A Study on Catastrophe Bonds and Index Insurance

In the presence of natural disasters, such as earthquakes, hurricanes, and floods, insurance companies may face tremendous losses beyond their capacities. To address this situation, catastrophe bonds (CAT bonds) have been developed to transfer catastrophic losses from the insurance community to the capital market. Typically, insurance companies (or their agents) issue CAT bonds to investors […]

Actuarial Models for Cyber Risks

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 […]

Climate Risk Measures

The significant impact that extreme weather events have on the financial, insurance, agriculture, and insurance sectors is no longer news, and companies now prioritize physical risk and transition risk in addition to macroeconomic risk when managing their risk exposure. In light of climate change, it is important that companies develop their risk management tools, incorporating […]

Decentralized Insurance Market Analysis (Continued)

Cryptocurrency risk is considered an emerging and dynamic area of concern, and most traditional insurers tend to steer clear of this market due to the scarcity of data and the difficulty in risk assessment. On the other hand, by leveraging the blockchain technology, decentralized insurance has become the pioneers to offer covers for hacks and […]

Neural Networks from Scratch

This project creates a neural network from scratch using basic coding techniques with Python or R, specifically leveraging the basic library or packages, such as NumPy and basic R functionalities. The primary objectives include providing an educational experience to understand the fundamentals of neural networks, offering practical exposure to coding in Python and R, and […]

Data Discovery and Consolidation

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 […]