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 […]
Cyber risk refers to the potential losses that a firm might suffer due to a failure of its information system. The exponential increase in the use and the complexity of information systems has made cyber risk one of the most important and vulnerable operational risks for a company. In order to determine the total cyber […]
This project is a continuation of the IRisk Lab project, European-type basket option pricing: independence and comonotonicity approximations with modern machine learning approaches, in Fall 2019. Feedforward neural network (FNN) has been employed in the previous project to revisit the basket option pricing proposed in [1]. This project aims to further improve and investigate modern […]
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. This project is a real-life actuarial data science project provided […]
Data visualization is a great tool for you, a wannabe actuary or data scientist, to communicate with your teammates and clients. And interactive visualization is even better. R Shiny is a framework that makes the process of developing an interactive web application easy. This project is a continuation of a summer 2020 project, in which […]
A rapid and persistent market value decline of the US bank equity, around 50% since January 2020, can be observed during the COVID-19 pandemic. While the economy as a whole is under stress, stock returns of banks have done worse than those of non-bank financial institutions such as broker-dealers and insurance companies, and non-financial firms. […]
Life is a game with sophisticated rules. With today’s AI technology, we can develop a lifecycle strategy guide for successes in such a game. This project aims to build algorithms that optimize decision making process for meeting important financial goals in life. We look for students who can assist in programming various life-changing scenarios for […]
With the ever-increasing reliance on technology, such as Zoom meeting, online purchase, and even national security for sensitive research, the importance of proper cyber risk management is evident, especially during the time of COVID-19 when everyone works remotely. Learning from the cyber incident history is crucial in order to build risk management and pricing models. […]
An important variable in assessing risk of a commercial/residual building is the actual age of the building. While this seems obvious, obtaining the true age of the building can be challenging. COUNTRY has made use of data available but would like to explore machine learning techniques for assessing the age of a commercial/residual building. Using […]
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. This project is a real-life actuarial data science project provided […]