Findings from the Field: Consumers and Small Dollar Credit• Used payday loan, pawn loan, deposit...

© 2012 Center for Financial Services Innovation


Findings from the Field: Consumers and Small Dollar Credit

Rob Levy - Manager, Innovation and Research, CFSI Josh Sledge - Analyst, Innovation and Research, CFSI

Rourke O’Brien - Researcher, Princeton University Center for Financial Services Innovation

Underbanked Financial Services Forum June 13, 2012


In the consumer’s own words… “I have a hard time adjusting to the fact that everyday expenses - food, gas, utilities, meds, everything has gone up; and yet my salary stays the same; an hourly rate that has not changed in two years.”

"Due to [the] loan repayment terms, I was forced to continually take out another loan just to meet my basic needs. It was almost like modern day sharecropping in the form of a loan. I wish I had never taken the first loan.”

“My loan experience was a good one. The people were very nice to deal with and the process was quick and easy.”

“These people gave me a chance when no one else would help me out, and I did not disappoint them. I paid every penny back on time as scheduled.”

“Do not ever get a payday loan if you can help it. They are full of traps and crap.”


An Examination of Small-Dollar Credit Consumers

Background • Funded by the Ford Foundation • Two-Part Study

• Quantitative Survey >> Big picture understanding, data analysis (July 2012) • Qualitative Study >> Consumer voice, product-specific focus (Q4)

• Key research areas of focus • Demographics and financial state • Consumer need • Purchase decision process • Experience

Methodology for the Quantitative Study

• Fully-representative Knowledge Networks online panel • Adults (18+) with less than $75,000 in household income • 1,100+ consumers of SDC receive full survey

• Used payday loan, pawn loan, deposit advance, non-bank installment loan, or auto title loan in past 12 months

• 500 consumers of “mainstream” credit answer 3 questions for comparison • Used credit card, personal loan, friend/family, etc. WITHOUT using SDC

product in past 12 months


Who are SDC consumers?


Who are SDC consumers?

43%

38%

20%

26%

40%

34%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

$0k - $25k $25k - $50k $50k - $75k

% o

f Seg

men

t Pop

ulat

ion

SDC Consumers

Non-SDC Consumers

Distribution of Income for SDC and Non-SDC Consumers


What is the credit used for?

0% 5% 10% 15% 20% 25% 30% 35% 40% 45%

For home repairs

To pay back another loan

To help out friend/family

Car Related (Purchase or repair)

To pay rent

For my general living expenses(e.g. food, clothing)

To pay utility bills

% of Segment Population

Very Short-Term

Short-Term

All SDC Users


Why was there a funds shortage?

0% 5% 10% 15% 20% 25% 30% 35% 40%

I planned to make a major purchase thatexceeded my monthly income or savings

(e.g., car or truck, major appliance)

I spent most of my money that monthpaying off a previous loan

I had an unexpected drop in my income(e.g., lost job, hours cut, benefits cut)

My general living expenses areconsistently more than my income

I had an unexpected expense (e.g.,medical emergency, car broke down)

I had a bill or payment due before mypaycheck arrived


Very Short-Term

Short-Term

All SDC Users


Additional steps taken to cover credit need

0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%

Also used another loan product

Worked more hours/Earn moreincome

Deferred or skip paying bills

Went without certain basic needs

Reduced general spending


Very Short-Term

Short-Term

Any SDC User


Usage of savings to cover credit need

Had No Savings, 66%

Had Savings, but Chose Not to Use

Any, 7%

Used Some, but Not All

Savings, 12%

Used all Savings, but Still Short,

16%


What loan attributes matter most?

Average Rating (Scale of 1-5)

Loan Attributes All SDC

Consumers Very Short-

Term Short- Term

How quickly I can get the money 4.4 4.4 4.4

I Can Qualify for this loan 4.4 4.4 4.5

Clear Terms/Knowing exactly what I'll pay 4.3 4.3 4.4

Amount I Can Borrow 4.2 4.2 4.3

Term or Length of Loan 4.1 4.0 4.2

Easy to do/few forms 4.0 4.0 4.0

Ability to pay back over multiple payments 3.9 3.7 4.3

Fees 3.9 3.8 4.1

Feel comfortable/Staff is Friendly 3.9 3.9 3.9

Store location convenient 3.8 3.8 3.8


Why not use other credit options?

