Mohsen Bahremani Receives MS2Discovery Early Student Researcher Award
Mohsen Bahremani is a student member of the MS2Discovery Interdisciplinary Research Institute and was a recipient of the Early Student Researcher Award in 2020. The main idea of his research is regarding applying the self-exciting point process in financial corporations, especially insurance companies.
His study aims to determine when customers or potential ones need new policies and what policies are necessary for them based on the previous events. In other words, once the insurance companies can predict the future needs of individuals, the way to offer more effective policies would be paved by the benefit from self-exciting point process, which bring the history of the customers' life-style into play to improve the accuracy of the model.
His research tries to address three crucial matters:
· Examining the occurrence of future potential events of customers by self-exciting point process,
· Developing a model of price adjustment for any specific customers,
· Proposing a recommendation system.
This study will be accomplished and will form one integrated model to increase the profits of insurance companies and satisfy insurees simultaneously, compared to the traditional system with one premium fee for any customer, a ruled-based pricing system, or even regular machine learning algorithms.
Mohsen's research interests are to develop data analytic models in the finance industry. He is a Math MSc student with a concentration in statistics and data analytics at Wilfrid Laurier University under the supervision of Dr. Xu (Sunny) Wang. He also holds master's and bachelor's degrees in Industrial Engineering and Systems Analytics.
His study aims to determine when customers or potential ones need new policies and what policies are necessary for them based on the previous events. In other words, once the insurance companies can predict the future needs of individuals, the way to offer more effective policies would be paved by the benefit from self-exciting point process, which bring the history of the customers' life-style into play to improve the accuracy of the model.
His research tries to address three crucial matters:
· Examining the occurrence of future potential events of customers by self-exciting point process,
· Developing a model of price adjustment for any specific customers,
· Proposing a recommendation system.
This study will be accomplished and will form one integrated model to increase the profits of insurance companies and satisfy insurees simultaneously, compared to the traditional system with one premium fee for any customer, a ruled-based pricing system, or even regular machine learning algorithms.
Mohsen's research interests are to develop data analytic models in the finance industry. He is a Math MSc student with a concentration in statistics and data analytics at Wilfrid Laurier University under the supervision of Dr. Xu (Sunny) Wang. He also holds master's and bachelor's degrees in Industrial Engineering and Systems Analytics.