Washington, DC – CAB Meeting (AM Session) on 06/09/2017
Welcome to the Consumer Financial Protection
Bureau’s field, um — public meeting of its Consumer Advisory Board, or CAB. The Consumer
Financial Protection Bureau is an independent federal agency whose mission is to help consumer
finance work by making rules more effective, by consistently and fairly enforcing those
rules, and by empowering consumers to take more control over their economic lives. As
part of the Bureau’s mission to protect consumers, to date, we have handled over one million
complaints, and our actions have resulted in nearly 12 billion in relief to more than
29 million consumers. My name is Zixta Martinez. I’m the associate
director for the External Affairs Division at the Consumer Bureau. Today’s meeting is
being held at the Consumer Bureau’s headquarters in Washington, D.C. This is the CAB’s second
meeting of the year, and, as always, we have a packed schedule. Today’s meeting is being
livestreamed at ConsumerFinance dot gov, and a recording will be made available on the
same website. You can also follow CFPB on Facebook and Twitter.
Let me spend just a few minutes telling you what you can expect at today’s meeting. First,
I’ll introduce the CAB members. Then, the Consumer Bureau’s director, Richard Cordray,
will provide opening remarks. Following the director’s remarks, Ken Brevoort, Section
Chief for Credit Information and Policy in the Bureau’s Office of Research, will engage
the CAB in a discussion about credit visibility. Then, at 11:20 a.m., the CAB will hear from
Will Wade-Gery and Wei Zhang, respectively the assistant director and the credit card
program manager for the Bureau’s Office of Card, Payment, and Deposit Markets. The two
will lead a discussion about deferred-interest products.
After that discussion, the CAB will adjourn, at approximately 12:00 p.m. At 2:00 p.m.,
the CAB’s chair, Maeve Elise Brown, will resume the meeting. CAB members Paulina Gonzalez
and Lynn Drysdale will lead a discussion about trends and themes in the field. Following
that discussion, the CAB will hear from Grady Hedgespeth and Alan Ellison, respectively
the assistant director and the small business program manager for the Bureau’s Office of
Small Business Lending. They will lead a discussion about the Bureau’s recent request for information
about small business lending. The meeting will then adjourn, at approximately 4:30 p.m.
As many of you know, the Dodd-Frank Wall Street Reform and Consumer Protection Act, which
created the CFPB, also provided for the establishment of a consumer advisory board to advise and
consult with the CFPB in the exercise of its functions and to provide information on emerging
practices in the consumer financial products or services industry, including regional trends,
concerns, and other relevant information. Today’s meeting and discussion is in support
of this important statutory responsibility. As a reminder, the views of the CAB are their
views, and they are greatly appreciated, yet they do not represent the views of the CFPB.
So, let’s get started with an introduction of the CAB members. The chair is Maeve Elise
Brown. She is the executive director of Housing and Economic Rights Advocates in Oakland,
California. The Vice Chair is Ann Baddour. She is the director of the Fair Financial
Services Program at Texas Appleseed in Austin, Texas. Seema Agnani is the director of policy
and civic engagement at the National Coalition for Asian Pacific American Community Development
in Washington, D.C. Tim Chen is the CEO of NerdWallet in San Francisco, California. Lynn
Drysdale is the managing attorney of the Consumer Law Unit at Jacksonville Legal Aid in Jacksonville,
Florida. Kathleen Engel is a professor at Suffolk University Law School in Boston, Massachusetts.
Judith Fox is a clinical professor of law at the University of Notre Dame in Notre Dame,
Indiana. Paulina Gonzalez is the executive director of the California Reinvestment Coalition
in San Francisco, California. Julie Gugin is the executive director for the Minnesota
Homeownership Center in Saint Paul, Minnesota. Neil Hall is retired, having previously served
as the executive vice president and head of retail banking at the PNC Financial Services
Group in Pittsburgh, Pennsylvania. Brian Hughes is senior vice president and chief risk officer
at Discover Financial Services in Deerfield, Illinois. Christopher Kukla is the executive
vice president at the Center for Responsible Lending in Durham, North Carolina. Ruhi Maker
is a senior vice attor — is a senior attorney at the Empire Justice Center in Rochester,
New York. Joann Needleman is a member at Clark Hill’s Consumer Financial Services Regulatory
and Compliance Group in Philadelphia, Pennsylvania. Patrick O’Shaughnessy is the president and
CEO of Advance America in Spartanburg, South Carolina. Arjan Schutte is the founder and
managing partner at Core Innovation Capital in Los Angeles, California. Lisa Servon is
a professor of City and Regional Planning at the University of Pennsylvania in Philadelphia,
Pennsylvania. Jim Van Dyke is founder and CEO of Futurion in Pleasanton, California.
James Wehmann is the executive vice president of scores at the Fair Isaac Corporation in
Roseville, Minnesota. Chi Chi Wu is a staff attorney at the National Consumer Law Center
in Boston, Massachusetts. And Joshua Zinner is CEO of the Interfaith Center on Corporate
Responsibility in New York, New York. We also have with us Delicia Hand, Staff Director
for the Bureau’s Office of Advisory Board and Counsels.
I am now pleased to introduce Richard Cordray. Prior to his current role as the CFPB’s first
director, he led the CFPB’s Enforcement Office. Before that, he served on the front lines
of consumer protection as Ohio’s attorney general. In this role, he recovered more than
2 billion for Ohio’s retirees, investors, and business owners, and took major steps
to help protects its consumers from fraudulent foreclosures and financial predators. Before
serving as attorney general, he also served as an Ohio state representative, Ohio Treasurer,
and Franklin County Treasurer. Director Cordray? Thank you, Zixta, and welcome to this meeting
of the Consumer Advisory Board. Once again, I thank our members for sharing your expertise
and perspectives on the concerns of consumers and the issues we face at the Consumer Financial
Protection Bureau. You help us maintain our focus, prioritize our work, and fulfill our
responsibilities more effectively. We share a belief that consumers deserve fair treatment
and a more transparent and competitive financial marketplace.
Usually, in these remarks, I highlight the work we’re doing in one particular area and
describe it in some detail. Today, I will do something different. My remarks will touch
on several different issues to show more of the breadth of the work that we’re doing in
various areas simultaneously. For each, I’ll identify our goals and describe the progress
we’re making to achieve them. In particular, I’ll discuss four topics. First,
I will address our latest efforts to encourage more transparency in the credit card market
to reduce risk to consumers, especially those who are the most vulnerable. Second, I will
update our groundbreaking research into the phenomenon we have described as credit invisibility
by discussing a new report on how consumers become credit visible. Third, I will say more
about our recent request for information to help us fulfill our mandate to develop data
collection for small business financing. Fourth, I’ll describe how we intend to proceed in
formulating new rules to govern the debt collection market. Each of these topics reflects our
efforts to understand better how to support and protect consumers.
On the first topic, we’re announcing today that the Consumer Bureau has sent letters
to the top retail credit card companies, encouraging them to consider adopting more transparent
credit practices. Many retail credit cards offer consumers promotions, with deferred
interest as a financing option for certain purchases. They promise consumers that they
will incur no interest charges for a set period if the promotional balance is paid in full
at the end of the period. Our research has led to concern that these
promotions may surprise consumers with high retroactive interest charges after the promotional
period ends. The Bureau’s suggesting, instead, that companies consider a zero percent interest
promotion that is more transparent and carries less risk for consumers.
Deferred-interest financing is commonly offered on store brand credit cards. They may be marketed
as an attractive way to buy big-ticket items, such as appliances, furniture, or even medical
or dental services, while avoiding interest charges, but they can be confusing for many
consumers. Under these plans, customers are generally not charged interest if they make
payments on time and pay off the purchase balance within a set time frame, usually 6
months to a year. However, if any balance remains unpaid at
the end of that period, consumers can be hit with interest charges that are retroactively
accrued from the date of the original purchase on the entire amount of their original promotional
balance. This can happen no matter how little remains unpaid and whether or not they’ve
actually paid more than the original balance, which can be the result when they’ve made
other purchases in the meantime. All of this can make these deals confusing
and surprisingly costly for consumers. This back-end pricing is less transparent and thus
can obscure the costs and risks of entering into the promotion. The problem is compounded
if the promotions are marketed in ways that may be questionable or even illegal.
This lack of transparency can also hamstring consumers who are trying to manage their finances.
In 2015, our Consumer Credit Card Market study showed that a large percentage of consumers
who fail to repay the balance during the promotional period, and thus get hit with all of the retroactive
interest, will pay off the amount of the remaining principle and related interest charges shortly
thereafter. This suggests that many consumers could have completed the terms of the promotion
in a timely fashion, which suggests they may have misunderstood how the product works.
We saw this again in the Monthly Complaint Report we issued last week, which noted that
some older consumers on fixed incomes have expressed confusion about the terms and conditions
of deferred-interest credit promotions. The Bureau’s research has found that deferred-interest
programs tend to have uneven effects for different categories of consumers, predictably posing
the greatest cost and risk for the most vulnerable. Those with low credit scores manage to avoid
retroactive interest charges only about half the time, yet those with high credit scores
avoid interest nearly 90% of the time. When other purchases are made on the same
card before the original promotion expires, it muddies the waters further. Our 2015 study
showed that over half the people with other purchases who were assessed deferred interest
actually paid more than their full promotional balance during the promotional period. Over
one-third of these consumers paid more than 150% of their promotional balance during that
period, yet they still suffered the adverse consequences of the retroactive deferred interest
charge. The Consumer Bureau has long warned about
the pitfalls associated with deferred-interest financing, which does not reflect the general
shift toward more transparent, upfront credit card pricing spurred by the Card Act of 2009.
Its reforms aimed to reduce back-end fees and abusive credit card policies. Over the
last few years, we’ve taken legal actions against credit card companies for deceptive
marketing of deferred-interest financing and certain add-on products that carry risks for
consumers. We’ve imposed penalties, secured relief for those who were harmed, and made
clear that such practices can violate the law.
Last month, Walmart, one of the nation’s largest retailers, in partnership with one of the
largest U.S. credit card issuers, announced that it will no longer offer differed-in — interest
promotions on its store credit card. Instead, it will offer a more straightforward, zero
percent interest promotional program. Under this program, interest is not assessed retroactively
if the full balance is not repaid at the end of the promotional period. Following the promotional
period, the interest rate converts to the regular rate, and interest begins to accrue
only on remaining balances. These terms are easier for consumers to understand, and the
costs are more transparent, so we’re encouraging others to consider adopting this approach.
In the meantime, you can find consumer tips about credit card interest rate promotions
on our website, at ConsumerFinance dot gov. We have advice on ways to keep interest costs
down and how to avoid surprise charges. Consumers who have complaints about credit cards can
submit them on our website or by calling us toll-free at 855-411-CFPB.
Our second topic returns to the seminal research we’ve been doing on those who are credit invisible,
those with no credit record with a nationwide credit reporting company. The Consumer Bureau
estimates that 11% of adults in the United States, or about 26 million people, fall into
this category, and we’ve discussed the obvious consequences. Lenders are hindered because
they cannot readily assess the creditworthiness of these potential customers, and consumers
can be hindered if they have less or no access to responsible credit, which means less or
no access to the opportunities that such credit can create. Having pointed out these undesirable
facts, we’re now working to understand what can be done to change them for the better.
One line of inquiry is to explore how those who start out as credit invisible could become
more visible. For all the real challenges consumers face, millions of them every year
do establish credit records. In particular, few Americans have any credit record before
they turn 18, yet by age 29, about 90% of Americans are able to become credit visible.
So, the interesting question is: How do people make this transition?
A new report we issued yesterday examines the transition to credit visibility, when
and how consumers first establish a credit record. Our study found the way consumers
establish credit history can differ greatly based on their economic background. People
in lower-income areas are more likely than people in higher-income areas to become credit
visible due to negative records, such as a debt in collection. Consumers in higher-income
areas are more likely to establish credit history by using a credit card or relying
on somebody else. Credit cards are the most common way that
consumers establish their credit, with roughly 38% of consumers becoming credit visible based
on a credit card, yet our study found this was more likely to be true of consumers in
higher-income neighborhoods. Forty-four percent of them established a credit history with
a credit card versus 34% of consumers in lower-income areas.
