Analysis of Customer Behavior in Banking

Collaborate with a local bank and a data scientist from the Applied Analytics & Emerging Technology Lab (AETL) of the Lucy Institute for Data & Society to derive data-driven insights on customer behavior. Following a Banking 101 introduction, the project team will utilize deidentified customer records and transaction data to examine customer trends and habits, incorporating a variety of demographic factors.

Students will:

  • Develop banking domain knowledge
  • Work with real-world big data
  • Learn and practice effective visualization techniques 
  • Build experience communicating technical findings to a lay audience

Past projects:

  • Exploratory analysis of the shopping trends of debit card users
  • Development of quantitative descriptions of customers utilizing different banking products
  • Design and implementation of machine learning models to predict the strength of a customer’s relationship with the bank
Name of research group, project, or lab
Applied Analytics & Emerging Technology Lab (AETL) of the Lucy Institute for Data and Society
Website
https://lucyinstitute.nd.edu/centers-and-labs/aetl/student-opportunities/experi…
Why join this research group or lab?

The Lucy Family Institute for Data and Society is Notre Dame's hub for everything data science, an innovative nexus of academia, industry, and the public. We offer a variety of educational opportunities for students, realizing our commitment to training the next generation of data scientists.

Logistics Information:
Project categories
Applied and Computational Mathematics and Statistics
Computer Science & Engineering
Student ranks applicable
Junior
Senior
Student qualifications
  • Current Notre Dame or St. Mary’s undergraduate student – preference will be given to juniors and seniors
  • Some programming experience (Python or R preferred)
Hours per week
2 credits / 6-12 hours
Compensation
Research for Credit
Number of openings
4
Techniques learned

Students will learn data analysis techniques using Python or R

Contact Information:
Mentors
Jay Brockman
jbb@nd.edu
Professor of the Practice
Margaret Nichols
mnichol9@nd.edu
Data Scientist, Lucy Family Institute
Richard Johnson
rjohns14@nd.edu
Associate Professor of the Practice, Lucy Family Institute
Name of project director or principal investigator
Margaret Nichols
Email address of project director or principal investigator
menichols@nd.edu
4 sp. | 11 appl.
Hours per week
2 credits / 6-12 hours
Project categories
Computer Science & Engineering (+1)
Applied and Computational Mathematics and StatisticsComputer Science & Engineering