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«OHIO STATE LAW JOURNAL VOLUME 66, NUMBER 4, 2005 Predatory Lending and the Military: The Law and Geography of “Payday” Loans in Military Towns ...»

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Often the most populous counties in our survey had the most payday lenders statewide, but in terms of per capita density, the worst counties tended to be 536 This number of bases includes only bases with over 550 on-base personnel, including civilians, according to the DOD’s Directorate of Information Operations and Reports, Statistical Analysis and Information Division. See Department of Defense, supra note 287. Georgia’s Fort Benning, which lies close to the Alabama border, and a few others, were also included in our study, but not counted among the 109 bases mentioned above.

2005] PREDATORY LENDING AND THE MILITARY 823 military counties. Among the military counties we surveyed, we found 4765 payday lenders, which was 386 more than we predicted based on the population in these same counties. Seventeen of the 93 counties that had the highest per capita density of payday lending were military counties. Some of these counties, such as El Paso County, Texas, had huge populations while some, such as Mason County, Washington, had few people. However, both had military bases.

Moreover, we found the same pattern when we zoomed into the ZIP code level, often in even sharper focus. About sixteen million people live in a ZIP code near one of the bases in the nineteen states where ZIP code data was available, and well over a half-million of those people are currently serving in the Armed Forces. Including their families, this number probably reaches over one million. In these ZIP codes, we found about 1854 payday lenders and 3852 banks. This equaled 12.5% of the total number of payday lenders in our survey but only 8.5% of the banks in our survey. Given the population in these ZIP codes, this is about 370 payday lenders over the number we predicted based on the population in these ZIP codes. While 370 extra payday lenders may not seem an extraordinary excess, it is greater than the number of payday lenders in the entire state of Colorado, and if they were all in California it would be enough to service 5.6 million citizens.

In seven out of nineteen states, the single worst ZIP code in the state was adjacent to a military base. This is a momentous statistic given that many states have over a thousand ZIP codes statewide. Some of these worst-ranking ZIP codes would have been very difficult for us to predict before we began this study. Who among the casual observers of this industry would have guessed small towns like Lakewood, Washington; Radcliff, Kentucky; or Sumter, South Carolina would have the greatest combination of payday lending frequency and payday lending density in their states?

In five additional states, the worst payday lending ZIP code was either adjacent to a closed military base (California) or just beyond the three-mile range we set as our parameter for inclusion as an “adjacent” ZIP code. The statistical picture would have been even more compelling had we gone with a more liberal definition of geographic proximity. Many Air Force bases, such as Luke or Fairchild are isolated from the nearest commercial-retail district. This strategy removed several ZIP codes from our list, though they are by default the place where soldiers, sailors, and other service personnel and their families would take out a payday loan. Other ZIP codes were also left off our list because we used the primary on-base ZIP code to define the perimeter of what we consider the base, even though including off-base housing annexes and facilities would have included many more offending ZIP codes.

In several states, including Virginia, Washington, Colorado, and Texas, where multiple bases were found, more than half of the worst ZIP codes were within a few miles of a base. Only Ohio, Tennessee, and Florida were without a military-adjacent ZIP code among the ten worst in their respective states, and 824 OHIO STATE LAW JOURNAL [Vol. 66:653 these anomalies are easily explained. Ohio, for example, has only one base and the payday lenders and service families surrounding Wright-Patterson Air Force Base are divided among a dozen different nearby ZIP codes, of which three manage to rank among the worst 30 in the state. Tennessee only has the small Navy Support Facility and part of Fort Campbell, so there are few military targets for payday lenders in the Volunteer State. Still, the second worst ZIP code in Tennessee is just over five miles from Millington, where the Navy Support Facility is located and the second worst ZIP code in Kentucky serves Fort Campbell just over the Tennessee border. In Florida, the caveat we offer is that the second, third, and fourth worst ZIP codes in the state lie just outside our three-mile buffer but still within very easy commuting distances from the bases they serve.

The pattern of payday lender targeting becomes even more troubling when compared to bank location strategies. Banks did not follow the same location patterns as payday lenders, suggesting that neither local zoning ordinances nor ordinary business development patterns forced payday lenders into military counties, ZIP codes, and neighborhoods. Our study found that the ratio of payday lenders to banks was most lopsided in counties and ZIP codes with a military base. Twenty-seven of the worst 100 counties in our survey on our Location Quotient score were military counties, almost three times the number we expected to see.

Concentrations of competitive businesses are common in certain industries, and there are a variety of good reasons why such clustering happens. For example, some businesses benefit from cooperative agglomeration, as is the case with car dealerships, appliance stores, furniture stores and other retailers of expensive durable goods which find clustering together helps consumers comparison shop. Fast food franchises also agglomerate along certain high traffic corridors, but generally these are carefully calculated site location decisions that keep them, as a group, from exceeding the population threshold necessary for survival. In the case of payday lenders, we find the agglomeration pattern difficult to explain utilizing any of the standard rationales for such patterns.