We also found that almost 25% of consumers become credit visible by relying on credit
already established by somebody else, such as a family member. About 15% opened a credit
account with a co-borrower, and another 10% became an authorized user on someone else’s
credit card. Again, we see differences based on economic background. About 30% of consumers
in higher-income neighborhoods turned first to co-borrowers or authorized users, but only
15% of consumers in lower-income neighborhoods did so.
A third way to become credit visible raises graver concerns. We found that 27% of consumers
in lower-income neighborhoods first establish a credit record not through their own efforts
to seek credit, but instead, when various items, such as debt collection accounts or
public records, begin to populate their credit reports. This rate is 240% higher for them
than it is for consumers in higher-income neighborhoods, and almost all of these credit
records — we estimate 90% — reflect uniformly negative information about the person’s creditworthiness.
This tells us that consumers in lower-income neighborhoods often become credit visible
in ways that leave their credit record shadowed by unfavorable items right from the start.
Another interesting finding is that student loans are becoming a more common means for
consumers to establish a credit record. Ten years ago, about forty percent of consumers
who became credit visible before age twenty-five did so with a credit card, whereas only ten
percent did so as a result of a student loan. Today, that gap has narrowed considerably.
Twenty-six percent of younger consumers who became credit visible in 2016 did so as the
result of a student loan, and thirty-three percent did so based on a credit card. This
reflects both the increasing importance of student loans in the lives of younger consumers
and some reduction in their use of credit cards.
This study on credit visibility is helping us learn more about how credit can be expanded
to include more consumers, so they can better participate in the mainstream financial system.
Yet another way to achieve this outcome and another potential route to establish a credit
record is through so-called alternative data. This includes payments made on items such
as rent or cell phone bills, which may be used to as — assess the creditworthiness
of consumers that would otherwise remain credit invisible. We issued a request for information
back in February to learn more about how this non-traditional information is used or can
be used. The comment period has now closed, and we’re digesting what people have told
us, and we will have more to say before long. We’re also studying the availability of credit
to small businesses, which are so vital to the nation’s economy and our communities.
The primary basis for our interest is the Dodd-Frank Act. In creating the Consumer Bureau,
Congress directed us to write a regulation about the collection of information from financial
institutions that lend to small businesses. This data is intended to benefit small businesses,
creditors, policymakers, and regulators so they can better understand the credit needs
of small businesses and the opportunities to meet those needs.
There are other reasons why a deeper understanding of small business financing may be quite important
to progress in our economy and our quality of life. One 2013 study found that counties
with higher percentages of their workforce employed by small businesses showed higher
local income, higher employment rates, and lower poverty rates. Small businesses have
created an estimated 2 out of every 3 jobs since 1993, and they provide work for almost
half of all private-sector employees, yet we remain aware of large gaps in the public’s
understanding of how well the financing and credit needs of American’s entrepreneurs are
being served. Last month, we issued a request for information
to get feedback on how to carry out this task in a careful, thoughtful, and cost-effective
way. We’re facing a number of difficult questions as we assess how to proceed in this new area.
In particular, we’re looking at how a small business should be defined for these purposes
and what types of information lenders consider when financing them. We’re looking into where
small businesses currently seek credit and what credit is available to them. We’re also
considering the privacy implications that could arise in publishing this information.
The importance of this undertaking could not be clearer. In a whitepaper, we documented
the importance of small businesses to our economy and the critical role that financing
plays in enabling these businesses, especially minority- and women-owned businesses, to thrive.
At a recent field hearing in Los Angeles, we heard compelling repornts — ports that
in many communities of color and immigrant communities, the most frequent paths to wealth
creation are to start a small business and to develop equity in one’s home. Obviously,
if there are roadblocks that impede lending to such communities, then economic vitality
can be severely diminished. So, the same mechanisms that have been used
for years to diagnose community development needs in the mortgage market and impediments
to mortgage lending would now be applied, in some fashion, to small business lending,
as well. Our job is to figure out how best to accomplish that, recognizing the clear
differences between these two lending markets. The Bureau is also mindful of the potential
complexity and cost of small business data collection and reporting. We will explore
ways to fulfill this duty in a balanced manner, seeking to provide timely data with the highest
potential to meet the statutory objectives, while minimizing the burdens for both the
industry and the Bureau. We welcome input from a wide range of stakeholders, including
lenders and business trade associations. Several of these groups have asked for more time to
respond to the request for information. We’ve also been hearing from Congressional officials
who want to see more progress made on this rulemaking.
We’ve had a steady plan, from the outset, to take up this task right after we finished
the HMDA rules, and we are now moving forward. We do recognize the importance of quality
responses from the public, so the Bureau is granting the request for a 60-day extension
to the comment period. The final issue I’ll discuss today concerns
our efforts to write new, common-sense rules of the road for the debt collection market.
We’ve already begun taking steps to develop new rules for this industry to protect both
consumers and honest businesses. Debt collection is still the single largest source of complaints
to the federal government in any area of consumer finance. People cannot vote with their feet
if they experience problems, because they have no choice over who collects their debts.
This makes them less able to protect themselves from harmful practices, which is a classic
example of what economists would term a market failure. For these and other reasons discussed
below, we’re moving forward with the rulemaking process here.
In addition to those concerns, there are two other reasons why it would be appropriate
to adopt new rules to govern the debt collection industry. Both tend to show how regulation
can improve and benefit the marketplace by bringing more order, more clarity, and more
transparency to its everyday functions. In the first place, this market is one where
the primary governing law is a statute enacted way back in 1977. That law, the Fair Debt
Collection Practices Act, contains broad prohibitions on practices that are, quote, unfair or unconscionable
or acts whose natural consequence is, quote, to harass, oppress, or abuse. Yet, until the
Consumer Bureau was created, no agency had the authority to define more specifically
the scope of these broad prohibitions. As a result, this area of the law has been
— become outmoded over the past 40 years. The courts have been forced to try to make
sense of the statutory provisions and apply them to a very different world, leading to
a patchwork of inconsistent rulings that breeds disarray and uncertainty. Conflicting rulings
from different courts make it difficult for compliance attorneys to give firm guidance
to companies that operate in this realm. So, writing new regulations in this area makes
a great deal of sense. Both industry and consumer groups are pressing for updated interpretations
of the law, because so much is happening in this marketplace that the law cannot easily
keep pace with developments. The 1977 statute mentions telegrams and was written with landline
phones and postal mail very much in mind. By contrast, many of today’s consumers are
adept in using the internet, email, and social media, yet debt collectors are uncertain how
to address many issues involving these new technologies. Cell phones were unknown at
the time the law was drafted, and the debt buyer industry barely even existed.
Although the courts can try to use their tools as statutory construction to retrofit the
statutory language in light of these fast changes, the better course is likely to be
to reinterpret it based on a frank and thoughtful assessment through a rulemaking process. That
process can be informed by industry officials, consumer advocates, and market experts about
how to apply the statute to these new and unforeseen circumstances.
Last summer, we outlined proposals under consideration that would apply to third-party debt collectors
and debt buyers. We also announced our intention to move forward with separate rules for first-party
creditors who collect on their own accounts. The proposals we outlined focused on three
primary issues. First, make sure that collectors are contacting the right consumers for the
right amount. Second, make sure that consumers clearly understand the debt collection process
and their rights. Third, make sure that consumers are treated with dignity and respect, particularly
in their communications with collectors. As we evaluated the feedback we received on
the proposals under consideration, one thing became clear: Writing rules to make sure debt
collectors have the right information about their debts is best handled by considering
solutions from first-party creditors and third-party collectors at the same time. First-party creditors,
like banks and other lenders, create the information about the debt, and then they use it to collect
the debt themselves, or they may provide it to companies that collect the debt on their
behalf or buy the debt outright. Either way, those actually collecting on the debts need
to have the correct and accurate information. All of these parties must work together to
ensure they’re collecting the right amount of debt from the right consumer.
But breaking the different aspects of the informational issues into pieces in two distinct
rules was shaping up to be troublesome in various ways, so we’ve now decided to consolidate
all the issues of right consumer, right amount, into the separate rule we will be developing
for first-party creditors, which will now cover these intertwined issues for third-party
collectors and debt buyers, as well. That way, we can address this entire set of considerations
market-wide. In the meantime, we will be able to move forward
more quickly with the proposed rule focused on the remaining issues. These issues, again,
are: information third-party collectors must disclose to people about the debt collection
process and their rights as consumers, and ensuring that third-party collectors treat
people with the dignity and respect they deserve. Once we proceed with the proposed rule on
these issues, we will return to the subject of collecting the right amount from the right
consumer, which is a key objective, regardless of who’s collecting the debt, and we will
take care to get it right. The issues I’ve just discussed span a considerable
spectrum, but at their core, they have much in common. They touch on fairness and protection
for all consumers, especially those who are underserved or having financial problems.
Our mission is to make sure that markets are fair and transparent, that people are treated
with dignity and respect, and that every consumer counts. We look forward to hearing from you
today in order to better inform our approach to our work. As always, we’re giving a great
deal of thought to these and other issues, and we welcome your suggestions. Thank you.
Thank you, Director Cordray. Today’s meeting focuses on some very important topics, such
as credit visibility — And let me back up for a second to say, welcome, everybody in
the audience, the audience at large, online and in — before us today, in person. Our
meeting today is going to cover topics such as credit vi — visibility, as the director
mentioned, the costs and risks associated with deferred-interest products, and the small
business lending market, among other trends and themes in the consumer financial marketplace.
The CAB has long followed the Bureau’s work on credit invisibility, and as we now transition
into examining some of the data explored about consumers who are new to credit, we look forward
to learning about consumer con — experiences and what we can do to empower and assist consumers.
We also look forward to discussing products, like deferred-interest products, which, for
many consumers new to credit, can be challenging. To start this morning’s sessions, we will
hear from Ken Brevoort, Section Chief in the Bureau’s Office of Research, on a report that
was released just yesterday. Ken? So, good morning, everyone. Um, as you just
heard, I’ll be talking about our report, which came off — uh, or was published just yesterday.
Uh, it was joint work with my colleague here at the CFPB, Michelle Kambara. Um, and I should
have slides that will hopefully be appearing momentarily. Ah, good. Uh, I once was late
getting slides to, uh, a conference, and I promised the organizer that if I didn’t actually
get them in on time, I would just do the entire talk through interpretive dance. Um, and believe me, no — nobody wanted that. Um, so, the — the work I’m going to be talking
about today actually starts with — Okay. It — it starts with a — a data point that
we issued about 2 years ago, in May of 2015. Uh, it was called credit invisibles, and it
was basically our attempt to come up with a better measure of, uh, the number of people
who lacked a credit report at one of the three nationwide credit reporting agencies and a
better understanding of exactly who these people are, in terms of what their characteristics
are, to get a better sense of, sort of, what efforts may be most fruitful in trying to
get these people access to — to credit, because if you do not have a credit record at one
of the large credit reporting agencies, ultimately, you can’t have credit scores generated for
you, generally, um, and it’s going to — it’s going to make, uh, obtaining credit all that
much more difficult. Now, in that report, one of the things that
we did was, we came up with a broad estimate of the — the number of people who are credit
invisible. Um, and what we want to do in this, uh, paper is take another step and look at,
sort of, how people were able to make the transition from being credit invisible to
having a credit record. Uh, in the data that we came out with about
2 years ago, one of the results we found was that if you looked at people who are 25 to
29, 9% of them, uh, were credit invisible, meaning that they did not have a credit record
at the credit reporting agency that we looked at. Now, if you turn that number around, it
means that 91% of people who were 25 to 29 at the time we did that study had managed
to get a credit record. Now, no one starts life with a credit record,
and very, very few people have a credit record before they turn 18. So, what this means is
that in this 10-year period between, say, when they turned 18 and when they hit their
late 20s, about 90% of the people are able to make this transition from not having a
credit record to having one. And we know that there’s been a lot of policy
interest in the people who are credit invisible, because we all know that there are — there
is difficulty there. If you do not have a credit record, you have a harder time obtaining
credit. And so, what we wanted to understand is, why
it is that so many people seem to be able to make this transition, while others have
had difficulty with it, and we want to understand the types of consumers who are making this
transition and the means that they’re using to make this transition. So, what types of
credit products or other information, um, are they acquiring their credit history from?