Credit Card Overdraft Loans from Friends and Family

I don't qualify (32%)

Too expensive (25%)

I did - in addition to SDC (21%)

I maxed out or can no longer use this product

(19%)

Too inconvenient (17%)

Too inconvenient (20%)

Too expensive (16%) I don't qualify (15%) Not offered near me (17%)


How do Very Short-Term Credit Consumers Fare?

Yes, 62% No, 38%

Did you pay off your first loan on time?

Average # of rollovers: 5.1

Payday

Yes, 55% No, 45%

Did you pay off your first loan on time?

Pawn

Average # of extensions: 2.4

Did you pay the first loan w/o overdrawing your

checking account?

Deposit Advance

Yes, 85%

No, 15%

Participants reporting taking out another advance in the next month: 35%


How do Short-Term Credit Consumers Fare?

Yes, 76%

No, 24%

Did you pay off the loan by the end of the original term?

Average number of refinances: 2.9

Installment Loans

Did you pay off the loan by the end of the original term?

Average number of refinances: 3.0

Auto Title Loans

Yes, 71%

No, 29%


Why are so many consumers repeat users?

Regression Analysis: What factors contribute to rollover

or repeat usage?

Rourke O’Brien – Researcher, Princeton University


Regression Analysis…

• What it gets us: – Allow us to test for an association between two

variables “controlling” for other factors – Allows us to test for whether an observed difference

between groups is “statistically significant”

• What it doesn’t get us: – “Proof” or “Causality” that X leads to Y – “Statistically Significant” ≠ “Substantively Significant”


What predicts payday rollover?

• Outcome: Number of payday roll overs

• Primary Predictor: Loan to Income Ratio

• Key Controls in the models: -Income -Race -Age -Education -Marital Status -Urban Status -Whether first time user -Household Size -Sex


OLS Regression Predicting Number of Payday Rollovers (1) VARIABLES howmanyrollover paydaybyincome 1.271e+06* (7.148e+06) urban 0.466 (0.239) loghhinc 1.319 (0.443) firsttime 0.583 (0.224) black 0.693 (0.280) hispanic 0.642 (0.346) other 0.547 (0.379) Age 0.993 (0.0104) married 0.858 (0.292) widowed 1.400 (1.012) cohab 2.404 (1.770) divorcedorsep 1.366 (0.839) lessthanhs 0.630 (0.361) somecollege 0.919 (0.335) college 1.164 (0.618) hhsize 0.863 (0.0950) Male 1.092 (0.413) Constant 5.583 (19.80) Observations 320 R-squared 0.153

Notes: *** p<0.001, ** p<0.01, * p<0.05. Loan specific weights used in analysis.


Consumer’s Reason for Borrowing

• Motivating Question: Is there a connection between consumer’s reported reason for turning to SDC and loan outcomes?

• Primary Reasons for Needing to Borrow – Unexpected Income Drop (~25%) – Unexpected Expenses (~32%) – Expenses Routinely Exceed Income (~30%) – To Make a Major Purchase (~8%) – Bill or Payment Due (~32%) – Money Spent Paying Off Previous Debt (~9%)


Consumer’s Reason for Borrowing

Are borrowers who report needing to borrow because their expenses routinely exceed their income

more likely to:

• Payday: Rollover • Pawn: Extend term of loan • Autotitle: Refinance Loan • Salary Advance: Use Loan Next Month


Payday Rollover

OLS Regression Predicting Payday Rollover Notes: *** p<0.001, ** p<0.01, * p<0.05. Loan specific weights used in analysis.

(1) VARIABLES howmanyrollover whyborrow_expexceedincome 2.738* (1.205) paydaybyincome 6.773e+06* (4.646e+07) urban 0.368 (0.197) loghhinc 1.426 (0.512) firsttime 0.483 (0.204) black 0.750 (0.317) hispanic 0.552 (0.329) other 0.747 (0.431) age 0.988 (0.0107) married 1.148 (0.390) widowed 1.637 (1.227) cohab 2.781 (2.255) divorcedorsep 2.024 (1.241) lessthanhs 0.528 (0.320) somecollege 0.896 (0.359) college 0.960 (0.536) hhsize 0.864 (0.102) male 0.935 (0.358) Constant 0.422 (1.597) Observations 320 R-squared 0.094


