My name is WenSui Liu and I am a statistician working for Fifth Third (5/3) bank in Cincinnati (OH). In 5/3 bank, I am leading a team of quantitative analysts developing operational risk models for the enterprise risk as well as working on annual submissions of Comprehensive Capital Analysis and Review (CCAR). Before joining 5/3, I had worked for LexisNexis Risk Solutions, JPM Chase, and Paypal on various interesting areas, including database marketing, risk modeling, and fraud detection with machine learning.
I truly enjoy working on the data and concerting with other statisticians. In my spare time, I like learning new computing languages and reading good books and paper in statistics and machine learning.
Let’s link up on Linkedin
– Modeling Practices of Operational Loss Forecasts, SAS Analytics Conference, 2015
– Modeling Fractional Outcomes with SAS ®, SAS Global Forum, 2014
– Modeling Practices of Risk Parameters for Consumer Portfolio, SAS Analytics Conference, 2011
– Rapid Model Refresh in Online Fraud Detection Engine, SAS Data Mining Conference, 2010
– Generalizations of Generalized Additive Model: A Case of Credit Risk Modeling, SAS Global Forum, 2009
– A Class of Predictive Models for Multilevel Risks, SAS Global Forum, 2009
– Count Data Models in SAS, SAS Global Forum, 2008 (Best Contributed Paper)
– Adjustment of Selection Bias in the Marketing Campaign, INFORMS Marketing Science Conference, 2008
– Behavior-based Predictive Models, SAS Data Mining Conference, 2008
– Generalized Additive Model and Applications in Direct Marketing, Direct Marketing Association (DMA) Analytical Journal, 2008
– Improve Credit Scoring by Generalized Additive Model, SAS Global Conference, 2007
– Data Mining: Decision Trees, Multivariate Adaptive Regression Splines (MARS), Generalized Additive Models, Projection Pursuit Regression, Neural Networks, Bagging, Boosting, Bumping, and Decision Stump.
– Statistics: Generalized Linear Models, Count Outcome Models, Proportion Outcome Models, Longitudinal Models, Finite Mixture Models, Quantile Regression, Multivariate Analysis, and Time Series.
– Programming: R / S+, Python, Julia, Matlab / Octave, and SAS.
– Database: Teradata (BTEQ), Oracle (PL/SQL), DB2, SQL server (T-SQL), MySQL, SQLite, and MongoDB.
– Utilities: Linux, Cygwin, Emacs (ESS), Vim, SED, Shell, Pig Latin, and HDF5.
– Risk Modeling: Credit Risk Models (PD / EAD / LGD) and Scorecard Development.