Visualization | Smoak Signals | Tableau, Excel, SQL

Background

As a data and visualization endeavor, I put together an infographic that highlights some product complaints analyses I performed using publicly available Consumer Financial Protection Bureau data.

In case you are unfamiliar with the CFPB, it is an organization that was created in 2010 as a result of the financial calamity that gripped that nation during the great recession. The CFPB’s mission is to write and enforce rules for financial institutions, examine both bank and non-bank financial institutions, monitor and report on markets, as well as collect and track consumer complaints.

On the bureau’s website they host a consumer complaint database that houses a number of complaints that consumers file against financial institutions.

Each week we send thousands of consumers’ complaints about financial products and services to companies for response. Those complaints are published here after the company responds or after 15 days, whichever comes first. By adding their voice, consumers help improve the financial marketplace.

Process

I downloaded the complaint database from the CFPB’s website and then decided to concentrate on selected bank complaints from the many financial institutions that are present in the database. I settled on a self-defined “National” category and a “Regional” category and then analyzed the percentage of complaints across three product spaces (Mortgages, Bank Accounts & Credit Cards).

I felt a percentage approach would be more useful than just merely listing a total count of complaints. The national banks category consists of the four nationally known firms: JP Morgan Chase, Wells Fargo, Bank of America and Citibank. The regional banks category consists of ten fairly large regional banks that have product offerings similar to the national banks.

It’s fairly obvious that the behemoth national banks are going to have more mortgage complaints than the much smaller regional banks on a total count basis. The more interesting analysis is to look at the rate of mortgage complaints for the national banks as compared to the regional banks (e.g. divide a specific product complaints total like mortgage by the total complaints for all products; calculate this percentage for national and regional categories across all three products).

I carried out this analysis using the ggplot package in R to generate the base graphics for the infographic. Adobe Illustrator was then used to further refine the graphics into what you see below:

I have an additional unrefined chart that is a straight output from the ggplot package in R. I didn’t have enough space on the infographic to include it there. However, this analysis is the same as is represented in the bottom quadrant of the infographic, except that it solely applies to regional banks.

The analysis consists of totaling all of the specific PRODUCT complaints filed against a particular bank and then dividing that number by the total number of ALL complaints filed against the individual bank (e.g. Total mortgage complaints filed against a bank/total complaints filed against a bank). I call the resulting number the Complaint Ratio.

In the ggplot graph output below we can see that Regions’s “Bank Account or service” product represents about 67% of all complaints filed against Regions. If I were to break out the numbers on a total count basis, we’d see that Regions’s overall complaints total is relatively small compared to other banks. However, the bulk of its complaints are distributed in the “Bank Account or service” product area.