1. Estimating Store Potential for Installment Lending
Presented by:
Mike Morgan
President, DM Metrics LLC
Strategic Consulting for Subprime Lenders

2. Direct Mail: Feeding Your Stores
Recapping the last slide from our Direct Mail topic…
For store based lenders, direct mail is a great way to keep your stores operating at full capacity.
Your busiest stores may not need any direct mail support, if they already have more customers than they can handle. You might want to exclude their ZIP codes when making mail selections.
Your average stores can probably use more loan volume from mail programs.
Your slowest stores could probably use a big boost in new customer traffic.
The answer might be to mail deeper in decile for ZIP codes near your slow stores, maybe.
But if the store is in a market with low loan potential, the remedy may be to close the store.
Using a strong response model, we can estimate loan potential for markets, to aid in deciding where to close (or open) stores.
(That was my main mission as VP of Marketing for SLFS: keep all the stores productive)

3. Good vs Bad Markets
Let’s look at how many households there are in two stores’ footprints…
And suppose your book
rates look like this by
decile…
Store A has virtually no high-response households, while Store B has predominantly high-response households.
Is the answer to mail deeper in low-response deciles for Store A, or to rethink having a store in that location at all?
Which store would you rather manage??

4. Store Closings Coming?
If and when the CFPB rule goes live, experts are expecting a big reduction in payday loan volumes.
Lenders are already shifting over into installment loan volumes – and installment loan stores need a larger area than payday stores.
Some lenders are reducing store counts now, and you can expect many more closings after the rule goes live.
But which stores should you close? And how many?

5. Rich Market Data
The good news is that strong data is available at a ZIP code level.
We can predict loan potential for every ZIP code, and thus for every store, with a reasonable amount of accuracy – at least on a relative basis.
Every lender will have different penetration rates depending on their interest rates, their approval criteria, their loan sizes, how much marketing they do, and how densely their stores are spaced.
But we can come up with estimates of loan potential that are pretty good on a relative basis between ZIP codes. In other words… this ZIP code can expect to have a penetration rate that is 5 times higher than this other ZIP code.

6. Predicting Loan Potential for ZIP Codes
Large lenders with enough history can develop a custom ZIP code penetration model that estimates what percent of the households in any ZIP code are likely to get a loan with that lender. If you don’t have that…
The next best thing is a strong response model that does a good job of rank-ordering book rate for sub-prime installment lenders…
While a response model is built to predict the odds of a prospect to book a loan in response to a mail offer, we can translate these odds into expected loan penetration rates for each decile.

7. Predicting Loan Potential for ZIP Codes
If your response model is installed at a list vendor, have that vendor provide you with household counts by decile for every ZIP code in your operating footprint…
The rest is just math. Multiply the number of households in each decile (for every ZIP code) by the expected penetration rate for each decile. That gives us an expected number of loans we could reach in each ZIP code over time.
Decile
38647
38650
38651
38652
38655
38664 1 20 11 40
298
401
300 2 79
123 82
615
1,050
337 3 - 38 42
251
290 4 73 67 25
119
295
128 5
111 83
368
671
205 6
144
160
110
637
1,200 7
131
207
225
696
1,673 85 8
356
470
1,613
3,269 9 10
267
1,463
1,128
3,753
135
350
1,059
4,599 46
Total
461
1,475
2,890
6,784
17,201
1,242
Avg Decile
5.2
6.9
8.1
7.7
3.7
Est Loans
6.8
13.9
18.5
70.0
137.1
28.6
Est Pen
1.47%
0.94%
0.64%
1.03%
0.80%
2.31%

8. Getting to Store Level Predictions
ZIP code estimates are relatively easy. Getting to store-level predictions takes a bit more work.
If your firm has already built a ZIP-store assignment table, where every ZIP code is assigned to one, and only one, store, then the work isn’t too bad. You just add up the loan estimates for all of the ZIP codes in each store’s footprint.
But if your stores share some ZIP codes, as many short term lenders do, you will need to make some assumptions about how to split ZIP codes among two or three stores based on their distance from the ZIP code.

9. Turning Loan Estimates into Store Profit Estimates
Knowing how many loans you can reach per store is very helpful in decision making.
By combining that with a quick loan profit pro forma, you can come up with an estimate of profit for every one of your stores.
Store Name
City
Est # Loans
# of Households
Est Pen Rate
Estimated Store Profit
xxx xxx
xxxxx
190
70,573
0.27%
-$88,276 to
-$64,160
258
42,570
0.61%
-$49,363
-$16,599
290
80,437
0.36%
-$31,561
$5,159
311
51,778
0.60%
-$19,408
$20,013
389
126,830
0.31%
$25,383
$74,757
394
99,911
0.39%
$27,836
$77,755
483
186,421
0.26%
$78,960
$140,240
506
191,928
$91,912
$156,070
514
167,833
$96,363
$161,510
790
75,532
1.05%
$253,956
$354,124
1,328
330,544
0.40%
$560,755
$729,101
Which stores would you close? Which would you expand?

10. A Spatial View
Loan estimates and store-profit forecasts are very useful in decision making, but it also helps to get a spatial view of your markets. Because every store you close or open or move changes the equation and impacts the loan potential for your other stores.
And it pays to have a view of competitor locations alongside your own.
Each ZIP code is color coded based on expected penetration rate, and the client and competitor stores are plotted. Mousing over each ZIP code you can see population and estimated loans.

11. An Iterative Process
It make take a couple iterations to re-imagine your store locations.
As you decide to close a low-potential store, that adds to the potential of your nearby stores.
As you move a store to a better location, that may steal some of the market potential away from one of your existing stores.
So you may need to rerun the match after your first set of changes.

12. Market Expansion The same process can be done for new markets.
By estimating loan potential in cities or states that you are considering entering, you can determine where your best expansion opportunities are.

13. We Can Help
The DM Metrics team can help with your store opens and closes…
Estimating the installment loan potential of each of your stores
Providing recommendations on which stores to close or combine
Recommendations on where to open new stores in high potential markets
State level loan potential for entering new markets
The DM Metrics team can also help with your overall installment lending efforts…
Loan approval criteria
Aligning interest rates with risk
Direct mail targeting
Risk & profit analytics / reporting