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http://www.responsiblelending.org “Under the Hood” Predatory Lending in Dealer-Arranged Auto Loan Financing Delvin Davis

CRL auto finance presentation

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Page 1: CRL auto finance presentation

http://www.responsiblelending.org

“Under the Hood”

Predatory Lending in Dealer-Arranged Auto Loan Financing

Delvin Davis

Page 2: CRL auto finance presentation

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Research Questions/Objectives

Illustrate different dynamics working within dealer-arranged auto financing.

Examine how these factors influence both loan affordability and sustainability.

Publish consistent data points on the auto loan industry that can be usable elsewhere. Including data on Buy-Here Pay-Here Dealers

Page 3: CRL auto finance presentation

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Dealer-arranged (Indirect) Auto Financing

Background Data on Indirect Auto Lending and the Dealer F&I Department

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Total Auto Loan Volume(Billions of dollars)

365.1 367.2 349.8 356.5 358.5 354.7 340.9 339.1291.7 301.0

380.2 371.2 370.6 381.6 407.2 420.5 446.9 436.9

352.9276.9

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

800.0

900.0

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

New Volume

Used Volume

Source: CNW Market Research

Note: New sales data from franchise dealers only. Used sale data include franchise, independent and casual sales.

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F&I Department Have Highest Margins of the Dealership

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Sales Dept (New & Used) F&I Dept Service Dept Parts & Accessories

Source: CNW Marketing Research

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Dealerships Lean Heavily on F&I for Profit

F&I profits are enhanced by high-margin practices APR Dealer Kickbacks

– $18.1 Billion in 2009

Loan Packing– Aftermarket product sales

with high markups

Yo-Yo Scams – More prevalent with low-

income borrowers

Rolling Negative Equity– “Drive one, pay for two”– Stretching loan terms

Source: CNW Marketing Research; For franchised dealers only (selling vehicles to private parties)

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Direct and Indirect Market Shares by Loan Source

Direct and Indirect Auto Lending

20.8%

45.1%

15.5%

8.3%6.9%

3.3%

79.2%

Direct Lending Captives Banks Credit Unions Independent (Finance) Other

Source: JD Power and Associates presentation (2008)

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Cars are More Affordable, but Less Sustainable

Source: Comerica Auto Affordability Index; CNW Marketing Research (repossession rates)

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Repossession Rates by Lender Type

Major captive auto finance lenders settled class action lawsuits from 2003-2007. Resulted in self-imposed

caps on interest rate markups (usu. 2.0%-2.5%)

Caps dealt with race discrimination in the extreme cases, but allowed markups across the board

Even with caps, captives still slightly outpace banks and credit unions in current repo rates

0.19%

0.47%0.54%

1.55%

0.55%

0.17%

0.38%0.52%

2.31%

0.62%

0.00%

0.50%

1.00%

1.50%

2.00%

2.50%

Credit Union Banks Captive Auto Finance/Other Total

2Q2009 2Q2010

Source: Experian data

Page 10: CRL auto finance presentation

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Auto Loan Sustainability and Affordability

Using Auto ABS Pool Data to Examine Loan Delinquency and Rate Markup

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Using Auto ABS Securities

Mined data from 76 auto ABS prospectuses Credit Info: Avg Amount Financed, Avg FICO,

% Used Sales, Avg Term, Weighted Avg APR Lender Type: Captive Lender (with and without a

markup cap), Bank, or Finance Company

Bloomberg: Pool yields and 60-Day DQ rates Added macroeconomic variables based on date of

pool issuance Unemployment rate, foreclosure rate, bankruptcy

filings, Federal Reserve market rates

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Estimating Interest Rate Markup

For each pool, an estimate for an objective investor rate was calculated. Used the reported yield and payment schedule for each pool’s class

to determine the combined yield for the pool overall. Determined what rate an investor would be willing to pay over and

above the comparable Treasury rate. Investor rates then adjusted to account for presence of

overcollateralization and withheld pool classes. (“Fitted Investor Rate”

Rate Markup = Pool Wtd Avg APR – Fitted Investor Rate

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Model 1: Dependent Variable – 60 Day DQ

Unstandardized CoefficientsStandardized

Coefficients tSig.

