National City Bank Data Analysis

Scenario

You are part of a research and modeling team at National City Bank.  You team has been asked to create a customer propensity model for a new product, specifically a line of credit against a household’s used car. Since the line of credit product is only in pilot, you are asked to identify the next 100 customers from a prospective customer list to contact.  Bankers will call and direct mail will be sent to households your model identifies with the greatest probability of accepting the offer.  Once your team has modeled and identified the customers, you must present your findings to the bank’s chief product officer.  Once she/he feels comfortable with your proposal, marketing will begin its process.  

You are asked to examine the historical data from 4000 previous calls and mailings for the line of credit offer.  Using this historical data, and any supplemental data, create a propensity model, evaluate it and identify by uniqueID the top 100 households to contact from the prospective customer list.  Additionally, bank executives are eager to learn more about the customer profile for historical and top prospective customers.  As a result, variable importance and sound EDA will aid the presentation.  Your team will need to turn in code and PowerPoint slides.

‍

Data

Source:  https://www.kaggle.com/kondla/carinsurance

Supplemental data represents fictitious 3^rd party data that the bank would purchase to improve the model’s accuracy.

As a result, there is some moral ambiguity related to the use of the dataset.

The data set your business analysis team is using has been authorized, cleaned and anonymized.  

The original data, publication, code, and codebook was obtained here: https://github.com/rudeboybert/JSE_OkCupid”
‍

marketing team's goalPublic R-Studio examination of the data example

https://rstudio-pubs-static.s3.amazonaws.com/209370_b62220c849b946088b463fdbec935848.html

‍

Keynote Presentation

‍