the spectrum of lending: completing the consumer picture€¦ · short-term borrowers are unbanked...

Liz Pagel

Vice President

Consumer Lending Market Strategy

The Spectrum of Lending:

Completing the Consumer Picture

© 2018 TransUnion LLC All Rights Reserved | 3

• What does the alternative credit database look like, and why is it relevant to

you?

• Can we test the conventional wisdom about consumers active in alternative

credit markets?

• How can blending traditional and alternative credit data help lenders refine

underwriting strategies?

• What are some practical applications?

In this session, we’ll review:

v

vv

What does the alternative credit database look like,

and why is it relevant to you?


Alternative loans

are a major

category of credit

obligations

not reflected in

the traditional

credit file

What are alternative loans?

Not included: Utilities, telecom, other non-loan obligations

Rent to

Own

Buy-here

pay-here

Installment

Loans

Short-term

Loans


Historically short loan terms

incongruous with:

• Standard reporting formats

• Monthly reporting cadence

Why haven’t we talked about alternative loan data before?

Technical

limitations

Relevance to

traditional lenders

Loan category historically outside

scope for lenders:

• Products not offered

• Perception that customer base

does not participate in this market


Recognizing the importance of these data, TransUnion

acquired FactorTrust in November 2017

Source: TransUnion alternative lending database

29.5 million consumers

+ 500,000 each month

Not widely reported Real-time updates Full file reporting

FCRA-compliant data

with adverse action

codes

Strict reciprocity-driven

reporting model


2015 2016 20172-YR

growthToday

Consumers 15.9M 21.2M 26.1M 64% 29.5M

Tradelines 48.5M 56.0M 72.4M 49% 78.8M

Inquiries 65.5M 88.1M 118.9M 82% 143.2M

Source: TransUnion alternative lending database

Our alternative credit database has information on 28M

consumers and is growing rapidly


The database has robust, FCRA-compliant data, much of

which is incremental and worth highlighting

8+Credit inquiries

per year

per consumer

Inquiry data Tradeline data

Contact• Email address

• Mobile/home numbers

• Up-to-date addresses

Payments• Payment account

• Payment status

• Payment amount

• Returned payments

Loan behavior• Loan roll-over tagging

Employment (stated)• Employer

• Monthly income

• Payroll type

• Payroll frequency

Checking• Bank

• Account number

v

vv

Can we test the conventional wisdom about

consumers who are active in alternative credit

markets?


What’s the conventional wisdom around consumers who

are active in the alternative loan market?

#1

#2

#3

Consumers active in the alternative loan market are

riskier than those who are not

Short-term borrowers are unbanked – they don’t have

access to traditional loan products

Consumers present in the alternative credit database

utilize credit differently

Consumers active in the alternative loan market are more

delinquent on their traditional products#4

Hypothesis #1: Consumers active in the alternative loan

market are riskier than those who are not


TRUE: Alternative credit consumers are much more likely to

be subprime, but over 30% are near prime or better

VantageScore® 3.0 risk ranges

Subprime = 300-600; Near prime = 601-660; Prime = 661-720; Prime plus = 721-780; Super prime = 781-850 Source: TransUnion consumer credit database,

TransUnion alternative lending database

Risk distribution as of Q1 2018

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Alternative lending consumers U.S. population

Ris

k d

istr

ibu

tio

n

Super prime

Prime plus

Prime

Near prime

Subprime

Unscored

25%

66%

12%

Hypothesis #2: Short-term borrowers are unbanked –

they don’t have access to traditional loan products


FALSE: Alternative credit market participants have open

traditional credit products on par with the U.S. population

Number of open traditional credit products as of Q1 2018

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Alternative lending consumers U.S. population

Dis

trib

uti

on

of

# o

f o

pen

tra

des

3+

2

1

0

Source: TransUnion consumer credit database,



To better understand these consumers and their use of

traditional credit, we conducted a study

t: consumer opens a

traditional credit productt + 12

Metrics measured at t-1:

Consumer demographics

Wallet profile

Presence in alternative

lending database

Alternative lending attributes:

Number of short-term trades,

number of cell phones, etc.

t - 1

Metrics measured at t+12:

Delinquency rates of

originated products

Measured at t:

Originated product

attributes

Lender type

We studied over 5 million consumers who originated a traditional product between Q2 2015 and Q1 2016


Distribution of consumers

449,294

5,134,172

Present in alternativelending database

Not present

Of the over 5 million consumers who opened a traditional

product, 8% were present in the alternative lending database



• “Not present” is also a valuable

data point

• Hit rate is much higher in

subprime at 22.0%

• Hit rate is much lower in prime

and above at 1.7%

The “not present” population represents consumers present in the traditional credit database but not

present in the alternative lending database.


