Bankrate Loan Analysis by Lending Partner

In this analysis, I will take a close look at the different factors that effect the approval of loans by the 3 different lending partners and give my recommendation for the most efficient path to maximize revenue and match clients to the proper lenders.

Step 1: Examine the Factors that Effect Loan Approval the Most

At a macro level, several key attributes of loan applicants significantly influence their likelihood of approval. For instance, an unemployed individual with a low credit score has a much lower chance of receiving a loan compared to someone with an excellent credit score and a high monthly income. In this section, I address questions to identify the variables that most strongly impact a person’s likelihood of loan approval.

Income:

This graph illustrates the distribution of monthly income based on approval status. Individuals with higher incomes have a greater chance of loan approval, as the median monthly income for approved applicants is nearly 50% higher than that of those who were not approved.

Living Above Ones Means?

Above, I created a variable to identify those who spend more than 30% of their monthly income on housing (the recommended threshold to stay below) and used this to understand better the proportion of individuals who were and were not approved. For those who were not approved, about half spent over 30% of their monthly income on housing, whereas for individuals who were approved, that number fell to about 30%. This indicates that those who spend high percentages of their monthly income on housing will have worse chances for loan approval.

Employment Sector as a Predictor?

Interestingly above, we find that those working in the Financial and IT sectors have the greatest chance of approval for loan. There are certainly many factors that go into this, but financials could be the top of the list due to the unique knowledge that one in this industry would have when compared to others.

Does the Reason for the Loan Have an Impact?

Above, it appears that there is little impact on the chance of approval of a loan depending on the reason for the loan. This is a bit surprising, as I would assume that reasons of debt consolidation or credit card refinancing would result in lower chance of approval, when compared to something such as home improvement.

Step 2: Analysis on the Lender Level

Now that we have done some general analysis of the factors that affect loan approval, we will look closer at each of the three specific lenders and how they behave uniquely in the lending process.

Approval Rates by Lender

With all factors considered, Lender C approves the highest portion of loan requests (About 17%) when compared to Lenders A and B (About 7% and 11% respectively).

What if the individual has…good credit, a full-time job, & has never gone bankrupt/foreclosed on a house?

To no surprise, the chance of approval increases significantly with all three lenders for a person with these characteristics. Lender C still leads as the chance of approval jumps to about 36%.

Do the Lenders Work With Individuals of Specific Incomes?

Next, I decided to analyze the average monthly incomes of those with approved loans from all three lenders. Surprisingly, in the case of lenders A & B both displayed median monthly incomes around $7,500 and for lender C the median monthly income was much closer to $5,000.

Do the Lenders Tend to Write Loans of Similar Amounts?

Next, I decided to see if there was a similar trend in the loan amounts (Ex: Since Lender C works with lower-income individuals do they give less in loans?). There is not a significant difference in the average loan amounts by each lender.

Lender Approval By Percentage of Each Applicant Employment Sector

In this chart, we see the breakdown of employment sectors for approved individuals by each lender. It appears there is a high concentration of those working in IT among all three lenders, and especially with lender A.

Step 3: How to Maximize Revenue

Now that we have a better idea of the types of applicants that each lender approves, we will now take a closer look at how this analysis could aid in raising revenue by directing certain customers to specific lenders.

Revenue Per Applicantion by Lender

Here, we see that for each applicant to any of the three lenders, the expected revenue will be between $25-30, as we must consider both the conversion rates for each lender and the different offer amount that they each provide for approvals.

Earlier visualizations showed that individuals with good credit, full-time employment, and no history of bankruptcy had the highest approval rates with Lender C. Another graphic highlighted that approved clients from Lender C had a lower median monthly income compared to those with the other two lenders. Together, these insights reveal an opportunity to recommend highly qualified clients below a certain income threshold to Lender C, potentially maximizing expected revenue.

Estimated Revenue from Sending Highly Qualified Individuals with Lower Income to Lender C from Lenders A & B

In this analysis, I estimated the projected revenue from individuals with good credit scores, full-time employment, no prior bankruptcies, and a monthly income under $5,500—around the median income of approved clients with Lender C. This income criterion highlights that Lender C’s approved clients have a lower median monthly income (just above $5,000) compared to those with Lenders A and B (around $7,500). Additionally, it’s important to note that qualified clients have a significantly higher approval rate with Lender C than with the other two lenders (approximately 36% versus 21% and 24%, respectively). Projected revenue was calculated by identifying individuals meeting these criteria with Lenders A and B, then applying Lender C’s revenue projections to this group. Ultimately, directing highly qualified, lower-income clients from Lenders A and B to Lender C could increase projected revenue by an estimated $5,000 to $6,000.