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The Cumulative Costs of Predatory Practices

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Spending by young, educated workers has historically been an important component <strong>of</strong> overall<br />

consumer spending. Also, the act <strong>of</strong> household formation, which has been depressed in the years<br />

since the recession, boosts homeownership and the general economy. High levels <strong>of</strong> student<br />

loan debt threaten to temper the historically positive impact college graduates have had on the<br />

nation’s economy.<br />

Payday Lending<br />

Payday loans also create externalities that affect the macroeconomy. One study found that the<br />

money payday borrowers spent on fees and interest would have been more efficiently spread through<br />

the economy if it had remained in the pockets <strong>of</strong> the borrowers. Payday lending led to a net drain <strong>of</strong><br />

nearly $1 billion and over 14,000 jobs from the economy in 2012 (Lohrenz, 2013).<br />

Unknown <strong>Costs</strong><br />

In some instances, publicly available data, such as state payday loan regulatory data or Home<br />

Mortgage Disclosure Act data, provide critical information that helps to quantify the cost and<br />

scale <strong>of</strong> abuses and hold lenders accountable for abusive practices. CRL and others have used these<br />

data to estimate the costs <strong>of</strong> particular lending abuses—costs that have been cited throughout this<br />

chapter. However, comprehensive public data are not available for all consumer loans. For example,<br />

comprehensive data about the terms and use <strong>of</strong> consumer installment loans are largely not publicly<br />

available.15 More information would be helpful in improving understanding <strong>of</strong> how installment loans<br />

work and addressing specific abuses within the market.<br />

In other areas, we are missing key pieces <strong>of</strong> data that are necessary to fully estimate the scale or scope<br />

<strong>of</strong> abuses. For example, we do not know how many debts the typical debt-settlement program participant<br />

settles, making it difficult to estimate how many consumers benefit or suffer and by how much<br />

(Parrish & Harnick, 2014). In another case, although we can estimate the impact <strong>of</strong> predatory auto<br />

lending practices such a “yo-yo” scams and financing negative equity on the total cost <strong>of</strong> an individual<br />

loan, public data are not available to estimate with confidence how many people these predatory<br />

practice affect or whether specific populations are targeted (Davis, 2012). Policymakers and regulators<br />

at the state and federal level should continue to require data from lenders, analyze data they<br />

collect, and make data available for public review.<br />

15 SEC filings and other sources do provide some important information about such loans.<br />

Center for Responsible Lending 21

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