B Std. Error Beta B Std. Error

(Constant) 2.280 1.098 2.076 .043

Avg Amount Financed (in '000s) .007 .014 .048 .479 .634

Weighted Avg FICO .001 .002 .086 .337 .737

% Used Sales in Pool -.002 .002 -.162 -1.158 .252

Weighted Avg Term -.030 .015 -.254 -1.938 *.058

Captive with Markup Cap -.257 .116 -.252 -2.222 **.030

Bank -.252 .153 -.226 -1.648 .105

Finance Co. -.012 .157 -.011 -.074 .942

Change in Unemployment Rate -.001 .003 -.084 -.335 .739

Change in Foreclosure Rate .006 .004 .508 1.322 .192

Change in Bankruptcy Filings -.008 .007 -.468 -1.217 .229

Change in Fed Reserve Prime Rate -.010 .010 -.122 -1.014 .315

2008 Issuance .088 .281 .094 .314 .755

2009 Issuance -.214 .410 -.216 -.522 .604

2010 Issuance -.417 .421 -.367 -.991 .326

Estimated Rate Markup .112 .036 .983 3.110 ***.003

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Model 1: Key Points

Rate markup is a significant driver of 60-day DQ No macroeconomic factors are significant

Implies dealers cannot entirely blame rising DQ on the current economy

Existence of a markup cap helps to lower DQ Loan term (in months) associated with lower DQ FICO, a traditional measure of risk, is also not

significant driver of DQ Possibly explained through the markup variable

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Model 2: Dep Variable – Estimated Rate Markup

Unstandardized CoefficientsStandardized

Coefficients tSig.

B Std. Error Beta B Std. Error

(Constant) -3.414 3.548 -.962 .340

Avg Amount Financed (in '000s) -.138 .039 -.116 -3.563 ***.001

Weighted Avg FICO -.058 .004 -.740 -16.237 ***.000

% Used Sales in Pool .018 .006 .140 2.853 ***.006

Weighted Avg Term .155 .045 .150 3.486 ***.001

Captive with Markup Cap -1.241 .389 -.144 -3.193 ***.002

Bank .537 .467 .058 1.150 .255

Finance Co. -.432 .503 -.049 -.859 .394

Fed Reserve Prime Rate .948 .689 .087 1.375 .174

Fed Reserve 3-Year Rate -.602 .263 -.114 -2.289 **.025

Fed Reserve BBB Rate .215 .378 .042 .568 .572

FICO x Captive w/Cap Interaction .030 .010 .114 3.175 ***.002

Fitted Investor Rate -1.546 .842 -.183 -1.835 *.071

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Model 2: Key Points

Credit factors, including FICO are significant with Estimated Markup On surface, conflicts with notion that markups are

arbitrary and subjective Extended terms and used sales drive higher markups Credit factors still significant even after controlling for

investor rate

Markup caps significant with lower markups For captive lenders with caps, low-FICO borrowers are

marked up to a lesser degree

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Buy Here Pay Here Dealerships

Churning vehicles with high markups, promoting extremely high default rates

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Buy Here Pay Here Facts

In 2009, there were 33,000 BHPH dealerships that sold 1.8 million units, with an estimated 2.37 million (worth $14 billion) sold in 2010.

BHPH accounted for 7.56% of all sales from dealerships in 2009.

Military groups are targeted, having above-average default rates Military default rate (32.8%) Retired military default rate (41.5%)

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BHPH Industry Data

2009 2008 2007 2006

Number of Weekly Payments 132 129 134 131

Average Weekly Payment $84 $84 $85 $82

Amount Financed $9,294 $9,195 $9,085 $8,844

Downpayment $1,040 $1,089 $1,018 $900

APR 24.4% 24.5% 28.3% 25.1%

Actual Cost Per Vehicle (including rehab) $5,064 $5,284 $5,111 $4,949

% Vehicle Sale Markup 83.5% 74.0% 77.8% 78.7%

Weeks Until Dealer Breaks Even at ACV 48 50 48 49

Average Default Rate 30.1% 28.4% 27.7% 26.2%

Bad Debts (% Written Off) 20.0% 21.0% 19.0% 20.0%

Troubled Loans (Defaults + Bad Debts) 50.1% 49.4% 46.7% 46.2%

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BHPH Collections and Business Model

Model promotes “churning” of same car to several customers, maximizing profit at origination. Quick trigger is needed on repos to reclaim car value

– GPS and starter interrupt units are increasingly popular– Quote: “It’s all about collections, not vehicle sales.”

Typical consumer starts to default 4th month from origination and has most severe delinquencies in 21st month.

– Follow-up calls on trading-in for a new car happen by month 18.

Problems with underwriting standards:– Quote: Using the SWAG method: a “Scientific, Wild-Ass Guess”

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Discussion on Findings

Questions about current data and findings? Points for Discussion:

Can we still claim that markups are subjective and arbitrary?

Advocating for markup caps as a viable solution? (as opposed to flat fees)

Discussion of BHPH: Include in this report or expound in a separate study?

Advocating for any particular policy recommendations?