Zeinab Amin is a professor in the Department of Mathematics and Actuarial Science and the associate provost for assessment and accreditation. Amin holds a PhD in statistics, is an associate of the American Society of Actuaries (SOA) and a certified actuarial expert at the Egyptian Financial Supervisory Authority (EFSA).
Amin is the recipient of the 2016 Excellence in Academic Service Award and the 2009 Excellence in Teaching Award from AUC.
Amin has designed and taught a wide range of courses in statistics, applied probability, life contingencies, construction and evaluation of actuarial models and enterprise risk management.
Recent Refereed Publications
Amin, Z. (2019). “A Practical Road Map for Assessing Cyber Risk,” Journal of Risk Research, 22, 32-43.
Salem, M., Amin, Z. and Ismail, M. (2018). “A Prediction Interval Approach to Developing Life Test Acceptance Criteria for Progressively Censored Data,” International Journal of Reliability and Safety, 12, 279-291.
Salem, M., Amin, Z. and Ismail, M. (2018). “Designing Bayesian Reliability Sampling Plans for Weibull Lifetime Models Using Progressively Censored Data,” International Journal of Reliability, Quality & Safety Engineering, 25 (3). Published online January 25, 2018
Amin, Z. (2016). “Quantification of Operational Risk: A Scenario-Based Approach,” North American Actuarial Journal, 20, 286-297
Amin, Z. and Salem, M. (2015), “Bayesian Modeling of Health Insurance Losses,” Journal of Applied Statistics, 42, 231–251.
Chapters in Peer-Reviewed Books
Book Reviews in Refereed Journals
Amin, Z. (2014). “Operational Risk Modelling and Management by Claudio Franzetti,” Journal of Risk and Insurance, 81, 969–973.
Amin’s current area of research focuses primarily on quantitative risk assessment, highlighting the power of developing an effective enterprise risk management framework in an organization, a framework that overcomes the challenges that prevent traditional risk programs from achieving their full potential. Amin emphasizes the importance of adopting new methodology for operational risk assessment, methodology that allows for better understanding of the shock resistance of the company to its key risks, developing an appropriate risk management environment, making better risk-adjusted decisions and ensuring appropriate actions are implemented to better manage enterprise risk exposure to be within its risk appetite.