Are Defaults Really Just Customer Acquisition Costs?

An alternative framework for Defaults in Lending Businesses

Lending businesses have four primary cost centers: (1) cost of origination (2) cost of underwriting (3) cost of capital and (4) credit losses. Oftentimes, the cost of origination is directly correlated with the credit losses.

For example, if you originate loans to borrowers with 700 FICO scores and above, you will be passing on applicants that are below that metric, who may be deemed more risky, which drives up the blended customer acquisition cost (CaC). A numerical example goes as follows:

• Number of Applicants: 200

• Number of Qualified Applicants: 100

• Loans Originated: 100

• Total Cost of Origination: $4,500

• Total Cost per Origination: $45

If we assume of the 100 non-qualified applicants, 50 would qualify if the FICO threshold was lowered to 650, the numbers would be revised below:

• Number of Applicants: 200

• Number of Qualified Applicants: 150

• Loans Originated: 150

• Total Cost of Origination: $4,500

• Total Cost per Origination: $30

By moving up the risk spectrum and increasing the addressable market, the lender has decreased their CaC by 33%. The question remains, is this a good decision?

The answer, as in most instances, is “it depends”. 

Vanity Metrics for Fundraising:

Some lenders can use this as a trick when fundraising, as CaC is realized at the point of origination and defaults are recognized after some type of realization (which could be many months down the line). In some cases, lenders can have convoluted default definitions that delay write-offs or defaults for over a year from when the loan becomes troubled. This approach is myopic and can impact the financeability of the assets moving forward, but can help increase origination volume and equity dollar inflows.

Unit Economic Improvements:

If the marginal saving on the CaC is greater than the probability weighted default increase, then it is worthwhile to expand the credit box. The math is as follows:

Scenario 1: 700 FICO

1. Cost of Originating Loan: $45

2. Loan Size: $1,000

3. Interest Earned over Life: $100

4. Total Collections: $1,100 (#3 + #4)

5. Probability of Default: 3% or $33 (#4 x #5)

6. Gross Profit per Loan*: $100 - $33 - $45 = $22 (#3 - #5 - #1)

*Excludes Cost of Capital

Scenario 1: 650 FICO

1. Cost of Originating Loan: $30

2. Loan Size: $1,000

3. Interest Earned over Life: $100

4. Total Collections: $1,100 (#3+#4)

5. Probability of Default: 4% or $44 (#4*#5)

6. Gross Profit per Loan*: $100 - $44 - $30 = $26 (#3 - #5 - #1)

*Excludes Cost of Capital

In this example, by opening the credit buy-box to 650 FICOs and increasing defaults on a relative basis by 33% or an absolute basis by 1%, the lender has improved their gross profit margin from 22% to 26% (an 18% relative improvement). For longer duration loans (such as mortgages), the delta can become more significant, as the lifetime value of the loan is greater due to the higher total interest accrued over a longer period of time.

Underwriting Model Improvement:

As in any discipline, the underwriting model and risk teams learn more from mistakes than they do from successfully completed loans. Therefore, it is important for lenders to originate loans slightly outside of the credit box from time to time to better understand the inputs that are correlated with successful and unsuccessful outcomes. There is no way to understand the viability of a new customer base without learning how loans to that demographic perform.

If the model becomes smarter on a broader population, future credit decisions will be improved (thereby lowering losses) and the set of customers that can be lent to will be greater (thereby lowering CaC).

Repeat Customer Usage:

In some consumer lending disciplines, first time customers are loss-leading, meaning their defaults exceed the revenue that they generate for the lender. So while a group of borrowers may look unprofitable out of the gate, in reality they could be a valuable customer segment in the long run. Repeat customers typically have significantly lower rates of default and generate strong returns. That is why many lenders will offer interest rate savings to repeat customers. The retention rate, performance of repeat borrowers and re-lending opportunities will determine whether the loss leading first-time customers are worth the expense.

In this instance, the losses on the first time customer are a form of CaC as they are spending money on unprofitable customers to identify long-term, profitable customers.

In Conclusion:

Lending businesses are hard. Money is a commodity and each lender’s money is as green as the next. Preventing pricing margin compression without increasing defaults or customer acquisition costs is the name of the game. Generally, when a lender begins to move down the risk spectrum, it is a sign that the CaC has gone up and the only way to offset the additional CaC would be to expand the population. Unfortunately, in most instances this leads to deteriorating performance beyond the increased revenue from the new originations, but this is not always the case.

As detailed above, taking additional risk has many forms for paying off in the long run, all of which decrease upfront CaC metrics. So, as a lender, it is important to manage these trade-offs and take a data-driven approach to find the balance between risk and CaC.

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