报告题目：A Multivariate Frequency-Severity Model for Healthcare Data Breaches
报告摘要：Data breaches in healthcare have become a substantial concern in recent years, and cause millions of dollars in financial losses each year. However, an obstacle to studying data breaches in healthcare is the lack of suitable statistical approaches. We develop a novel multivariate frequency-severity framework to analyze breach frequency and the number of affected individuals at the state level. A mixed effects model is developed to model the square root transformed frequency, and the log-gamma distribution is proposed to capture the skewness and heavy tail exhibited by the distribution of numbers of affected individuals. We further discover a positive nonlinear dependence between the transformed frequency and the log-transformed numbers of affected individuals (i.e., severity). Both the in-sample and out-of-sample studies show that the proposed multivariate frequency-severity model that accommodates non-linear dependence has satisfactory fitting and prediction performances.