Pawn Extension

Logistic Regression Predicting Pawn Loan Extension (1) EQUATION VARIABLES odds ratio pawn_extended whyborrow_expexceedincome 2.730* (1.097) pawnamtbyincome 0.441 (2.071) urban 0.482 (0.294) loghhinc 1.161 (0.287) firsttime 1.261 (0.557) black 1.223 (0.573) hispanic 0.821 (0.446) other 0.0995* (0.0898) age 1.001 (0.0166) married 1.719 (0.991) widowed 0.950 (1.260) cohab 1.187 (0.703) divorcedorsep 2.282 (1.443) lessthanhs 1.040 (0.571) somecollege 1.838 (0.803) college 1.833 (1.459) hhsize 1.021 (0.121) male 0.874 (0.342) Constant 0.0778 (0.178) Observations 272 Pseudo R-squared 0.0969



Autotitle Refinance

Logistic Regression Predicting Autotitle Refinance (1) EQUATION VARIABLES odds ratio auto_refinance whyborrow_expexceedincome 8.642** (6.130) autoamtbyincome 0.000245 (0.00136) urban 0.270 (0.231) loghhinc 0.646 (0.315) firsttime 1.107 (0.853) black 6.902* (5.853) hispanic 7.279** (5.415) other 3.650 (5.429) age 0.995 (0.0286) married 0.620 (0.455) divorcedorsep 0.507 (0.655) lessthanhs 0.214 (0.218) somecollege 2.565 (1.988) college 0.936 (1.040) hhsize 1.267 (0.201) male 0.363 (0.277) Constant 24.05 (119.1) Observations 126 Pseudo R-squared 0.249



Salary Advance Next Month

Logistic Regression Predicting Salary Loan in Subsequent Month (1) EQUATION VARIABLES odds ratio salary_loannextmonth whyborrow_expexceedincome 3.402+ (2.212) salaryamtbyincome 0 (0) urban 1.915 (1.327) loghhinc 0.523 (0.287) firsttime 0.225* (0.169) black 2.195 (2.180) hispanic 1.119 (0.837) other 0.531 (0.506) age 1.005 (0.0230) married 1.244 (1.088) widowed 5.565 (9.163) cohab 0.654 (0.499) divorcedorsep 4.642 (4.793) lessthanhs 6.092* (5.401) somecollege 12.14** (10.63) college 3.769 (3.527) hhsize 1.033 (0.225) male 0.516 (0.340) Constant 35.37 (202.2) Observations 137 Pseudo R-squared 0.259

Notes: *** p<0.001, ** p<0.01, * p<0.05, +p<.10. Loan specific weights used in analysis.


Summary Findings on Predictors of Repeat Usage

• Among payday borrowers, a higher loan to income ratio appears to be associated with more roll overs, net of other financial and sociodemographic characteristics.

• SDC users who report that their monthly expenses routinely exceed their income appear to be more likely to “roll over” or the equivalent across SDC products


Consumer Experience

55% 58%

61% 58%

49%

22%

12% 9% 10%

16%

0%

10%

20%

30%

40%

50%

60%

70%

Payday Pawn Direct DepositAdvance

InstallmentLoan

Auto Title Loan

Overall, How Satisfied Were You With This Loan? 1 (Not Satisfied) to 5 (Very Satisfied)

Rating of 4-5

Rating of 1-2


Consumer Experience Short-Term Medium-Term

Payday

Loan Pawn Loan

Deposit Advance

Install-ment

Auto Title

Fairness Overall, how fair did you consider the terms of your loan? 3.26 3.63 3.73 3.64 3.31 Average rating on a scale from 1 (Not Fair) to 5 (Very Fair)

Expectations % reporting cost of loan was more than expected 40% 19% 15% 26% 43% % reporting it took more time than expected to repay the loan 32% 29% 20% 17% 32%

Would you use the product again?

Yes, without hesitation 33% 44% 53% 45% 22% Maybe, if I have no better options 44% 44% 41% 39% 55% No 22% 10% 5% 14% 22%


Conclusions from our research • SDC consumers have a diverse and complex set of needs,

choices, and experiences

• Too many consumers rollover, refinance, repeat use and have very negative experiences

• Consumers would benefit from a multiplicity of safe, affordable, high-quality credit products and tools designed to meet different needs for different people

• Successful credit products will combine affordability with accessibility, speed, and clear terms

• Credit can play a role in consumers’ lives alongside (and possibly linked to) savings

• Sound underwriting will be critical to preventing repeat usage

• No easy answers here. There is still much to understand…

20 N. Clark Suite 1950 Chicago, IL 60602

www.cfsinnovation.com

http://www.cfsinnovation.com/

+

Jennifer Romich University of Washington Jody Meisel Seattle, Washington

Consumers’ Views on Small Dollar Credit

+ 11 Consumers Ages 39 – 70

Most had some college

5 homeowners

7 women

Spoke with interviewer for 1-2.5 hours

+

Describe your financial life and money management

“I’m recovering… kinda slowly but surely do get back to where I want to be, where I can be comfortable” -Bob “I don’t consider myself as low-income, but I made some bad choices in my life” -Jane

+ Why borrow?

