Class of 2021

Photo of Binqi Shen

Binqi Shen graduated Magna Cum Laude from the University of Illinois at Urbana Champaign with a Bachelor of Science degree in Actuarial Science and a minor in Business in December 2019. With interdisciplinary coursework during her undergraduate studies, Binqi equipped herself with both theoretical and practical tools to process, explore, and analyze data. In an equity project, Binqi led a team of 4 to conduct investment portfolio analysis using R. Drawing from her training in finance and statistics, Binqi actively utilized statistical tools to perform simulations and analysis on historical stock prices and spotted optimal portfolios for investors by plotting the Capital Market Line and efficient frontier of portfolios in R. This project further strengthened her passion for analytics and interest for seeking data monetization opportunities. Binqi’s minor in Business has prepared her with the indispensable business intuition and management theories. Specifically, she has learned to heed the economic factors and ethical implications behind pricing designs, as well as to measure the efficiency of an organization via appropriate models.

Binqi’s academic preparation, in turn, incentivized her to seek data-driven solutions to real-life business problems at her internships. Being cognizant of the gender bias prevalent in the healthcare industry in China, Binqi zeroed in on the mainstream practice of gender pricing during her product actuarial internship at Bohai Insurance, one of the top insurance providers in China. Binqi employed data analytics skills and built a multi-factor regression model, articulating a clear negative correlation between the use of preventive care and healthcare costs among urban female populations. Using her quantitative skills to reconstruct the narrative, Binqi successfully instilled new statistically informed insights into the calculation of premiums for new policies targeting young female professionals in the urban areas, expanding target audiences and reducing gender discrimination in pricing. During Binqi’s internship at Roland Berger, she first conducted data cleaning and manipulation with Python to ensure data quality, then employed exploratory data analysis and correlation analysis to identify the most impactful automobile pricing factors in each customer segment. Based on her analysis, she pinpointed data monetization opportunities for clients and provided insightful and feasible suggestions to maximize the client’s operational efficiency.

Impressed by the power of data and analytics, Binqi is thrilled to continue her education in the MSiA program at Northwestern University, where she will improve her technical skills and gain ample hands-on experiences. She is looking forward to becoming a data scientist who provides insightful recommendations and informs customer-oriented strategies to build robust business models and generate immense value.