We controlled for risk and open traditional trades and ended

up with a study population of almost 1.5 million consumers

The “not present” population represents consumers present in the traditional credit database but not present

in the alternative lending database. Source: TransUnion consumer credit database,


Example of sampling down for VantageScore® 3.0 661-720 and 1 open trade

1.27%

4.04%

1.27%

0%

1%

2%

3%

4%

5%

% o

f co

nsu

mers Present in alternative lending

database

Not present

Not present, sampled

Hypothesis #3: Consumers present in the alternative

credit database utilize traditional credit differently


TRUE: These consumers are more likely to open auto and

personal loans. But, they’re present across all products.




Distribution of traditional credit products opened at t

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Present in alternative lendingdatabase

Not present

Dis

trib

uti

on

of

op

en

ed

pro

du

cts

Other

Real estate

Private label

Bankcard

Secured personal loan

Unsecured personal loan

Auto

50%37%


Slightly more consumers borrow from traditional finance

companies, but all lender types are represented




Distribution of lenders for traditional products opened at t

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%


Not present

Dis

trib

uti

on

of

len

der

typ

es

FinTech

Credit union

Bank

Traditional finance company


When looking at just unsecured personal loans, all lender

types are still represented




Distribution of lenders for unsecured personal loans opened at t

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%


Not present

Dis

trib

uti

on

of

len

der

typ

es

FinTech

Credit union

Bank

Traditional finance company


Consumers with alternative lending activity receive lower

unsecured personal loan amounts




Average originated amount of unsecured personal loans

$0

$500

$1,000

$1,500

$2,000

$2,500

$3,000

$3,500

Ori

gin

ati

on

am

ou

nt

Present in alternative

lending databaseNot present


These consumers also tend to receive lower lines on

cards, potentially driven by choice of providers




Average credit limit of originated revolving products

$0

$200

$400

$600

$800

$1,000

$1,200

$1,400

$1,600

$1,800

$2,000

Bankcard Private label

Avera

ge c

red

it l

imit


Not present

Hypothesis #4: Consumers active in the alternative loan

market are more delinquent on their traditional products


TRUE: At first glance, these consumers have higher

delinquency levels across all products

Serious delinquency is 90+ DPD for card, 60+ DPD for all else.




Ever seriously delinquent in 12 MOB of originated traditional product

0%

5%

10%

15%

20%

25%

Unsecuredpersonal loan

Auto Securedpersonal loan


% s

eri

ou

s d

elin

qu

en

cy


Not present


Consumers who perform well on alternative loans have

delinquency rates closer to those not present on the file

Serious delinquency is 90+ DPD for card, 60+ DPD for all else.




Ever seriously delinquent in 12 MOB of originated traditional product

0%

5%

10%

15%

20%

25%

Unsecuredpersonal loan

Auto Securedpersonal loan


% s

eri

ou

s d

elin

qu

en

cy


Not present

Consumers with atleast one alternativeloan and nodelinquencies


In summary, these consumers are higher risk overall, but

additional data points can help separate that risk

Credit profile factors

Are more likely to originate auto or personal loans than other products

but do originate all product types

Skew heavily toward subprime but are not all subprime

Have smaller personal loans and lower credit limits on cards, even

when controlling for credit score

Have higher serious delinquency rates across all products

Are less delinquent when they’ve had multiple paid-as-agreed

short-term loans

Alternative lending consumers:

Risk distribution

Product type

Credit performance

Loan amount

Borrow more frequently from finance companies, although they’re

materially present across all lender typesLender type

v

vv

How can blending traditional and alternative credit

data help lenders refine underwriting strategies?


Lenders commonly utilize credit score thresholds for risk

decisioning



Ever 90+ DPD on traditional product by risk score

0%

10%

20%

30%

40%

50%

60%

Delin

qu

en

cy r

ate

VantageScore® 3.0

All consumers


Knowing a consumer is in the alternative lending database

can help lenders make more precise evaluations




Ever 90+ DPD on traditional product by risk score

0%

10%

20%

30%

40%

50%

60%

Delin

qu

en

cy r

ate

VantageScore® 3.0

All consumers

Present inalternativelending database

Not present



in the alternative lending database.