“Tell me about the time when you decided to take out the loan, what was going on?”

“Everything. I can't remember any one specific thing. It was right around the holidays. …the water main had broken… And when the water came back in, it flooded my bathroom … [and] the holidays, I do know that much. I had to send [my daughter] some money from mom, and I can't remember precisely what it was, but anyway, I needed some money. “

+ Product choice

“I’m not trying to do a cycle where it just continues and continues…. I don’t like the idea of the interest rate being so expensive. [But] I understand it, because of the risk factors. “ -Jane

Photo: Rinkjustice

+ Loan experience

“Well you type in your name and your address and stuff and you turn it in. … then about 30 minutes later, you had a call, they asked me some questions about my work, how long I’ve been employed. ... And they said, ‘Ok, boom.’ The next day it was in my account.

-Luke

+ Impact When you think about your ZestCash loan, how has it impacted your financial life since you took it out?

“It really hasn't. It's just extra money that I got, well, ya know, I try to balance it, so that when I know the first payment, I pay what I got to pay, I take care of what I have to take care of while I got it”

-Ivy

“I think it has helped me when I’ve needed it (laughs). It’s helped me make sure I pay my other bills and stuff when I was stupid with my money, so I do think it offers a service. I think people just need to be smart about it.

-Luke

Thank You

40

Emerging Opportunities for Innovation in Small-Dollar Credit

Kim Manturuk Senior Research Associate in Financial Services UNC Center for Community Capital University of North Carolina at Chapel Hill

Pre-Conference Workshop on Findings From The Field – Consumers and Small-Dollar Credit

41

Small-Dollar Credit Customers Hard to Find

4% 2% 6%

11%

77%

Source: 2011 North Carolina Comissioner of Banks Consumer Banking and Finance Survey

Auto title loan

Payday loan

Installment loan

Pawn loan

No small-dollarcredit products

42

CFSI’s Compass Principals for Credit Products

Report to credit bureaus

Support repayment

Market transparently Price fairly

43

Very Short Term Loans = Too Short Term Loans

Low loan balance

borrower can repay quickly

High fees so lender can

achieve profitability

44

Disclosures Need Improvement

0%

10%

20%

30%

40%

50%

60%

Payday loan Pawn loan Direct depositadvance

Installmentloan

Auto title loan

Cus

tom

ers

who

did

not

kno

w lo

an c

ost i

n ad

vanc

e

Source: CFSI Research on Small-Dollar Credit

45

How Much Will This Loan Cost?

47

Convenience and Accessibility Are Important

48

Underbanked But Not “Under-Smartphoned”

growth in iPhone use in 2011

use mobile banking

Smartphone is primary internet connection

Sources: Fjord Consulting and Pew Research Center

Minorities own smartphones

49

Underbanked Borrowers Are Not High-Risk

55% paid at initial repayment date

38% extended loan

5% relinquished collateral

item complete default rate

Paw

n lo

an o

utco

mes

Source: CFSI Research on Small-Dollar Credit

50

Most Existing Products Do Not Meet Consumer Needs

Reasonable cost

Time to repay

Installment payments

Disclosures

Consumer needs

Profitability

Long-term customers

Cost covers risk

Lender needs

51

Strategic Partnerships Reduce Costs

Lender + Employer =

Lender + biller =

52

Technology Can Reach Underbanked Consumers

Payment apps Money management and savings apps Loan

apps?

53

Underbanked Consumers Operate Through Many Channels

54

Even Traditional Financial Institutions Can Succeed in Small-Dollar Credit

12% APR Includes savings

< 0.2% default ~200,000 loans/year

NC State Employees Credit Union Salary

Advance Loan

55

Research and Evaluation Are Crucial to Understand What Works

Findings from the Field: Consumers and Small Dollar Credit• Used payday loan, pawn loan, deposit...

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