Page Not Found
Page not found. Your pixels are in another canvas.
Sitemap
A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About me
About me
Page not in menu
This is a page not in th emain menu
Posts
Future Blog Post
Published:
This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.
Blog Post number 4
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 2
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2
publications
Cybersecurity insurance: Modeling and pricing
Published in North American Actuarial Journal, 2019
Cybersecurity risk has attracted considerable attention in recent decades. However, the modeling of cybersecurity risk is still in its infancy, mainly because of its unique characteristics. In this study, we develop a framework for modeling and pricing cybersecurity risk. The proposed model consists of three components: the epidemic model, loss function, and premium strategy. We study the dynamic upper bounds for the infection probabilities based on both Markov and non-Markov models. A simulation approach is proposed to compute the premium for cybersecurity risk for practical use. The effects of different infection distributions and dependence among infection processes on the losses are also studied. This paper won the Best Paper Award in 2019!
Data breach cat bonds: Modeling and pricing
Published in North American Actuarial Journal, 2021
Data breaches cause millions of dollars in financial losses each year. The insurance industry has been exploring the ways to transfer such extreme risk. In this work, we investigate data breach catastrophe (CAT) bonds via developing a multiperiod pricing model. It is found that the nonstationary extreme value model can capture the statistical pattern of the monthly maximum of data breach size very well and, in particular, a positive time trend is discovered. For the financial risks, data-driven time series approaches are proposed to model the complex patterns exhibited by the financial data, which are different from those in the literature. Simulation studies are performed to determine the bond prices and cash flows. Our results show that the data breach CAT bond can be an attractive financial product and an effective instrument for transferring the extreme data breach risk.
A Multivariate Frequency–Severity Framework for Healthcare Data Breaches
Published in The Annals of Applied Statistics, 2023
Data breaches in healthcare have become a substantial concern in recent years and cause millions of dollars in financial losses each year. It is fundamental for government regulators, insurance companies, and stakeholders to understand the breach frequency and the number of affected individuals in each state, as these are directly related to the federal Health Insurance Portability and Accountability Act (HIPAA) and state data breach laws. 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 in this work.
Download here
EBiCop: Ensemble Bivariate Copulas for Modeling Multivariate Cyber Data Breach Risks
Published in The Annals of Applied Statistics, 2024
Modeling cyber data breach risks poses a formidable challenge, primarily due to the intricate multivariate dependencies within a backdrop of limited data. This study proposes a novel ensemble learning approach that effectively captures both the temporal and cross-sectional dependence inherent in cyber risks. The proposed approach is significantly different from those traditional ones that directly model the multivariate dependence among risks. Instead, our approach leverages bivariate copulas to generate predictive members to capture the multivariate dependence, and the resulting predictive distribution is calibrated by minimizing the distribution score. Furthermore, the proposed model is applied in insurance pricing, and the results show that it can lead to more profitable contracts. Through extensive simulations and analysis of real-world data, our findings reveal that the proposed model has satisfactory fitting and predictive performance and outperforms those in the literature.
Download here
talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.