And so, that’s going to be the — the — the topic of the — the research I’m going to
talk about today. Now, we’ll start with the — the data that
we’re using for this talk. The data come from what — uh, the same data source that we used
in our earlier work, and that is our Consumer Credit Panel. Um, this is a large, nationally
representative sample of de-identified credit records that we obtained from one of the three
nationwide credit reporting agencies. Um, the — the records are de-identified,
and what I mean by that is that they do not contain any information about name, address,
Social Security number — anything that would directly identify the consumers in this data.
So, we don’t know the — who the consumers are, but we know the contents of their credit
records. So, we know if they had credit cards, when they were opened, what their balances
were, and things like this. And we’ve been using this — these data for a number of things,
um, to inform, sort of, our general policy and market monitoring missions, um, and part
of it is to better understand what the characteristics of credit reports look like for these consumers
who are making these transitions. So, what we’re going to do is, we’re going
to use the archives that we have from December 2006 to December ’16 — uh, two — sorry,
December 2016. Um, in the credit records that we have, we do not have date of birth. That’s,
sort of — We — we didn’t get that because we thought it was potentially, uh — it — it
— We — we didn’t like the idea of having date of birth because it was potentially im
— impeding the anonymity of the data. But we did get year of birth, so this gives us
a chance to look at different ages of consumers. So, one of the things we looked at in our
early credit re — credit invisibles report was how the likelihood of being credit — or
the incidence of being credit invisible differed by different age bands, right? And credit
invisibility was much more common amongst the young, much more common amongst the old,
uh, and people in the — the ages in between, it was much lower. So, what we’re going to
do is, we’re going to take the credit records from the December of each year, and then we’re
going to look at, sort of, how the transition is played out across different age groups,
um, based on what the age of the consumer was at the end of that year.
Um, and we’re going to look at transitions in, specifically, I think, 11 different age
groups, starting with consumers who are under 25, 25 to 29, 30 to 34, up by 5-year age bands,
through 65 to 69. Um, and the way we’re doing this is, in each of the December archives,
for each of those age groups — We take — For example, in the 2006 archive, we take everybody
who turned 24, uh, in 2006. We then look at their credit record, and then we look at how
they first became, uh — or how they first moved out of credit invisibility. For some
reason, I don’t like the word credit visible, but, um, I — I probably should start using
that more, because it’s going to make this talk a lot easier. Um, and we did the same thing for — for older
ages. So, we looked for — We took everyone in 2006 who was 29, and then looked at those
people who established their credit record when they were 25 to 29. So, a lot of the
analysis we’re going to be doing is also going to be doing cohort analysis. So, when we look
at 2006, and we talk about people who were under 25, or who established their credit
record before they 25, using the 2006 archive, we’re really talking about those consumers
who were born in 1982. When we use that same age group for the 2007 archive, we’re going
to be talking about consumers who were born in two — in 1983, and so on and so forth.
So, we’re going to be able to also look at how these transitions out of credit invisibility
were playing out differently for pop — different populations of consumers, right? So, as we
moved further and further into the Millennial population, how did these transitions play
out? Or, for the older consumers, we’re looking at a — a much, uh, different age range.
Um, th — this table here shows the summary statistics for the data that we’re — we’re
looking at. Overall, we have records, uh, for about a little bit over a million people
who appear to have made this transition from being credit invisible to having a credit
record over the time period of — of our sample. Um, the table — or the column at the — the
right-most side shows the birth year cohort ranges, right? So, for the under-25 population,
we’re going to be looking at people who were born between 1982 and 1992. Uh, in the older
ages, we’re going to be looking at slightly different, uh, birth-year cohort ranges.
Now, one of the things that jumps out at you are — are —
Would — would you just take a moment, Ken, and explain to people that this data is deidentified
and anonymized, how — Mm-hmm.
— how it is? Just take a minute for that? Thank you.
Yeah. So, the — the data are deidentified. We do not have name, address, Social Security
number. We have nothing that would identify the individuals. Um, we don’t know where they
live in terms of their address. We do have a Census tract that we’ll — we’ll use a little
bit to understand, sort of, uh, what — what the neighborhood that they were growing up
in, uh, looked like or what the neighborhood they were living in looks like, uh, but there’s
nothing that would actually directly identify these consumers in the data.
Now, if — if you look at the — the data in these tables, one of the things that — that
jumps out at out, I think, is that if you — the share of the population that establishes
their credit record, makes this transition, um, who are under 25, is about — I think
about 80% of — of the entire sample. Right? So, most of the people who make this transition
from being credit invisible to being credit visible seem to do so at a very young age.
Right? And that’s consistent with the results we published, um, in our earlier study, where
the — the ratio of — of credit invisibility was much, much higher amongst people who were
18 and 19 or — or younger than that, than it was at older ages.
Um, and the — the sample size actually declines pretty consistently throughout the age groups,
so the number of people who we observed making this transition over this period of time,
uh, goes down as they go higher and higher. Right? So, you generally don’t see a lot of
people who are 65 to 69, um, establishing a credit history.
Are — are you open to questions, or — or —
Yeah. — do you want them at the end?
Sure. Of those who, uh, establish credit history
at a later age cohort, would a high percentage of those be immigrants, or would — would
— Do you have a sense of what percentage of those might be immigrants?
I — I don’t think we have a sense. Uh, a — a good portion of them may very well be
immigrants. It also could be people who had a credit record at one point, and then something
went wrong and they stopped acquiring new credit, and the credit they — or the credit
items that were on their history migrated off.
These the kind of things you’re going to be digging into further, perhaps?
All right. Everyone else, if you have questions as we go, feel free to interrupt me if I’m
not being clear. Okay, so we have these credit records of people,
um, who went from being credit invisible to visible, and one of the first things we’re
going to do is, we’re going to start identifying what are — what item it was that was first
reported on their credit record. Right? Because this should have been the piece of information
that ultimately led to the creation of their credit record.
And we’re going to characterize that item, uh, according to one of six — or one of eight
different — There should be, like, little circles. All right. Sorry, the — the bullets
aren’t — aren’t printing. But anyway, one of eight different, uh, types of entry products.
Uh, people whose first credit experience or whose first item on their credit record, uh,
was an automobile lo — loan or lease, a credit card, a mortgage, a personal loan, or some
other type of loan, uh, not classified — retail loans, uh, which include department credit
score — uh, credit cards, and student loans. So, we’re going to look at those six types
of entry products, all of which are loans that the consumer has applied for, uh, and
wound up being reported, and then we’re going to look at two other pieces of information
that are for non-loan activities, and these are collection accounts that are reported
by third-party debt collectors — So, if the consumer had a cell phone, uh, that they didn’t
pay the bill on, the bill was then sent to a third-party debt collector, and that wound
up being reported, it is possible that that reporting of that third-party debt collection
was the item that triggered the creation of their credit record.
Uh, and so, those are — We have collection accounts like that, and there are other non-loan
things that are reported. Uh, in particular, there are public records — could be bankruptcy
filings, could be tax liens, uh, could be civil judgements that are reported.
There may be utility bills, uh, that are sometimes reported to the credit bureaus that could
lead to the triggering, uh, of one of these, uh, credit records. Uh, the utility bills
can actually be either bills that are being paid on time, but they are very frequently,
uh, bills that are reported once they’ve become delinquent, and there’s even some reporting
of child support and family support payments in there, as well.
And so, for each consumer who makes this transition out of credit invisibility, we identified
the product, uh, what we’re calling the entry product, or the item that was first reported,
that led to the creation of their credit record. Um, and I should point out that the way we’re
defining, uh, credit invisibility here is very narrow, and we’re doing it using the
same definition that we used in our previous study, and it is just the question of: Did
this person have a credit record or not? I mean, that’s narrow —
Can I note something here? Yes.
This is something we remark upon from time to time and — and think about and aren’t
always sure what to make of it, but if you look at the first six categories there, they’re
all loans that — Yep.
— the consumer would take out. Mm-hmm.
And, therefore, positive data about their performance in their loans would be fit into
the credit reporting system over time. Presumably, negative information would, as well, if —
Yeah. — they fail to make a payment, but a lot
of those things will then show up as collection accounts, so negative information will feed
in that way on loans. Right? The last category is kind of unique, the other
non-loans, because in those areas, uniquely, only negative data will tend to feed onto
your credit report. So, it’s kind of a one-way ratchet that has always felt, to us, somewhat
unfair. So, in terms of utility bills, child support payments, and other things, a long
history of making these payments — rent would be in this category, too, I suppose — Uh,
you get no credit for any of that, yet if you fail, likely, it will go to a debt collector
and end up getting reported, uh, onto your — That — that feels like a, um — a — a,
sort of, misalignment of the reporting system to — to many people, and it’s something that
continues to be a source of interest and concern and — and — and, uh, consideration as to
what to do about it, so. Can I ask a quick question? Uh, following
up on rent, that, uh — I would be fascinated to know if you can pull out, uh, fo — utility,
child, and — and especially rent, uh, how much of not, uh, being able to pay rent, uh,
is impacting people’s, um, invisibility or lack thereof. Uh, and that would be a very
fascinating number for me. Yeah, and I don’t think we’ve looked at that
specifically. We can. I — I think it’s a pretty small number. I mean, generally, we’ll
— we’ll see a little bit that the other non-loans category, generally, itself, is a pretty small
number. One — one question, I suppose, people might
be thinking about is, of the collection accounts reported, are you able to segment that into
collection re — accounts reported on failing on a credit card as opposed to failing on
a mortgage or failing on something else? Are you able to do that? Or will you be able to
over time, do you think? So — so, we have broad categorization. So,
for example, we could identify which of the collection accounts were medical related,
um, which tend to be telecom. Um, I think there’s a category for banks. So, I don’t
know that we necessarily could distinguish between what was a mortgage or what was a
credit card, but we can sort of see, um, what —
One of the things Ken and his colleagues run into frequently is, there might be more they’d
like to know in the data, but the data just isn’t collected that way, so one of the things
we’re trying to do over time is figure out how we might go about collecting it in that
way or figuring out how we can take the data as it exists and break it down to figure out,
uh, uh, this meaning, and, uh, that’s — that’s part — a big part of what they’re trying
to do. Ken, are you willing to take a couple more
questions? Awesome. Chi Chi, and then Jim.
We’ll just try this with the weird feedback. Um, to — to follow up on Director Cordray’s
point, I wanted to ask you: Um, in terms of the collection items, I would assume a lot
of them are actually medical, given the previous research that the Bureau has done showing
50% of collection items are medical, something, what, 17% are — are telco, and so, they — actually,
the vast majority, I would assume, are not financial accounts that have a prior, um,
account history of either positive or negative payments.
Um, and then, just to make the point we always do with respect to gas and electric utilities:
We have some concerns about paying — uh, recording full payment history for those because
of the unique status of natural monopolies that are heavily regulated.
Yeah. And I would just say, too, I think that’s a — it’s an interesting observation, Director,
that we do see. Uh, I think, by definition, these collection accounts are — are non-financial,
because this is the first visibility we’re seeing for this group of people, right? In
other words — to your point, uh, if — if it’s a financial account, you’re seeing deposit
or payments, and then eventually, some of those will end up in collections. But that
won’t create the visibility. They’ll already have had visibility through the payments.
And so, these are collection accounts that — that don’t come out of nowhere. Um, by
— by definition, there’s obligations, then, that aren’t being paid.
