Big Data Analysis in Credit Card Industry

#"Big #Data #Analysis #in #Credit #Card #Industry" #by #Dr. #Lana #Song #and #Jun #Bai #from #JP #Morgan #Chase.
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• Do you know credit card is a 1+ trillion industry in USA?
• Do you know the difference between raw data and information?
• Do you know how credit card companies utilize and analyze big data?
• Have you ever heard of FICO score?
• Do you know how to build a credit score to predict future profitability and losses?
• Do you want to know how statistics is being used in one of the biggest banks in USA?
This presentation intends to give a high level overview of American credit card industry and provides insights on how Big Data Analysis being applied in this industry, with an emphasis on credit scoring - its history, objectives, methodologies, and processes. A case study is provided to illustrate why credit scoring is one of the most successful applications of statistical and operations research modeling in finance and banking.

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  • Fairleigh Dickinson University
  • Teaneck, New Jersey
  • United States 07666
  • Building: Auditorium M105, Muscarelle Center
  • Click here for Map
  • Contact Event Host
  • Hong Zhao (201)-692-2350, zhao@fdu.edu; Howard Leach h.leach@ieee.org
  • Co-sponsored by School of Computer Sciences and Engineering, FDU
  • Starts 30 March 2014 08:00 PM UTC
  • Ends 23 April 2014 04:00 PM UTC
  • No Admission Charge




Agenda

Dr. Lana (Xiaolan) Song is a Director at JP Morgan Chase leading Core Risk Modeling group for Chase Card Services. Lana obtained her Ph.D. in Statistics from Rutgers University in 2003. She also has an MS in Industrial & Systems Engineering from Rutgers and a Master in Statistics from Renmin University of China. Lana joined JP Morgan Chase (its predecessor Bank One) in 2002. She began her career by building Bank One's first customer level credit risk model. Lana is responsible for core risk scores and decision support tools for all aspects of credit risk decision points across life-cycle of Chase's 60 million credit card customers. Examples of core risk scores include proprietary credit bureau attributing system and models to support both underwriting and customer management decisions, internal behavior based risk assessment models with 360 degree of Chase customer view, and ground breaking proprietary models in fraud detection on both transaction authorization and account protection. Prior to joining Chase, Xiaolan has worked for United Technologies Research Center (UTRC) and Educational Testing Service (ETS) as a summer consultant.

Dr. Jun Bai is a Senior Manager at JP Morgan Chase Card Services (CCS) responsible for CCS balance transfer analytics and strategy development. He obtained his Ph.D. in Industrial & System Engineering from Rutgers University in 2004. He also holds an MA in Economics from American University-Washington DC and an MS in Statistics from Rutgers University. Before joining Chase, he has worked in Agricultural Bank of China as a statistician after graduating from Renmin University of China (RUC) with a BS in Statistics. He also worked for Merrill Lynch and Unilever as a summer associate. His research interests include statistical modeling, financial analytics, warranty design and analysis. He is a referee for various journals such as European Journal of Operational Research, IEEE Trans. on Systems, Man, and Cybernetics-Part A, and IEEE Transactions on Reliability.