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

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)

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??

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?

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.

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.

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%

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.

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?

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.

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.

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.

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 www.dmmetrics.com mike.morgan@dmmetrics.com