What that means is, there are millions of other similarly situated consumers that are
making payments, um, that — that are — that would be positive that aren’t being captured
in the — in the system, in the bureaus, and that, um, if — if we could look to those
things, we could provide visibility before it — it goes to collection, that that would
— would help people, I think, not only provide visibility. Because you get visibility here,
but it — it — it doesn’t help you, right? It’s just a negative thing on the file as
a standalone thing. And we could — we could score that, but, um, it’s — it’s very incomplete
and — and not a reliable score. Um, but what’s — what’s important is to — is
to find that — that positive data for the millions — And I — You know, I think you
talked about the fact that, uh, you know, these collection accounts are — it — it’s
the first thing for — for many low-income consumers. That means there’s millions of
low-income consumers that are making on-time payments of these types of — of payments.
And it could be medical payments. It could be utility. It could be rental. But if we
set out to find those positive payments, we could score those and provide visibility — positive
visibility that would be very helpful to consumers in — in — in terms of credit access.
Can — can I ask — The only thing I would quibble with what you
said is saying that some of these are financial transactions. I mean, the problem here is,
they’re all economic transactions, it’s just that our system has defined credit as only
applying to transactions, uh, that involve a loan, and there’s many other economic transactions
people engage in, uh, and as — as Ken’s getting to here, the credit invisibles are engaging
entirely in economic transactions that are non-credit — not — not defined as such.
That’s the flaw in our system. I don’t want to take us too far off point with this, because
I know — I know Ken’s research is — is not on this particular point today, but, uh, so.
Well, can I ask just one quick follow-up, which is, um, in terms of, maybe, future research
or if you saw anything, those who, um, their entry point is collection items, are you able
to follow their trajectory in terms of what happens to them? Do they actually get credit
based on this, you know, bad — You know, because we’ve often heard a bad score is better
than no score, um, and I’m highly doubtful, so it would be interesting to see the trajectory
of these consumers. You know, that’s actually where the — So,
the next study that we do along the lines of this is going to go to exactly that. Um,
I think I mentioned at a — a previous CAB meeting that I — I’d done some research with
some colleagues at the Federal Reserve Board, before I came to the CFPB, that actually looked
at some of these issues. Particularly, we were looking at how the, um — the origins
of cr — how credit score differences across races and ethnicities differed in how they
emerged. Um, and it was really fascinating research,
because what you saw was that, you know, most po — most of the different populations would
start around the same level, and then all of their scores would go down substantially,
and, sort of, like, immediately, bad things would happen, or they would not — young people
would not pay their bills. Their scores would go down.
And what you saw for the differences across the minorities, uh, particularly the African
Americans and non-Hispanic whites, was that a lot of the difference really, uh, came in
that early period. Right? African Americans tended to have more negative items appear
on their credit report very early in their life. It led to a separation, and that separation
was maintained thereout. Um, and I think that had interesting policy implications about
how you might reach out to the African American community, sort of help them, from early in
their lives, to sort of help them from going on this track.
And we actually — It was fascinating research, and I presented it at a few different conferences
and — and universities, and we never wrote it down, um, because we were too busy. So,
it’s something I want to go back and revisit, um, at — at least, sort of, as a follow-up
to — to this study here. Because, uh, right now, we’re looking at, sort of, how people
make the transition, uh, into having a credit record. The next step will be: All right,
once you’ve established a credit record, either because it was a collection account or an
automobile loan or what have you, what happens? Right? How do you actually — How does that
play out? Um, because one of the things we’re not going
to look at in this study is, we’re not going to really categorize, when you established
a credit history, did you establish a good history or a bad history quite yet. Right?
And the reasons is, there’s — there’s a lot of shades of gray there, right? An auto loan
may be great, or it may be — say good things about you once it’s reported, but 3 months
later, it turns out to be negative, right? And so, they’re — they’re a little bit hard
to categorize in terms of just understanding that point of transition. Um, so, we’ll — we’ll
do that in a — in a subsequent, uh, part of this — or as a subsequent study.
The — the point of wistfulness here is that it would be great to come back and see what
the CFPB will know, say, in the year 2050. It would be great if we could know it all
now, which — — of course, we don’t. But Ken and his folks
will see to it that the — God willing, the later Consumer Bureau will be much more, uh,
knowledgeable and certain of itself on some of these issues.
One more quick question. Josh? Yes, just — Uh, just very quickly on this
topic. Uh, it’s — And this is really interesting research, and it’s good to see that you’re
going to follow on, because many of these types of, uh — of accounts, even if they
start positive, there’s — uh, you know, there’s always a — a, you know, a risk of disparate
impact in terms of high-cost credit, and just one thing to point to in that is with student
loans. Um, I think that studies said that 25% of
initial collections — uh, or, sorry, of, um, initial visi — credit visibility is due
to student loans, uh, and there’s a real risk there because, uh, disproportionately, people
of color, um, are steered into, uh, the type of student loans that, uh, are accompanying
for-profit schools and trade schools, where there really isn’t, uh, the — You know, the
education isn’t what is advertised, and people end up with high, uh, debt, uh, and in a — a
degree that often doesn’t help them, uh, in getting employment, uh, to pay off that debt.
Uh, so the — there’s so many layers of this, but it’s — it’s — it’s critical, I think,
as — as you’re looking at this, to — to follow the types of debt, um, and — and how
that impacts people’s, uh, credit, uh, going forward.
To follow on that very briefly: For any form of credit where there are loss mitigation
measures that are possible, and somebody has sought those loss mitigation eff — eff — uh,
efforts and qualified for loss mitigation and yet was not ma — given access — Obviously,
I mean, raises other questions about how that fits into damage to credit.
When the student loan work that we do — We have, for examples, people with disabilities,
well documented, sent the records repeatedly to the servicer, um, and were improperly denied
until we got involved. You shouldn’t have to have a lawyer get involved for something
that’s just, really, obviously, somebody’s entitled to under the rules. I know that’s
going to be, maybe, hard to account for, but it would be interesting to — to maybe try
to figure out what percentage, however you do it, in that brilliant, statistical, but
logical fashion, what is a rational way of trying to, you know, discount for or account
for in some fashion that kind of bad behavior. One other thought, also, is on identity theft
for young — younger folks. Um, um — And I’m — and that — maybe that’s a very tiny
percentage of — that you’re going to find as you dig in deeper, but I am — I am interested
in that, and that seems to happen at varying levels, in some communities more than others,
so. Thank you. All right. So, I’ll — I’ll continue. Um,
so, we have entry products, which are the — the items that are reported to the credit
bureaus that lead to the creation, uh, of these very narrowly defined credit records.
So, the following shows the distribution of entry products by age group. So, basically,
what this table shows is, for each different age group, the percentage of people whose
entry product was each of these eight different types, uh, of credit product. We’re actually
only showing six of them here, because if I’d — I’d shown eight, it wouldn’t have fit
on the slide. Um, so we’ve left off mortgages and personal or other loans, uh, both of which
are — are very small in terms of percentages. But what, sort of, draws the eye on — on
this table, I — I think is, first, that credit cards are the dominant means by which consumers
seem to establish or acquire credit histories. Right? Across all the different age groups,
uh, credit cards are the largest entry product by share of any of the other products.
The second most common overall are student loans, um, but that is almost entirely driven
by people who are under 25. So, consumers who transition out of credit invisibility
before they turn 25, almost 20% of them do so using a student loan. Uh, for age groups
above that, it — it’s a much, much smaller percentage. Right? Amongst the people who
are 60 and older, um, it’s below a percent. Uh, and the third most common use — or — or
the third most common product is, uh, retail. Uh, these include department credit scores,
uh, and they tend to be a little bit more common amongst the older population.
Now, also — Mm-hmm? Ken, does — does retail include rent-to-own,
which is one, uh, more common way of getting credit in low-income communities?
It should. Okay, so they do report.
Yeah. Well, um, I — I don’t know how often they report, but if it’s reported, it should
have been put in the retail group. Okay. So, it could — it could be that they
only report when there’s negative information. Yeah.
Okay. Thank you. And so, the other thing that — that, sort
of, draws the eye here is that about 15% of people overall have their credit re — report
created as the result of either a collection, uh, or one of these other non-loan categories.
So, the — this is a population who starts their credit report with one of these non-loan,
uh, items, and even though we’ve generally tried to — or I’ve generally tried to avoid
categorizing the start of a credit history as either positive or negative, because the
— particularly with the loans, it’s a fair — fairly nuanced, uh, determination, but
for these non-loan items, 90% of them are items that, when they’re reported, always
convey information that would be considered negative. Right? So, they’re debt collections.
They’re, uh, tax liens. Uh, so — Is — is non-loan the right adjective to use?
Wouldn’t a lot of the collections stem from loans?
It — it — So, uh, the — the share of collections that
come from loans, I think, is relatively small. Is that right?
Um, and — Well, I should say, the share of collections overall that the — the accounts
are being collected by third-party debt collectors, a lot of them are loans —
Mm-hmm. — I don’t think very many of them are reported
to the credit bureaus. Okay.
And I think the — a lot of the reason for that is that if you have a credit card and
it goes delinquent, that’s being reported by the credit card company, and if it was
then reported by a third-party debt collector, you would essentially penalize the same consumer
twice for the same delinquent. So, if it’s first reported by a collector,
it’s likely to be a non-loan . That’s right. Yeah. And so, I think the — the
reporting to the bureaus of — of third-party debts that are — are loan related is — is
relatively small. Two quick questions that I assume are follow-ons
to this. First Kathleen, then Joann. I think I just wanted some clarification.
If this is people’s first encounter with a credit report, wouldn’t it be the case that
if it was a loan, at least from a financial institution or a credit card, that would get
reported as the first encounter? The debt collection would be later. So, that may be
why. Yeah. Okay. Yeah, that — that’s very true.
I — I will say, a lot of third-barty — party debt collectors have stopped reporting. The
requirements, because of accuracy and having policies and procedures, it’s just too onerous,
uh, the — the risk of error is too high, so a lot of them are just stopping. Uh, it’s
just better to — not to do it. Just a clarification: You said that 90% of
collections items are negative. What kind of collection item could be positive? Just
— Sorry, it — it was 90% of the non-loans,
which includes the collection items and the other category.
Oh, okay. Right. So, you’re right. All — all the collection
items we were considering as — as always negative when they’re reported. Yes, that’s — Yeah.
Wasn’t the other about non-payment of — Not always.
So, child support or — So, it — it could be like —
— other issues? Yes, the — the child support payments would
have been negative, um, but things like utility payments sometimes are reported, even though
they’re not delinquent. Um, and there were other types of accounts, rental payments that
maybe are being reported and the person’s actually current on sometimes, but delinquent
on others. So, since they’re not uniformly negative, they’re in this 10%.
Now, a lot of that 10% may also be items that have gone negative, so a utility payment that
for one consumer they didn’t pay and it was reported as being derogatory, and so the 90%
is sort of a lower band on — on what that might be. Uh, but it’s — Disproportionally
these non-loans are — are negative when they’re reported.
All right. So, in thinking about the — the importance of credit cards in establishing
credit histories, um, one of the ways that a credit card could be established is the
use of secured credit cards, where the consumer puts down a deposit before the car — account
is opened, and that deposit could be used to cover losses should the consumer not repay
the debt. So, we were interested in how many of these
credit card, um, accounts that were basically establishing someone’s credit history might
have been the result of the use of — of secured credit cards. So, we took all of the credit
card entry products that we observed the data — Um, the — the column there, under credit
cards, just reproduces the column from the previous table, so the 35.6% of people under
25 established their credit history from a credit card.
Of those, 34.7%, um, did — did so using what appears to be an unsecured card, and about
0.9%, or less than 1%, used a credit score — or used — I’m sorry, used a secured credit
card. So, about 2.5% of that age group, um, made the transition — uh, uh, 2.5% of the
population that made the transition out of credit invisibility using a credit card did
so using a secured credit card. And what you can see is that the use of secured
credit cards as an entry product, uh, appears to be relatively low. Um, it’s — it’s much
more common amongst people in middle age, uh, than it is older or younger consumers.