There are businesses that agglomerate in certain spaces of a city because they are making a conscious effort to be close to their target demographic. We have no doubt that the military is a target demographic for the payday lending industry. Around each of the bases we analyzed, the greatest concentration of payday lenders anywhere in the county was within a few miles of the military base. Payday lenders crowd around the gates of military bases like bears on a trout stream. Around most of the major military installations we have mapped, we have found at least 20 and sometimes as many as 40 payday lenders within just a few miles of the base gates. The only logical reason that we can fathom as to why ten to 20 businesses competing against one another for customers would locate within a few miles of each other, while simultaneously forsaking less 2005] PREDATORY LENDING AND THE MILITARY 825 crowded locations elsewhere in the community, is that there is something peculiarly profitable about the site of agglomeration.

Some would argue that the neighborhoods we have examined near bases suffer from poverty, have large minority populations, or high population densities, but this is not the case. We have found most military neighborhoods to be relatively prosperous, not particularly crowded, and generally unremarkable from a demographic standpoint. Indeed, in several instances, such as Oceanside, California, the neighborhood adjacent to the military base is affluent and without a large minority population. We have little doubt that the payday lending industry targets poor, minority, and crowded areas, but we can confidently assert that distance to military bases is the variable that best predicts a large number of payday lenders. When considered in light of the ancient history of predatory lenders targeting military personnel and the compelling body of social scientific literature suggesting financial vulnerability of service members, our findings should stand as conclusive proof that the payday lending industry targets members of the armed forces and their families.

B. Legal and Public Policy Considerations

1. Voluntary Compliance and Industry Best Practices The public policy response of choice for the payday lending industry has been voluntary “best practices” lists written and sponsored by industry trade associations. Currently, two trade associations represent the interests of the payday lending industry: the Financial Services Center of the America (FiSCA) and the Community Financial Services Association of America (CFSA). FiSCA has a voluntary “code of conduct” which trade association members aspire to comply with.537 FiSCA’s code calls on trade association members to maintain “integrity” in eleven different business activities such as collection practices, invoking criminal process, consumer education, pricing and consumer charges,

and extensions.538 For example, the code states:

Integrity in Invoking the Criminal Process. FiSca members will never threaten to file criminal charges against a customer merely for defaulting on a debt. Criminal charges can be appropriate where a customer seeks to defraud a FiSCA Member, such as by closing their checking account or passing a false 537 Financial Services Center of America, Code of Conduct (Feb. 7, 2001), www.fisca.org/FiSCACodeCcc.pdf [hereinafter FiSCA Code of Conduct].

538 Id. Other activities for which the code suggests acting with integrity include:

marketing and advertising, operations, documentation, consumer’s right to rescind, in the industry, and as a money service business. Id.



Similarly, the CFSA best practices list encourages members of that organization to give full disclosure, truthfully advertise, encourage consumer responsibility, limit rollovers to four or the state limit, whichever is less, and comply with “applicable” laws.540 Recently, CFSA has also adopted a separate “military best practices” list. This list requires members not to garnish military wages, temporarily defer collection activity against a military customer deployed in combat, refrain from contacting commanding officers in an effort to collect a loan, honor the terms of any agreement, educate military customers, develop a brochure and a hotline, and develop and maintain a military best practices web site.541 Neither trade association’s voluntary guidelines includes any form of price limitation, leaving members free to charge unlimited interest rates. Neither trade association has committed to refrain from refinancing one payday loan with another payday loan. With carefully qualified language, both policies appear to leave open the possibility of threatening borrowers with criminal prosecution.542 Neither policy commits to comply with the Fair Debt Collection Practices Act.543 Neither trade association imposes any penalty or sanction on members who do not comply with their best practices. Also, payday lenders who do not pay dues to join either trade association do not make even a nominal commitment to comply with the policies. CFSA’s military best practices say nothing about obtaining judgments and then seizing automobiles or other property of service members, garnishing from bank accounts where wages are deposited, or garnishing the wages of service members’ spouses.

But perhaps more fundamentally, our empirical findings raise significant red flags about whether the payday lending industry will comply with voluntary standards. While collecting our data, in state after state we found significant numbers of payday lenders openly doing business who are not registered to 539 Id.

540 Community Financial Services Association of America, Best Practices for Industry (Feb. 15, 2005), www.cfsa.net/genfo/egeninf.html [hereinafter CFSA Best Practices].

541 Community Financial Services Association of America, Military Best Practices (2004), http://www.cfsa.net/genfo/MilBestPractie.html [sic].

542 For example, FiSCA’s Code somewhat ambiguously authorizes members to threaten borrowers with criminal prosecution for “passing a false instrument.” FiSCA Code of Conduct, supra note 537. CFSA’s prohibition of criminal threats is similarly ambiguous.

CFSA Best Practices, supra note 540.

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