Date post: | 19-Oct-2014 |
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How does risk change when payment and spend behavior changes?
Michael McGinley Experian
#vision2014
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Using trended data to understand consumer behavior
Payment data
► Payments and risk
► Spend and risk
Creating a trended payment metric
Optimizing line and loan amounts
Agenda
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Trended data
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Trended data Experian retains 24 months of history on key data fields on every trade
Trade #1 Bank name Account # Open date Credit line Balance Actual payment Loan type
Visa 4812 3/9/1990 $25,800 $13,300 $650 Credit card
Account condition
Account status
Special comment
Months reporting
Minimum payment due
Months since update
Date of payment
OPEN CURR ACCT CH 231 $275 1 Aug-13
Trade #1 Balance Credit limit Minimum payment
Actual payment
Date of payment
Month 0 $13,300 $25,800 $275 $1,000 Aug
Month 1 $14,680 $25,800 $280 $1,000 July
Month 2 $16,060 $25,800 $286 $1,000 June
Month 3 $17,440 $25,800 $297 $1,000 May
Month 4 $18,820 $25,800 $310 $1,000 April
Month 5 $20,200 $25,800 $330 $1,000 March
Month 6 $21,580 $25,800 $343 $1,000 February
Month 7 $22,960 $25,800 $350 $1,000 January
These historical fields allow Experian the ability to:
Compare actual payments vs. the minimum payment due
or Compare actual
payments vs. the balance
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A new view of the consumer
6 month yield:
$74
Average effective APR
16.99%
In the market?
Bankcard
BT Index (0-999)
875 BTs in last 12
months
2
Revolving trades:
4
Transacting trades:
0
Risk Index rating:
Unstable
Utilization in last 6 months:
+ 35%
Credit card bals last 6 months:
+ $8,000
Behavior
Risk Revenue
Response
Trended data allows Experian to reveal a comprehensive view of a consumer’s credit behavior to improve risk, response and profit…
Annual card spend:
$7,500
Payment behavior:
Min pay – 2%
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Payment stress
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Understanding payment behavior has always been a key metric for risk and line decisions within a portfolio
An “off us” view is now available to provide that same level of insight and value
Payment stress Viewing payment data, both currently and over time, to understand consumer risk
May 2014
VantageScore® 800
Balance $22,000
Status Good standing
Balances Min pay DUE Actual pay
Apr $22,000 $550 $2,000
Mar $26,000 $650 $3,500
Feb $20,000 $500 $12,000
Jan $28,000 $700 $8,000
Dec $35,000 $875 $6,000
Nov $45,000 $1,125 $11,000
Total $176,000 $ 42,000
Balances Min pay DUE Actual pay
Apr $22,000 $550 $550
Mar $19,000 $475 $475
Feb $16,000 $400 $400
Jan $15,000 $375 $400
Dec $11,500 $288 $320
Nov $9,000 $225 $300
$92,500 $ 2,645
Consumer A Consumer B
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Experian stores historical payments, balances and requested payment data at the trade level
The data enables a detailed view of changes in pay rates and debt burdens that are not captured in credit scores, providing a unique profile of a consumer
Payment stress Viewing payment data, both currently and over time, to understand consumer risk
May 2014
VantageScore® 800
Balance $22,000
Status Good standing
Balances Min pay DUE Actual pay
Apr $22,000 $550 $2,000
Mar $26,000 $650 $3,500
Feb $20,000 $500 $12,000
Jan $28,000 $700 $8,000
Dec $35,000 $875 $6,000
Nov $45,000 $1,125 $11,000
Consumer A Paying well over minimum
payments
Demonstrated ability to pay
No stress
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Payment stress Viewing payment data, both currently and over time, to understand consumer risk
May 2014
VantageScore® 800
Balance $22,000
Status Good standing
Balances Min pay DUE Actual pay
Apr $22,000 $550 $550
Mar $19,000 $475 $475
Feb $16,000 $400 $400
Jan $15,000 $375 $400
Dec $11,500 $288 $320
Nov $9,000 $225 $300
Consumer B
Making minimum payments for the last three months
Payment amounts vs. minimum due is decreasing over time
Payment stress
Experian stores historical payments, balances and requested payment data at the trade level
The data enables a detailed view of changes in pay rates and debt burdens that are not captured in credit scores, providing a unique profile of a consumer
10 © 2014 Experian Information Solutions, Inc. All rights reserved. Experian Public.