Um, so it also seems that, uh, most of the use of credit cards to establish credit history
doesn’t seem to be relying on the use of these secured cards.
I wonder if this — this group, between, like, 25 and 50, the middle-aged people, like — Well,
I’d like to make middle age a little older just for self-interest purposes, um, but — — uh, um, I’m wondering if these are people
who are going into secured credit cards because of some financial trouble — right? — something
that didn’t get onto a credit report but that prevented them from getting an unsecured card?
Yep. I think — I wonder if that’s what it’s picking
up? Although you would expect they would have had some — something on their credit report,
in this age group, like a bankruptcy, at least, or something, and they wouldn’t have — right?
— to be in this. So, it sort of cur — I’d li — I’m interested in what’s up with those
people. Yeah, we — we don’t really have a — Sorry.
We — we don’t really have anything in the data that would tell us, sort of, why they
chose a secured card. Um, it — it’s possible that some of these consumers had a previous
bankruptcy, and they then became credit invisible because all the information on their credit
report migrated off, and then maybe they didn’t even realize that it was all gone. Then, you
go out, and you know that for the past several years, you’ve been unable to get a credit
card, so when you try to get one this time, you go and take a secured route. Uh, but we
— we have no way of really verifying if — if that’s true or not directly from these data.
So, one of the results that we observed in our earlier data point, also, was that there
were significant differences in the incidence of being credit invisible across different
neighborhood income levels. Right? Credit bureau records themselves do not contain any
information about the intel of — of borrowers, but what we can do is, because we know the
Census tract associated with each of the credit records in our data set, we can categorize
the neighborhood — the income level of the neighborhood in which the borrower resides,
and use that as a method of understanding, sort of, how the transition out of credit
invisibility varies between lower- or — or moderate- or upper-income consumers.
Uh, and so, we’re going to categorize each tract based upon a — a concept known as relative
income. Uh, for people who are familiar with the Community Reinvestment Act or the Affordable
Housing and also the GSEs — This should be a familiar concept. It’s something that’s
been used, uh, I — I think, for quite a long while, and it’s basically — Relative income
is, you take the median family income in a Census tract, and you compare it to the median
family income of the surrounding area, the surrounding area being for urban tracts, the
metropolitan statistical area, or whatever they call those now, uh, and for rural tracts,
it’s the non-metropolitan portion of the state. And you take that ratio, and that tells you
something about the income level, uh, of the community in a way that’s — allows you to
adjust for the fact that the same dollar amount of income may mean different things in different
parts of the country. And so, there are four, uh, income levels
that are created from this: low, which are people whose relative income is below 50%;
moderate, 50- to 79%; middle, 80- to 119%; and then the upper-income communities, which
would be 120%, uh, relative income or higher. And so, this tra — uh, this table shows the
distribution of the observations in our data set across these different, uh, income groups.
Um, overall, you generally see that the share, uh, of people in — in low, moderate communities
tends to be relatively low. Um, this is not surprising, because there aren’t as many people
who live in low — low- to moderate-income neighborhoods as there are overall.
So, as a — a way of comparing what we see in our sample versus the — the population
that’s, sort of, available, the column all the way to the right, the percent of invisibles
— This is a number that we produced as part of our earlier study, which shows the percentage
of the population of people who are credit invisible who reside in — in low-income neighborhoods.
Right? So, if you looked at the entire population of people who are credit invisible, 14.3%
of them live in low-income neighborhoods. In our sample of people who transitioned out
of credit invisibility, about 7.5% of them appear to be in low — low-income neighborhoods.
And so, what you can see from that comparison is that in low-income neighborhoods, the share
who appear to be making the transition is consistently lower than the share who are
out there — or the — the — the entire portion of the population. Right? So, low-income com
— communities, they’re 7.5% of transitioners, 14.3% of the population that could transition.
Moderate-income communities, uh, 24% of the transitioners but 32%, uh, of the available
population. And in upper-income communities, you see that
the — the percentages are much larger, right? The consumers who are credit invisible, only
10% of them live in upper-income communities, but in our data, it looks like 25 — they
account for 25% of the people who make the transition, uh, out of credit invisibility.
So, this is sort of consistent with the results, um, that we found in an earlier data point,
where consumers in upper-income neighborhoods seem to be able to make this transition more
readily than people in — in lower-income communities.
Uh, and consistent with that, also, is that if you look at the age of, uh — of which
this transition was made, there’s not a lot of differences, but it is the case that consumers
in lower-income communities tended to transition out of credit invisibility a little bit later
in life, uh, than did people, uh, in higher-income communities. And if you look at the share
of people who actually then become visible by the time they were 25, you’re now starting
to talk about a difference of about, maybe, 8% of the population.
Now, if you look at the ways in which these, uh, consumers in these different communities
made the transition out of credit invisibility, uh, acro — we — we get the graphs, uh, shown
here. Once again, if you look at credit cards across all thr — all four different income
levels, credit cards are the dominant means of transitioning out of credit invisibility.
Uh, they’re more commonly used than any of the, uh, other products in all four, uh, income
levels. In terms of student loans, student loans are
much less common, uh, in low-income communities. About 12% of consumers or 13% of consumers
use the student loan to transition out of credit invisibility, compared to about almost
18% in upper-income communities. But I — I think the real difference here
is in the collection and no — other items, these non-loan categories. Almost 27% of consumers
in low-income communities had their credit record created as a result of one of these
non-loan items being reported — right? — these non-loan items which, I said earlier, are
almost always negative when they’re reported. In upper-income communities, the number’s
a whole lot smaller. It’s about 8%. Um, so what we’re seeing is that of consumers
who are, sort of, making this transition in lower-income communities, you’re less likely
to make the transition, and when you do, you’re more likely to make the transition as a result
of negative information. Is there — Uh, this may not be where you’re
going with this research, or maybe you’re not going there at this point in the research,
uh, stage, but is there a how-to takeaway from any of this? Does this tell us that for
people who are having trouble making the transition to credit visibility, they or, perhaps, we
as policymakers or perhaps financial institutions should be trying to make more efforts to get
them credit cards, uh, because it is such a natural way to, sort of, make this transition?
Should there be more aggressive offering of secured credit cards? Uh, is — is there any
sort of takeaway here as to what — yet as to what we might do to try to address the
problem of the invisibles? Yeah, this is jumping a little bit ahead,
but I — I would say one of the take-offs, for me, is that we see a lot of people making
this transition using credit cards that they take out by themselves. And I don’t know that
I have a really good feel for what it is — what pieces of information lenders are using to
decide, if two people come into my shop, neither of whom has a credit record, why is it that
I’m giving a credit card to some but not others? And so, there are other items of information
that I don’t know that I have a really good sense for what those are. And it could be
— You know, it could be that they’re checking income, or it could be that the banks that
are offering credit cards are using deposit accounts, right? So, if you have a customer
who comes in with no credit record, but they have a banking account or a — a checking
account that they’ve maintained with the bank for some time, they’re using that, and that,
therefore, some of the differences that we observe across low- to moderate-income communities
may be a reflection of the fact that consumers in these neighborhoods tend to be more unbanked
in terms of deposit services. And what this says is that one of the ways
of, sort of, dealing or — or — or leaving the problem of credit invisibility may not
necessarily be, you know, only to rely on alternative data, but it could also be trying
to address the unbanked problems in these communities — right? — making sure that
these consumers have access to deposit services that then lead them to establish these relationships
with financial institutions that they can — then can use to transition into credit
visibility. Um, uh, you’re not to these slides, yet, but,
uh, your research also seems to suggest that maybe we should be trying to consider, uh,
consumer groups or community groups, uh, financial mentor programs for people. Maybe we could
get people hooked up with someone who would be willing to be the co-borrower of the user
on the authorized account — Mm-hmm.
— if they had enough of a relationship to feel comfortable doing that. Maybe more aggressive
efforts should be made to do that. That — that’s what seems to be happening, sort of, readily
and easily in the upper-income areas, uh, higher-income areas, but not so much smaller-income
areas, perhaps just because they lack anybody to — to be available to help them. Uh, and
that — that may be a tough thing to do. The other thing I worry — wonder about is,
uh, the other issue, for one of the other studies, the retail cards that we’re going
to get to a minute. Uh, if a lot of people are going in and getting retail cards as a
way to establish credit, and if some of those products are trickier, then it’s yet another
reason for us to be concerned about trying to make sure those are true zero-interest
products that might be clearer to people, because that’s — that’s going to lead some
of them, uh, in — into a bad area. Got a few follow-up questions. Uh, let me
start with, um, Neil, Paulina — Neil, then Paulina. I see you, Chi Chi.
So, I wonder, uh, in terms of the products that you’re looking at to look, uh, into the
credit, uh, is — what — is payday loans on your — or small dollar on your radar screen?
So, generally, no. I mean, most payday loans are not reported directly to the Bureau.
Right. Some — some will be indirectly reported by
third-party debt collectors as they go into default, uh, but, generally, no.
So — so — so back to the director’s point about entry-level products, and so I wonder
if there’s an opportunity here to either get the payday lenders to —
Mm-hmm. — report or, uh, thinking, as you’re doing
rulemaking on small dollar, uh, positioning the rules to encourage banks or other, you
know, mainstream financial institutions to actually get more involved there.
Mm-hmm. Um, thank you for this research. It’s extremely
important. Um, one of the, uh, questions I have: I don’t remember if you said whether
the collection and the other category here is actually broken down in the research in
terms of, um, whether you know whether it’s medical or — or rent, um, and then I have
a follow-up to that. Because if — or maybe I can just say it now. Because if it is medical
or negative rent or utility payments — then it seems like it’s more of an income problem,
um, or an in — income challenge for families, because if that’s the first — If — if it
was a credit card as a first point of entry, we would see it here, but if the first point
of entry is a collection account or an other, than it seems like an income problem.
And so, then, you get into the cycle where you’re not able to qualify for that credit
card, um, and then you’re stuck in this cycle of, you know, bad credit, um, and not able
to get back into the positive. So, there is both an income issue, and then there’s the
financial mentorship issue: How do you get yourself out of that cycle?
But until you — until you deal with the income issue, it’s — it’s constantly — you’re constantly
in that cycle, which is why, I think, um, there’s a connection between all the work
that the Bureau is doing — um, going back to the small business point, um, that the
director made at the very beginning, about how small businesses are an economic engine.
And so, if, um — if the lending is not happening there, and small businesses in low-income
areas are not, um, having that access to financing, then there’s also trajectory that affects,
um, income, uh, and — and the economy of those counties. And so, I just wanted to make
that — make that connection. Yeah, thanks. And — and we actually don’t
talk in the paper a lot about the types of collections that were here, but we did an
analysis. And so, the dominant form of collections across all the different income groups was
— was medical. Um, so, it was more than 50% of people in low-income communities and more
than 50% of people in upper-income com — communities who made the transition via a collection account.
And I think we would agree with the other things you said. The only thing I would say
is, with medical debt, it’s not so clear that that’s an income problem, because what we
found is, a lot of medical debt is fairly random. Uh, it — it is — it is a, uh — it
is a very questionable, um, uh, credit reporting item. Uh, people don’t even realize, someti
— $5-, $10 co-pay or something finds its way onto their — They don’t even realize
they were supposed to pay that. They’re confused, and then — So, for that — It’s a whole separate,
interesting category that our folks are looking at, so.
Couple more questions: Brian, then Jim. I see you, Patrick, and — Thank you.
Thanks. This is good research. Every installment that comes out is — is more educational,
so it’s so interesting. So, just a couple of things. I think we’re just sort of hitting
on some of the levers to improve visibility. Um, among them, we’ve hit on, I think, education,
starter-product data, and — and then, one I’d like to add to the discussion is distribution,
uh, and servicing. On the data side, I think, Ken, you asked,
uh, you know, how do you pick, uh, from one or the other? And, um, at — at present, there
isn’t — you know, having some experience — and this is an issue where there — there
isn’t a whole lot to pick from. The — the — this — Where we’ve seen success are th
— are around things like presence of a banking account, um, a household relationship, uh,
with another product, um, and then, also, uh, education, uh, are all good predictors.