Note: For near prime tier only. Near prime = VantageScore® 3.0 601-660

10%

17%

0%

4%

8%

12%

16%

20%

24%

0%

10%

20%

30%

40%

50%

60%

0 1 2 3 4-5 6-7 8+

Delin

qu

en

cy ra

te%

of

near

pri

me c

on

su

mers

# of deposit accounts

Deposit accounts in alt. lending file; ever 90+ DPD in 12 MOB on traditional product



We can also use other attributes to mitigate risk. Near prime

consumers with more deposit accounts are more delinquent.


Consumers with more address changes are more likely to

be delinquent



Note: For near prime tier only. Near prime = VantageScore® 3.0 601-660 Source: TransUnion consumer credit database,


11%

16%

0%

4%

8%

12%

16%

20%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 2 3 4+

De

linq

ue

nc

y ra

te%

of

near

pri

me c

on

su

mers

# of zip codes

Number of zip codes in alt. lending file; ever 90+ DPD in 12 MOB on traditional product


A high number of cell phone numbers on file is another

high-risk indicator





10%

20%

0%

4%

8%

12%

16%

20%

24%

0%

10%

20%

30%

40%

50%

60%

Unknown 1 2 3 4-5 6+

De

linq

ue

nc

y ra

te%

of

near

pri

me

co

nsu

me

rs

# of cell phone numbers

Number of cell numbers in alt. lending file; ever 90+ DPD in 12 MOB on traditional product


Consumers who make ST products part of their financial

management strategy handle all debt more responsibly

Note: Only includes consumers who have ever had a short-term trade.





14%

9%

0%

3%

6%

9%

12%

15%

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

10%

1 2 3 4 5 6 7 8 9 10 11-20 21-50 51+

Delin

qu

en

cy ra

te%

of

near

pri

me c

on

su

mers

# of short-term loans

Number of short-term loans ever; ever 90+ DPD in 12 MOB on traditional product


Consumers who have experience successfully managing

alternative credit also perform better on traditional trades



18%

8%

0%

4%

8%

12%

16%

20%

24%

0%

5%

10%

15%

20%

25%

30%

0 1 2 3-4 5-6 7-8 9-10 11+

De

linq

ue

nc

y ra

te%

of

near

pri

me c

on

su

mers

# of satisfactory short-term loans everNote: Only includes consumers who have ever had a short-term trade.



Note: For near prime tier only. Near prime = VantageScore® 3.0 601-660

Satisfactory short-term trades; ever 90+ DPD in 12 MOB on traditional product


Alternative data can provide deeper insights into consumer

behavior than traditional credit data alone

Alternative data factors

Are more delinquent when they utilize several deposit accounts over time

Experience more delinquencies with more moves

Are typically higher risks when they have more than two cell phones on file

Alternative lending consumers:

Deposit accounts

Regular borrowing

Contact information

Address stability

Are less delinquent on traditional products when they’re regular short-

term loan users

Positive paymentsAre less delinquent on traditional products when they’ve had

multiple, positive, short-term loan payments

v

vv

What are some practical applications?


Subprime Near prime Prime Prime plus Super prime

Trended data

Multisource alternative data

Alternative credit data

VantageScore® 3.0 risk ranges

Subprime = 300-600; Near prime = 601-660; Prime = 661-720; Prime plus = 721-780; Super prime = 781-850

The alterative credit data complement CreditVision Link

data sources to score consumers across the spectrum


For traditional,

FinTech, and

consumer finance

lenders

For short-term /

alternative lenders

CreditVision® LinkSM Scores

CreditVision Link Short-Term

Risk Score

Additionally, a suite

of Alternative

Credit Attributes

(ACA) will be

available for:

- Prescreen

suppression/

inclusion

- High-risk triggers

- Custom model

builds

The alternative credit data will be layered into

TransUnion’s next generation of CreditVision Link Scores


• Alternative data are a valuable supplement to traditional credit data when

making lending decisions

• Alternative loan consumers are active in traditional credit but have different

preferences and behaviors — understanding these differences can unlock

valuable insights

• Alternative data, when combined with traditional data, can be used to identify

experienced borrowers with good performance or to segment out higher-risk

consumers

• This is just one example — TransUnion is continually exploring and evaluating

data sources to provide new insights to better serve consumers

In summary:

the spectrum of lending: completing the consumer picture€¦ · short-term borrowers are unbanked...

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