Spend and risk
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Risk flattens after >$5 thousand in spend while income continues to increase
Experian Total Annual Plastic Spend (TAPS)SM Bin
Spend is orthogonal to risk
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Spend opportunity is correlated with credit risk
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
501-600 601-700 701-800 801-900 901-990
Low spend (<$25k/year, 100%=$659B)
Medium spend ($25k-65k/year, 100%=$653B)
High spend ($65k+/year, 100%=$653B)
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Low spenders making minimum payments have elevated risk levels
0.00
0.02
0.04
0.06
0.08
0.10
0.12
Bads are concentrated in
Low pay rates and
Low spend
Spend
$100K+
$50K–$100K
$25K–$50K
$10K–$25K
$5K–$10K
$1–$5K
Goods are concentrated in
High spend with high pay rate and
Low spend with higher pay rate
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Payments analysis
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Created a metric to capture aggregate six month credit card payments vs. the balances on those trades
Creating a payment metric
Balances Min pay DUE Actual pay
Apr $22,000 $550 $2,000
Mar $26,000 $650 $3,500
Feb $20,000 $500 $12,000
Jan $28,000 $700 $8,000
Dec $35,000 $875 $6,000
Nov $45,000 $1,125 $11,000
Balances Min pay DUE Actual pay
Apr $22,000 $550 $550
Mar $19,000 $475 $475
Feb $16,000 $400 $400
Jan $15,000 $375 $400
Dec $11,500 $288 $320
Nov $9,000 $225 $300
23% pay rate 2.8% pay rate
A single month is ineffective to capture meaningful behavior
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Analysis population
Percentage of payments vs. balances
on credit cards over last six months
16 million random sample
6.4 million Calculated pay rate
metric
1.4 million $0 balances
7.8 million Historical balance data
3.2 million No historical credit card
trades
11 million VantageScore® scorable
5 million No hits or
unscorable
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Pay rate discriminates risk within VantageScore® bands
0.00%
2.00%
4.00%
6.00%
8.00%
10.00%
12.00%
14.00%
16.00%
Pay rate
90 D
PD
on
an
y t
rad
e
VantageScore® 650–700
0%–2.3%
2.3%–4.2%
4.2%–8.9%
8.9%–20.1%
20.1%–40.2%
40.2%–66.3%
66.3%–86.5%
86.5%–100%
> 100%
Min payers
Transactors
Pay rate
Lower pay rates have 3x more incidence of 90DPD than
higher pay rate segments over the next 18 months
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650
660
670
680
690
700
Vantage
VantageScore® 650–700
0%–2.3%
2.3%–4.2%
4.2%–8.9%
8.9%–20.1%
20.1%–40.2%
40.2%–66.3%
66.3%–86.5%
86.5%–100%
> 100%
The difference in performance is not detected in traditional credit scores
Min payers Transactors
Pay rate
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0.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
Pay rate
90 D
PD
on
an
y t
rad
e
701–750 VantageScore®
0%–2.3%
2.3%–4.2%
4.2%–8.9%
8.9%–20.1%
20.1%–40.2%
40.2%–66.3%
66.3%–86.5%
86.5%–100%
> 100%
Pay rate discriminates risk within VantageScore® bands
Pay rate
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700
710
720
730
740
750
Vantage
VantageScore® 701–750
0%–2.3%
2.3%–4.2%
4.2%–8.9%
8.9%–20.1%
20.1%–40.2%
40.2%–66.3%
66.3%–86.5%
86.5%–100%
> 100%
VantageScore® does not differentiate pay rates
Min payers Transactors
Pay rate
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14.3%
12.5% 11.4%
9.5% 9.5%
7.4% 6.4%
4.8% 3.9%
90
DP
D o
n a
ny t
rad
e
650–700 VantageScore®
Lower VantageScore® segments with high pay rates have better performance than many segments with higher VantageScore®