Um, what we don’t have a lot of at this point are a lot of the positive data that — that
Jim mentioned earlier. There is a plethora of data out there, but the data that is available,
FCRA compliant, and then Fair Lending compliant is — is very — very minimal. Uh, and so,
anything that can be done to, sort of, unlock the good data, I think, is — will — will
help. Regarding starter products, uh, we — we’ve
offered a secured card, uh, for — you know, for — for some years now, and what’s — what’s
interesting on secured cards is the number of consumers that just don’t understand, uh,
how it actually works, uh, and might perceive the deposit as — as a fee that’ll, sort of,
never come back to them. So — so, to the comments on education — Uh, the more that
can be done to educate consumers about how the product works, uh, the — the better established
it may be and — and may be a — a — more, uh, a lever to visibility.
And then, the other thing to consider, um, are just, uh, when it comes to distribution
and product distribution, um, the — the ability to make digital a more easy way to distribute,
um, mainstream financial products. And I think anything that can be done to — to modernize,
uh, the regulations around it, uh, would be beneficial, particularly around disclosures,
uh, how disclosures are made over a — over a digital medium, and then, also, uh, Director
Cordray, some of your comments on — on, uh, telephone collection practices and the like
— modernizing that regulation, because if you can — if you can modernize the regulations
to make digital easier, it reduces the cost to serve and — and makes it easier to distribute
products, uh, directly, uh, to this group. And so, uh, uh, TCPA is one, and then, uh,
you know, around some of the disclosures is another, which — which are, you know, somewhat
cumbersome over a — over a digital medium. Uh, and if those can be better, it — it might
make distribution easier. One of the takeaways that I feel, from having
read the draft of this report and then the report, and then seeing the presentation,
it finally starts to seep in a little bit — The one thing that I think is pretty clear
is a rising tide that would lift all boats in this area is, uh, the households that are
completely unbanked almost certainly — Uh, uh, I don’t know if you will be able to or
have yet been able to correlate that with the invisibles, but that’s going to be a — a
huge issue that’s more likely to dump them into the bad categories. If we could get more
people into the banking system with these safe banking products, that at — I don’t
know exactly how that would move into the mechanisms for doing these things, but it’s
going to give them much more of a fighting chance, it seems, uh, and — and perhaps a
safe bank account coupled with a secured credit card.
You also seem to be suggesting, uh, that, um, if — may — maybe we need to be thinking
about and finding a way to do a simpler, more transparent secured credit card. Maybe it
— it is complicated for people. Does it have to be? Is there some other way to do it that
would be a little less complicated? I — I don’t know, but that comes to mind.
Great. Jim? Um, thanks, Ken, interesting data. The — the
— I’m about to ask about — about an area that’s probably beyo — beyond the bounds
of what’s possible, but it — but it — because it could be, uh, an area of — of high interest,
high impact to society in the whole, it could be worth considering.
Ask for the moon, and they’ll at least give you a street light.
There — there you go. Thank — Thank you. Maybe you could opine
survey data and make some — some inferences. So, the — the concern is these disproportionately
younger people who have had negative actions reported on their credit information. Uh,
and, you know, we — we know that there are problems with lower-income people, and especially
in — in, uh, you know, certain neighborhoods and so forth, that — that are, um — that
— that can’t find gainful employment. So, my — my — I’m wondering if it’d be possible
— again, probably through inference and other data — to identify, uh, inquiries on, um
— on one’s credit history by potential employers, showing that people who had a worsened credit
rating tended to get more inquiries by — by employers that offer, like, less desirable
employment, and then going a step further and asking for the moon, finding that that
could be correlated with arrest records. Because I simply — I — I made a poor financial decision,
I couldn’t find gainful employment. I took a crummy job, now I’m giving up in the system,
and I’m — you know, I — I’m willing to take a risk, and I end up in jail.
Yeah. So, that would be difficult. In the current data that we have, we have information
on hard inquiries, which are inquiries that are made when a consumer seeks out credit.
Um, the — the inquiries that are made in connection with employment are soft inquiries,
and as far as I’ve understood from my conversations with the bureau that’s providing us with the
data, they don’t have a means of providing that. They don’t normally provide it to lenders,
so it — it would be hard to do it for us. Um, then the — the arrest records is an interesting
thing. We’ve actually been working, trying to figure out if there are ways that we can
get data on arrest records. Uh, there had been a professor at Wharton, who I was talking
about, who had arrest records for — for Texas, and we were talking about possibly trying
to figure out if there was a way to merge the two data sets in a way that maintained
the anonymity of — of the consumers in our sample, because it would be very interested
to see, sort of, how that’s affecting credit, um, both before you wind up being arrested
— right? Does there seem to be some relationship between financial distress and being arrested,
and then what does it do to you subsequently? And not only you, but what does it do to the
people you — you share accounts with, or who are, perhaps, part of your household?
Uh, I think that’s something that we’re person — I’m personally very much interested in,
and so, hopefully, we’ll be able to get there eventually. But I — I think the employment
side of it’s going to be a little bit trickier to get at.
Patrick and then, Arjan, did you have your hand up, or you were not — Yes, Patrick,
Arjan, and then Chi Chi. Uh, just two things. One, first, to respond
to Neil’s question: Neil, when we pull our payday loan customers or — or files, it’s
only about 3- to 4%, usually, that are invisible. It’s very rarely their only or first source
of credit. It’s usually, they’re — they’re much more mature in the credit cycle.
Um, but secondly, just — You know, I think — it — it — th — this goes back to two
points Director Cordray made. I think the idea of, sort of, trying to — When you look
at this paradigm and trying to force people into this paradigm that is what we call the
credit bureaus or credit rating, credit scoring, is — is — is probably, uh, fraught with
problems and errors, and instead — and I think this plays a lot into the alternative
data discussion, is that instead of fitting people into this paradigm, say: Is this the
right paradigm to really measure someone’s credibility?
And, uh, some of the conversations we had earlier, particularly around credit cards
being the key entry point is, you know, credit cards used to serve a utility of — of just
being able to enable payments that — that — that wasn’t available otherwise. Now there’s
multiple ways of enabling those payments. And so, when you look at someone, uh, that
— that — that, uh — that makes payments through PayPal and debit and other things,
those don’t show up in this paradigm, but if they happen to be making the same payments
on a credit card, they’re in this group and paradigm. But the behavior you’re trying to
get to is really the same, whether it’s through a credit card or some alternative means.
So, I think that really comes back to that alternative data discussion is, uh, you know,
paying your bills is what you’re trying to find. The — the — the patterns are the same.
It’s just, you know, whether they fit in this box or not, you know.
Yeah, I think that’s the point I was trying to make earlier — I think you just made it
better — is that people have lots of economic activity in their lives. This is a skewed
way of measuring it, because only certain kinds of economic activities get — get added
into this system. And for some of them, it’s only a negative side of those that gets added
into this system, and the positive side is left out. That — that — it’s a problem,
and it — it does call into question the validity of this system or whether we can do better.
Arjan, then Chi Chi. I’m — I’m glad, uh, you, Director, and others
are asking “so what,” uh, about this research. That — that’s the right thing to be asking.
Um, my sense, having been working in and around financial services for low-, moderate-income
consumers is that a lot of the “so whats” that we’re exploring here are — are going
to be fundamentally ameliorative at best, um, which, sadly, within the context of this
bureau, uh, but maybe, you know, opportunistically, you know, kind of presents the issue of: We
have a very particular jurisdiction, and — right? — we’re — we’re stuck within a very narrow
can — confine of someone’s life. When you say ameliorative, you — you mean
improving, but only a little bit. Is — Yeah.
— that what you mean? Yeah.
So, not as far-reaching as you’d — Yeah.
— hope and like. Yeah. So, to build on Paulina’s co — comment,
and maybe where Jim was going: You know, I think, at some fundamental level, you know,
uh, finding ways to increase someone’s income is — is really — even — even a little bit
— really takes care of — in a much greater way, of a lot of the stuff that we would just
be able to, you know, add sand between the cracks through — through some of the reporting,
promoting a different kind of product, et cetera. Um, again, it — it — it’s a little
hard to talk about these topics, you know, in the confines of the CFPB, um, but I do
think it’s important, and maybe it — maybe the, uh — the — the call or challenge or
something like that is to find ways to reach out to others to find ways to solve for that. Sorry. I was instructed to use this microphone,
because that one has a problem. Um, so a few thoughts on a lot of the, uh, themes that
have been going around: Uh, first of all, on the issue of, um, a lot of these unsecured
cards maybe, um, uh, being under and based upon deposit account activity — Um, you know,
obviously, the things I think of immediately are: Okay, so what role does check systems,
then, and early warning services have in, you know, deterring low-income consumers from
getting banking accounts, um, and then not being able to form that deposit relationship,
which then leads to the unsecured card? Um, and, you know, safe accounts is a great
way to address that as a policy matter, so I totally agree with that. Research-wise,
you know, whether you can get checks or — or EWS information and sort of cross-match it
would be interesting. Um, you know, when we did our report on — on checks and EWS, one
thing we heard about, anecdotally, was that a lot of youths were, uh, uh, ending up with
checks records. And you would think: How does that happen? And, you know, uh, to Maeve’s,
uh, uh, point: identity theft. Um, you know, their — their identities being borrowed by
family members to be able to open up accounts. Um, uh, and then, of course, you know, deposit
accounts, there’s the issue of being able to share that information, because if it’s
only your — your — your bank that you have a deposit account with, that locks you into
that bank, um, to be able to get an unsecured card. Plus, it means you have to go to one
of the, um, deposit banks that also offers a major credit card product, right? And if
you’re banking with a community bank, and they don’t offer a credit card, then you don’t
get that same benefit, unless you can share that information.
Um, on secured offerings, you know, there is research by, um, CFSI about the — the
barriers to why they’re such a low percent, and — and mo — um, you know, it has to do
more with visibility and, um, lack of knowledge than, I think, regulatory barriers.
Um, and then, on medical collections, um, it’d be interesting to run this research a
few years after, um, the reforms due to the multi-state AG settlement and the National
Consumer Assistance Program kick in, where you have that 180-day, sort of, grace period
before medical debts show up. Thank you very much, Chi Chi, and I know I
have other people lined up, because we are very, very interested in the topic and the
research you’ve done already, Ken, but I want to check in with you, because we also have
a deferred, uh, uh, interest, uh, presentation. Do you have any, perhaps, maybe — What I
want to ask is that we hold these final remarks, and I’m sorry, because we can’t do everything
with the amount of time we have. Perhaps — Are there a few, final slides? Yeah, I’ll — I’ll — I’ll do, sort of, the
highlights of — of what remains. Thanks.
So, the — the main section that comes after this is — is, sort of, the role of other
people in helping people acquire a credit history. All right? So, if — if you yourself
m — perhaps because you’re credit invisible, go to a lender and are able — unable to get
a loan yourself, you may be able to, for example, enlist the help of a — of co-borrower. So,
we wanted to look at how many of these first-reported pieces of information, uh, were take — were
loans that were taken out with the help of somebody else.
Uh, and so, this shows you the share of each of the different entry-type products that
were opened up with a co-borrower. Um, the results there are — are not all that surprising.
Um, the real, sort of, significant difference, I think, is — I think if you look at what
the share is — the share of these different loan types that are taken out with a co-borrower
across neighborhood income levels. Um, so what we’ve done here is, we’ve plotted
the shares, uh, for the dif — for the six different loan types that we have in the data,
uh, for low-, moderate-, middle-, and upper-income levels. We’ve sorted them in a slightly different
way than they are in the tables to make them easier to see. Uh, in this case, the — the
share of, uh, co-borrower accounts, uh, is — is declining from left to right.
