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 […]
The insurance industry has long known the importance of data, and the success of its business heavily relies on data collection and analysis. With the fast growth in computing power and the development of machine learning techniques, more and more variables/features are used in predictive analysis in various aspects of insurance, such as rate making, […]
Since the time when cyber insurance was first introduced to the market, there has been a rapidly expanding volume of literature that focuses on other aspects of cyber risk, such as the legal and financial consequences of cyber incidents, and they are closely related to the development of the cyber insurance industry. With the large and […]
For the insurance industry, the potential to understand customers and businesses using new dimensions represented by social and other online data can unleash significant new insights from both customer behavior and risk perspective. These insights can drive insurance automation, underwriting efficiency, and enhanced customer experience. The objective of this project is to develop and optimize […]
For the insurance industry, the potential to understand customers and businesses using new dimensions represented by social and other online data can unleash significant new insights from both customer behavior and risk perspective. These insights can drive insurance automation, underwriting efficiency, and enhanced customer experience. The objective of this project is to develop NLP models […]
A smart contract is a set of codes that execute business logics for contractual agreement in financial transactions. Our University of Illinois team has designed various business models for catastrophe risk sharing. In this project, students are expected to learn smart contract programming and build the first of its kind smart contract for distributed insurance. […]
Foot traffic data is captured by various sources, such as smartphone APP, telematics devices in the vehicle, which can help insurance monitor policy holders’ behavior. It is beneficial for insurance companies to price the risk accurately and accelerate the underwriting process. On the other hand, policyholders are given incentives for good driving behavior. There are […]
TStock and index options are traded on the financial market and their prices are determined by supply and demand. These prices are publicly available and are forward-looking: they contain information about the aggregate view of the market about the future dynamics of the financial market. The Volatility Index (VIX) is the market barometer for volatility and […]
Classical backward preferences of an investor are simply defined by a family of her value functions across states and times. Due to the backward nature, a terminal preference must be specified a priori. However, pre-specifying the future preference is actually unjustifiable in practice. To rectify this modeling drawback, a novel concept called forward preferences has […]