Zhiyu (Frank) Quan, Eli O’Donohue
Graduate Supervisor: Litong Liu