And what you see is that if you look at middle- and upper-income consumers, most of the people
who make that transition, they have a very similar share of those entry products that
involve a co-borrower. But if you look at moderate areas or moderate-income areas and
low-income areas, you’re seeing much less — less — or much lower tendencies, uh, to
rely on co-borrowers across these different products, with the one exception being retail,
where, um, all four income areas tend to have about the same level of, uh — of co-borrower
participation. And then, we also looked at the role of authorized
users. Authorized-user status is — is one way that, uh, people, traditionally, have
gotten access to, uh, a credit record. Um, it’s the way that I personally got access
back when I was 18. Um, and the way this works is that you have somebody who has a credit
card, who has the ability to add — allow somebody else to use that credit card, without
them incurring any legal liability. Um, so in — in — in my case, when I was
eight — when I was 18 and I had a — a car, my mother made me an authorized user on her
credit card. And one of the things that this did is that once I was added to that credit
card, the entire history of that account was added to my credit record. So, even though
I was 18, if that was a 20-year credit card, that entire 20-year history wound up being
reported on my credit record. So, I instantly had a credit record that allowed me to get
credit from other users, um, which actually was my mother’s point in doing this. She worked
for a credit card company. She gave me — made me an authorized user on the card, gave me
a card, told me if I ever used it in a situation that she did not deem an emergency, there
would be hell to pay — — and then eventually, Citibank sent me a
— uh, a letter in the mail saying, “Hey, you want a card?” They gave me one, and, uh,
we tore that one up. So, I — I wanted to understand how these
authorized users to — to acquire a credit history was playing out, uh, and also, again,
particularly looking across, uh, different neighborhood income levels.
So, overall, about 19% of people have an authorized-user account, uh, on their credit record. Uh, about
half of these — that population tends to use at least one authorized-user account to,
sort of, make their entry into the credit-reporting system. So, about 10% of the population overall
had an authorized-user account that appears to have appeared on their credit record before
any of their other, uh, products. Uh, and on average, when they — when the authorized-user
account appeared on their credit record, generally, it was about 5 years of credit history that
they acquired right off the bat. And if you look across income levels, what
you see, again, is that this tendency, uh, of people to use authorized-user status, or
use the credit history of — of someone else to help themselves acquire credit, uh, is
much higher in upper-income communities than it is in lower-income communities. Um, so
they’re — in general, people in lower-income communities were much less likely to have
an authorized-user account, uh, and they were much less likely to have the authorized-user
account be the first thing that appeared on their credit record. Um, and when the authorized-user
account did appear on their credit record, they seem to have acquired less credit history.
So, if you take these two pieces of information together, the fact that about 15% of people
have their entry product be a — with a co-borrower, and an additional, roughly, 10% of the population
tends to have their entry be via an authorized-user account, about 1 in 4 people in our data,
it looks like, tends to acquire their credit history as a result of, at least in part,
somebody else. And then, this — this tendency tends to be much lower in lower- and moderate-income
communities. So, it seems that one of the barriers to ha — to credit visibility that
I don’t think it — it’s talked about quite as much, may be the inability to rely on others
to help you make this transition. Uh, and so, I don’t have a lot of time, so
I — I won’t really go through the changes by time. I think most people in the room have
— have — have — have read the document, it seems, so, um, if anyone has questions,
I’d love to answer them. Otherwise, I’ll cede the rest of my time.
I think we will have to wrap up on this point. Thank you very much for your great research.
Thanks, everybody, for a really great discussion — — um, and input. Um, I’m sure people will
have — do have much more to say to you. Um, we want to transition into deferred interest,
and we have with us today, um, Wei Zhang with Credit Card Pay — the credit card program
manager with Cards, Payments, and Deposit Markets. Thank you so much. Sorry to be starting
so late. Um, appreciate your being here. And we also have, uh, Will Wade-Gery, Assistant
Director at Cards, Payments, and, uh, Deposits. Um, please, take it away.
Good morning. How everyone? Um, I have to confess that we actually don’t have a presentation
here to share with you, uh, but we would rather use this opportunity, uh, to have a conversation
to solicit some feedback from all of you about this product. Um, I can begin by just highlighting
some, uh, facts that the director mentioned earlier, as well as some context, uh, around
the study, uh, that we have done so far, as well as some latest, uh, market development.
Uh, so deferred interest, as you all know, is a very popular product. It’s available,
virtually, every retail establi — establishment, uh, from appliances stores, uh, medical providers,
as well jewelers, and, uh, some home improvement, uh, stores. Uh, so when we first, uh, start
this pro — uh, report in 2013, in our report, where what you find most majority of the consumers
actually successfully manage the product, where it — what I mean, successful, that
mean 80% of consumer actually can pay their deferred inter — uh, the entire balance before
the promotion ended. Only 20%, for some reason, couldn’t do — do so.
So, in 2015, we actually look into this pop — 20% population very closely. We try to
figure out, you know, what’s the reason actually causing them couldn’t pay, you know, similar
to other, uh, data analytical work. You know, we don’t have a perfect data to gauge what
consumers really think. But at least some data point can — gave us some correlation
in terms why they actually didn’t manage to pay that whole balance off at — in the — the
promotion. So, one key observation, as highlighted by,
uh, Director, that’s where the 20% of the population where they couldn’t pay during
the promotion; however, they made rapid payment immediately after the promotion ended. So,
I kind of can imagine a situation where consumer probably, initially, didn’t understand the
product well. Then, all of a sudden, at the end of promotion, they have assume a very
small balance. All of a sudden, a big finance charge being added to that balance. This is
where — kind of a wake-up call, where, “Oh, gosh, actually, this is how product works.”
So, the data at least provides some kind of correlation to that scenario, where people
realize there’s a — this is actually how the product works. So, this is one key habit
that we — we find in our research. Uh, the other part, uh, kind of make the situation
little bit more difficult, because if you look at the deferred-interest pro — promotion,
this typically more looks like a — a installment loan: You make payment on a fixed pur — amount
purchase. But at the same time, actually, this is part of your credit revolving line.
So, that means, when you have a purchase in the promotion, same time — Actually, you
have ability to continue to use the card, to make more purchases on the card. So, with
multiple balances on the card, make managing the promotion appear very difficult. This
is where we find — Can — Can I — Can I emphasize this point
for a minute? Because this is one of the things you all kind of explained to me over the course
of preparing for this speech and so forth, and I had not grasped it before that.
Uh, I had tended to think about this situation as one where consumer with no prior history
goes into a store, gets a card on a promotion and then carries a balance and goes forward,
uh, and, you know, tries to pay off that balance in the time, uh, no prior events, history,
et cetera. Then, there’s the added complication of, they go in, they get this card, promotional
balance, et cetera, but then they may use the card a few times over the course of that
same period, and then, you know, it’s a little confusing, perhaps, to them whether they’re
still paying on that promotion or whether they’ve paid that off first, and then the
other payments come later, et cetera. But, you know, I think one of the points you’ve
made to me that I hadn’t quite grasped is, this can actually be even more confusing,
in a sense, because the person might have had this store card for some time. They don’t
always get the store card for the promotional balance. The promotion might — might not
be at the time they take out the card. Is that correct? They — they — they — they could have a
history at this store, and some charges and things, and then get a promotion on top of
that. So, there might be a pre-history, as well as a post-history. Is that right? It’s not always the brand-new card. Okay.
Got it. That — So, it’s even more confu — And you get the same effect. If you go — It
doesn’t have to — Yes.
— be new purchases during the promotional period. It could simply be going in with an
existing balance. Then, you’ve got promotional and non-promotional at the same time.
Yes, it’s very complicated. Absolutely. So, this is where we find, for
— for those people who actually, uh, fail to pay the whole thing off, with — with multiple
balances, where we actually find over 50% of the users who actually paid more than the
promotional balance and still end up being charged the deferred interest.
It’s even worse when you look the stream. Over one-third of the population actually
paid over 150% of the initial balance and still end up being charged the deferred interest.
So, this — this kind of highlight where, you know, the concept itself is not that straightforward.
Second, because the revolving nature of other balances — you know, consumer use over time
— that make this very difficult to manage. Uh, so those are the key observations that
we find. Also con — uh, on that is, this market actually grow very rapidly. Uh, the
data available to us show over 20% growth rate from 2010 through 2013. So, again, this
is a very, uh, popular product. Uh, so in light of the, uh, announcement that, uh, uh,
Director Cordray mentioned — Walmart make this change, where — kind of remove the deferred
feature of this product. So, like I said earlier, where 80% of the population actually manage
this product successfully, they’re not paying no re — retroactive interest at all.
So, under the true zero scenario, you can imagine: This population, basically, will
get the same results. They will continue to get zero percent finance charge. There’s no
change to them. However, for the remaining 20%, in particular in case where we find,
uh, student consumers actually have very small balance left at the end of the promotion but
still end up being charged a very large sum of the deferred interest.
So, imagine a situation where, you know, the consumer, in the first place, met some difficulties
to pay that smaller balance, the — and that was, in large, a finance charge on that balance.
So, clearly, this calculation will make them har — even harder. So, this is where we welcome
this change, and, uh, we hope, you know, others could follow and, um, make the change accordingly.
Uh, so like I said earlier, this is really, kind of, not a presentation but that we want
to, uh, hear from you what you think about this change, uh, what you think about the
product. So, you know, personally, I use this product quite often. I — I buy pair of, uh,
washer/dryer, and, uh, manage it successfully. Uh, I did my floor using the same product.
I think, probably, partially gives the fact I spent too much time research this product. But I don’t have a — a clear component to
support it, but at least, you know, this is what — my experience.
This is how we get all the disclosures . So, really, kind of, you know, I want to turn
around and ask you, you know, uh — you know, what your experience. Have you ever used this
product? What do you think about the risks and benefits of this product?
Great. We have Judy and then Chi Chi. So, I, too, just bought my washer and dryer
with the, uh — what, like, 6 months same as cash or whatever, uh, which brings up some,
sort of, positives and negatives. So, I really support the idea of having zero percent, you
know, interest, as opposed to this deferred interest, uh, largely because of the confusion.
Uh, in my recent experience, um, the, uh, store that we purchased this from, which we’ve
bought appliances from over the years, um, never sent a statement. They emailed my husband,
and my husband doesn’t read his email. So, we — we — I kept saying to him, “Well, you
know, why — We should be getting something, you know, in the mail.” And I finally called
them and, you know, discovered that they’d been sending them to my husband’s email.
So, I do think it’s con — and I notice that more and more, um, you know, some people like
electronic statements, but I think it’s a problem that we — that — that some places
are automatically, um, going to that without full disclosure, and, you know, in our situation,
it wasn’t good. Um, the other thing, I think, is that the
Card Act has improved how these things get reported. Um, I’ve found myself, um, getting
one of these promotions and not even knowing it. You know, like, you — you go to a — a
— a store, and you buy something, and then, when your bill comes, there’s like, “This
is your promotional level.” I was like, “I didn’t even know I — I did that.”
Um, I — I think it’s good that it’s broken out, um, but I also think that’s really confusing,
because you can’t allocate what you’re paying. In other words, if — if you — unless you
pay the whole balance off at that time, but — but if you just send in a payment, it gets
allocated to not the promotion. It gets allocated first to the non-promotion item, and that’s
confusing to consumers. You send it in and try to indicate to them
you want — Yeah, because it’s all computerized. Yeah.
You — And a person’s not looking at it, right? So — So, I think it would be useful if there
would be a way you could do that. You know, like, “I want to pay $50 on my balance, and
I want to pay my whole promotion off,” you know, and you could allocate. And — and as
far as I’ve been able to figure out, there’s no way to do that.
And then, my third point is, um, I — I must be with Chi Chi up late at night, watching,
uh, Star Trek, uh, watching all these commercials, but, um — And Max isn’t here. He mentioned
to us before that, you know, mattresses are the things that people do this for the most.