9.6% 9.1%
7.4%
6.1% 5.2%
4.1% 3.3%
2.5% 2.0%
701–750 VantageScore®
0%–2.3% 2.3%–4.2% 4.2%–8.9%
8.9%–20.1% 20.1%–40.2% 40.2%–66.3%
66.3%–86.5% 86.5%–100% > 100%
6.5% 6.2%
4.9%
3.7% 3.2%
2.5% 1.9%
1.4% 1.2%
90
DP
D o
n a
ny t
rad
e
751–800 VantageScore®
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6.8 million consumers would swap positions within VantageScore® segments based on pay rates
0.8
1.8
1.6
1.1
0.8
0.4
0.2
0.4 0.3
Co
ns
um
ers
(m
m)
650–700 VantageScore®
0.9
2.0
1.7
1.3
1.0
0.6 0.4
0.8 0.6
701–750 VantageScore®
0%–2.3% 2.3%–4.2% 4.2%–8.9%
8.9%–20.1% 20.1%–40.2% 40.2%–66.3%
66.3%–86.5% 86.5%–100% > 100%
0.8
1.5 1.4
1.2
1.0
0.7
0.5
1.2
0.9
Co
ns
um
ers
(m
m)
751–800 VantageScore®
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4.5 million consumers swap out at a 2% 90DPD threshold on mortgage trades
4.1 3.3% 3.4%
3.1% 2.7%
3.0% 2.8%
2.0% 1.9%
Volume
90
DP
D o
n m
ort
ga
ge
651–700 VantageScore®
2.7% 2.9%
2.7%
2.3% 2.2% 2.0%
1.8% 1.6%
1.4%
Volume
90
DP
D o
n m
ort
ga
ge
701–750 VantageScore®
2.1% 2.0%
1.7%
1.4% 1.3% 1.3%
0.8% 0.9% 0.7%
751–800 VantageScore®
0% - 2.3% 2.3% - 4.2% 4.2% - 8.9%
8.9% - 20.1% 20.1% - 40.2% 40.2% - 66.3%
66.3% - 86.5% 86.5% - 100% > 100%
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8 million prospects would swap positions at a 2.95% delinquency threshold on credit cards
10.3%
8.5% 7.3%
5.8% 4.9%
4.1% 3.5%
2.4% 1.7%
Volume
651–700 VantageScore®
6.7%
5.8%
4.3%
3.4% 2.9%
2.2% 1.6%
1.1% 0.9%
Volume
710–750 VantageScore®
4.3% 4.0%
2.8%
2.0%
1.5% 1.1%
0.9% 0.7%
0.5%
Volume
751–800 VantageScore® 2.8% 2.7%
1.8%
1.2%
0.8% 0.6%
0.4% 0.4% 0.3%
Volume
801–850 VantageScore®
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Identifying risk before scores change
Payment behavior will serve as a leading
indicator of risk – identifying accounts that will
go delinquent before utilization spikes, before score
changes and before a consumer goes delinquent
Delinquency Score
decrease High
utilization Payment behavior
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Optimizing line to
capture spend and
limit risk
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Payments – the value proposition:
5%–10% of the population shifts VantageScore® segments based on payments:
► Acquire same number of consumers and have lower loss rates
► Acquire more consumers and have the same loss rates
► Improve $$ loss rates by shifting line to high spending, higher pay rate consumers
Understanding payment behavior provides an opportunity to substantially improve loss rates
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Line optimization example:
Average line at 850 VantageScore® is $15,000
► Loss rates are .2%
Identify same number of accounts at .1 loss rates
► Increase lines to $20,000–$25,000
Identify segments in the 850 VantageScore® segment who would have losses greater than .2%
► Shift line down to $5,000–$10,000
Understanding payment behavior provides an opportunity to substantially improve loss rates
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0
100
200
300
400
500
<$5K $5K–$10K $10K–$25K $25K–$50K $50K–$100K > $100K
Acco
un
t valu
e
Annual spend
Interest Fees Interchange
Optimizing line within the right segments of spend and risk will improve profitability
Higher spending consumers contribute more profit from both interchange and interest revenue
Profit contribution and VantageScore® by spend bin
Credit Limits > $20K
30% less
profit
807 796 789 774 785 762
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