But I was watching a commercial for a mattress salesman, and they were offering, um, 4 years
same as cash, which as I was watching that, I was thinking: Is that deferred, or is that
zero percent interest? It’s probably deferred, but I could see you
watching that add thinking you had 4 years to pay and had no interest, and if you didn’t
pay for 4 years and missed a payment, you’d have an awful lot of interest. I mean, these
things tend to be short term, but that was very long term. And I think one of the problems
here is that if you look at the advertisements, it’s very hard for a consumer to figure out
if it’s zero interest or deferred interest. Just, on the allocation issues: There’s a
range of practices. So, the Card Act says that until the last 2 months of the promo
— um, with a caveat — the issuer would have to allocate to the non-promo balance, and
then that switches — I’m not talking about the minimum payment. I’m talking about amounts
above the minimum payment — that switches, in the last 2 months, to make the default
allocation to the promo balance. The Card Act does permit, but does not require,
the issuer to allocate differently upon consumer request, and there’s a range of practices
there. So, some issuers actually communicate to cardholders that they can make that allocation
change, um, and then honor those requests. Some honor those requests but don’t communicate
to cardholders that they can make those requests, and some won’t honor those requests even if
made. There’s a range of practices there. Yeah. And — And I — And I will say: I don’t
think it’s very clear to the cardholder how to make — even make the request.
Thank you. In the interest of time, because we’re being recorded — We’re going to have
a hard stop at noon, um, for a public session. We’ve got six comments. I’d like to ask staff
if we can take the six comments, so people — everybody has a chance to be heard, and
if all of you would be — commenters, uh, would be snappy, that would be great. Thank
you. I will try to talk really fast, because I
have a lot of comments. I mean, first, obviously, terrific research, um, by the — by way of
the credit card team. Um, there was so much more in that 2015 report about deferred interest.
Um, also, you know, um, really glad, Director Cordray, that, um, you’re sending the letter
to the retailers. It’s a great use of the bully pulpit, um, to — to try to encourage
good behavior. Um, however, I ultimately do think the solution
to this is: Deferred interest needs to be banned. Um, deferred interest only exists
because it is an exception, in Reg Z, to the Card Act provisions. The Card Act actually
literally prohibits the deferred interest, as — as — as this is constructed right now,
because the ban on double-cycle billing pro — prohibits retroactive interest on amounts
paid. Um, and so, um, that’s what happens with this form of deferred interest. And,
uh, the Fed created an exception in Reg Z for deferred interest to allow it to flour
— flourish. And what’s even more interesting is, before
that, they had banned — the Fed had banned deferred interest under its UDAP authority,
and went through an entire UDAP analysis saying how unfair and abusive this was to consumers,
um, and banned it, but then reversed itself. So, historically, there actually has been
a finding: This is so bad for consumers, it should be banned. So, that’s what we ultimately
urge. Um, you know, we — we’ve seen many examples
where this trips people up. Um, one of the great statistics in your report is, 20% of
these folks get socked with retroactive interest, but it’s 40% of subprime consumers. So, almost
half of subprime consumers end up hurt by this, so the — the ones, probably, that can
least afford it. Um, and then, you know, in the intersection
with electronic statements — You know, Judith’s example — You know, we’ve — In the, um,
Consumer Complaint Database, we’ve seen examples of, uh, consumers who have been tripped up
with the — the combination of deferred interest and electronic statements.
In general, um, we think, um, issuers are pushing people too hard into electronic statements
with respect to credit cards. They’re, you know, late — they’re paying late; there’s
late fees. Our most pop — one of our most popular papers, actually, is our whitepaper
on why, uh, the CFPB should protect consumers’, um, right to get paper statements.
Um, so — and then payment allocation incredibly confusing. Deferred interest itself is confusing,
and then the payment allocation, um, is even crazier, so.
Oh, and by the way, in terms of personal examples, I don’t have one. I haven’t been bold enough
to try this, but I do have colleagues, okay, colleagues at National Consumer Law Center,
okay, who have been tripped up by this. So, you know, e — e — even the most sophisticated
get tripped up. Thank you. Chris, Kathleen.
I had to build in time for a chair switch. Um, so, just, uh, two quick ones, and one
— one of my questions was around the, uh — the payment allocations and wondering how
it is you could pay 150% of your balance and still get hit with it, and I think that’s
clear. Um, like — like Judith, I’ve been up late
at night watching, you know, late-night TV, and, uh, there’s also — You know, I see the
same thing with furniture companies, except it’s, like, 5 and 6 years. And so, um, uh,
y — uh, I’m pretty confident these are deferred interest, because you would want them in this
for 5 years, because that’s 5 years of opportunity for them to screw up.
Um, I — When I was — When my wife and I first got married, we bought — I think it’s
the same story all the time. We bought the washer and dryer from Sears. Uh, they had
the zero percent thing, got the card. Um, nobody said a word about, there’s a minimum
payment that you have to be making in order to — to get that. Um, I read the disclosure,
and it was buried on page 2 of the disclosure, in — in between, I think, the, uh, um — the
— the separation clause and the choice of law clause that said you have to continue
making a minimum payment, which will be listed on your statement.
Um, and so, I could easily see how somebody who didn’t bother to look at it and thought,
“Well, this is zero percent interest,” would probably miss the first one, and then find
themselves in a 29% rate, uh, going forward. So, yeah, I — I think it’s incredibly easy
to get tripped up by these. Kathleen, then Ann.
So, I think the, uh, deferred interest, um, arrangements are, um, an evidence of, uh,
the way in which complexity creates cross-subsidies. So, I think, with the exception, um, of — of,
you know, people who ended up getting caught up in this, those of us who have used products
like this are making money on it — right? — because we’re not paying interest. And
what happens is that, um, the money that the issuers are making on the people who are less
sophisticated, um, is more than what they’re losing on us.
And that’s true with lots of things. I know I get at least 250,000 free airline miles
a year, right? Somebody is paying for my miles. So, it costs me about, you know, maybe $300
in — in, uh, credit card annual fees, but the miles are worth a whole lot more. So,
um — So, when this happens, really, is that deferred interest is a subsidy to sophisticated
consumers, and I think just from a — a philosophical standpoint, the CFPB should be doing what
it can to minimize or eliminate cross-subsidies that arise from complexity and confusion.
Thank you. Ann? Just, quickly — I had a family member who
got trapped in exactly what Chris was mentioning and thought they had this deferred-interest
time period and ended up getting charged interest immediately, and luckily had the money to
pay it off and were very disgusted with — or disappointed with the transaction.
But, also, just as a basic point: I mean, this seems like the perfect scenario where
this product is profitable where people mess up. And the profitability is based on people
messing up. And that’s always a problematic — It’s a problematic practice we’ve seen
across a lot of consumer markets, and — and probably a core reason why this is something
that it’s great to see the attention being paid on — on this. And whether it’s the market
that will change itself or whether it needs regulation — It — it seems like any product
based on — if it’s profitable because people mess up, is — is one that — that is concerning.
By the way, no — This is a great example of something I’m sure you all see all the
time, too: You’ll go to buy a product, typically at a computer store or something, and they’ll
sell you the product with a $30 rebate, but you have to send something in to get the rebate.
The only reason to do that is because they know that some portion of you will not send
it in and not get the rebate. So, it seems like it’s 30 — I mean, uh, I — I don’t — I
really don’t understand the functionality of that, uh, approach to selling a product.
I — I really don’t quite get it. Joann, and then Brian will have the last word.
Passing? Okay. Brian? Thanks. I think just about every point I was going
to make have been made regarding the subsidies and the — and the effect on consumers, so
the — the one thing I can think of is that you may need to do more than just ask for,
sort of, voluntary compliance. So, just knowing a product’s, uh — The zero is actually more
expensive for the retailers than — than if you were deferred interest, and for that reason,
it may take more than just a — a volun — you know, an ask for, sort of, voluntary compliance,
and you may have to do more, so. Uh —
Can I just add one quick — Yes. Ruhi.
— thing? Um, so we were also offered such a thing, and like, uh, uh, Chi Chi, I was
like, “I know there’s a catch. I know it’s going to mess up, and I don’t want to go.”
But the thing that was interesting that no one has mentioned — because I started quizzing
the guy, basically wearing my CFPB hat. And, apparently, what happens is, if you — somehow
you do and don’t qualify — this was for windows — and when you don’t qualify, they put you
into some — they sent you — and — and the guy very carefully, very nicely, explained
it to us, and he was very confused by it himself. He’s been doing this for a very long time.
But they sent you somewhere else, where, somehow, you ended up with a much higher interest rate,
complicated product that was, from what I — you know, uh, what it sounded like was
actually predatory. So, I’m wondering if the — if the money that’s being made isn’t just
from the people who — the 20% who mess up but the other people who end up in higher-cost
loans because they didn’t qualify for that first — for that first product.
And I — and I don’t quite know — and I — I — you know, I, sort of, wanted to follow
up with him and figure it out, but it all was very mysterious. And see, this is very
str — you know, strange. We say no to people, but then we send them somewhere else, and
there, they get charged 24.99%. And he was, himself, mystified by it. So, I — I want
— Oh, oh, sorry. So, yeah, I — I mean, I — uh,
uh, I — I don’t know how I would figure out what that — And he — he was — he was kind
of like, “That’s not really a great thing that they –” You know, but, you know, he
was — he had a job. And I would love to figure out, uh, how that plays out and whether — how
much that is playing out in the — in the appliance store and the washer/dryer store
and stuff. Great. We have a — a minute or two if you
have anything you want to put out here in public session to us in response to what you’ve
heard. Um, I — I — I’ll say something on the complexity
point, Wei. I don’t know if you want to say something on the second le — uh, part of
the issue. Um, another thing that we did in — in the study, um, we did look to see, um,
the extent to which consumers learn, over time, about deferred interest. So, we did
this at the account level. We tried to work out whether there was a higher payment rate,
meaning, people successfully paid off a promo during the promo period — if they did that
better the second time than the first time, or the third time than the second time.
And when you first look at that data, you do see that second transactions have a higher
payoff rate, but then if you look within that, that is not because people are learning; it
is because the population starts to skew towards people who use it successfully the first time.
So, if you fail, you then tend to drop out of having a second one or a third one, whereas
if you succeed, you go on and have more. And so, I think one of the more depressing findings,
uh, in the study was that we didn’t see learning about the product.
The — the second scenario you mentioned, I think, is related to, uh, a — a so-called
second-look program — This is where — FEYeah.
This is where, basically, a consumer initial — there’s two lenders, actually, in that
space. One has, maybe, a — a little tighter underwriting criteria. The second one have
a much looser criteria. So, that’s why you didn’t qualify for the first one, you end
up sen — be sent to the second one. Typically, the second one has much higher
rate, like — like you mentioned. The first one, typically, is higher, too — you know,
in the — in the retail establishment, roughly 25%. So, second-tier, definitely much higher
than that. So, again, if you look, the — the financing nature of this product, it’s really
help the retailer to make more sales. So, this is where the more, I — I think’s, better.
But it was the same finance company. So, that was what was interesting. So, it wasn’t — So,
you didn’t get sent to a second finance company. You got sent to the same finance company,
but it happened so — One way that — The vehicle was — I talked to the sales guy who
came to our house — it was windows. But then, the second one was — it was the same company,
and so that’s why this — You know, he was a sweet old man, and he was saying, “This
is very strange, you know. When I — When I turn — When I take you — This is how it
plays out: When I turn you down, the same company will lend to — will lend to you,
but at — at 28 — You know, what — I don’t –” And he was sort of war —
I mean, we qualified, and it wasn’t an issue at all, but you have to kind of — You came
to the house, and they somehow figured out your credit, and they ran it, and he was — there
you are. You know, he’s giving you all the measurements for the windows. You’re like,
“Okay, let’s go.” And then, you’re, like — And we were just going to pay cash. It wasn’t
an issue — issue for us. But it was a way of, like, you — you — you basically bought,
and then you suddenly realized you — you don’t qualify for the credit, and then you
qualify for the predatory credit. I — Sorry — Sorry to interrupt. Sorry. We are at — at time for our public
session. So, sorry. I want to thank staff, and I want to thank the CAB members for great
questions, great input. To the public, we’re breaking until 2:00. Uh, we’ll return at 2:00,
um, uh, and, uh, look forward to seeing you all back then. Thank you.