vision 2014: expand your consumer universe and improve profitability

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Expand your consumer universe and improve profitability

Paul DeSaulniers Experian

Kelley Motley Experian

#vision2014

2 © 2014 Experian Information Solutions, Inc. All rights reserved. Experian Public.

The recent financial crisis has reshaped the lending environment.

Focus on model governance to ensure mandated regulatory compliance

New emphasis on consumer education, model transparency, and inclusive lending practices

Importance of controlled growth that balances expansion with risk mitigation

Need for agile and flexible operational processes without single-threaded dependencies

Now is the time to challenge your consumer risk score.

1. Is your model geared to support expanding regulatory compliance?

2. Are you able to meet the growing demands for consumer transparency and education?

3. Does your model deliver superior and stable predictive power in the current economic and business environment?

4. Are you mitigating operational risks which can cause major disruptions in your business?

5. Are you partnering with a data and analytics expert who understands how to leverage the full power of traditional and emerging credit data to increase predictiveness?

Today’s reality


Greater prediction through the use of enhanced data elements and more granular data

Increased coverage by scoring 30-35 million more consumers over a traditional risk score

Easy-to-implement with a familiar industry recognized score range

More consistent results of the score across all three credit reporting companies

Optimized for origination and account management uses

Stable model for consistent results across timeframes

VantageScore® 3.0 Highlights


VantageScore® 3.0 Performance metrics

VantageScore® 3.0

KS in the high 50’s and 60’s

GINI’s into the 80’s

Captures over 75% of all bads in the lowest

scoring 20%

More accurately classifies consumers who may

be inaccurately categorized as subprime

► An Experian study shows 2.5 million

consumers being reclassified from subprime

into higher score intervals

Lift in 90+ DPD captured at 20% – overall

64.7%

62.6%

VantageScore® 3.0 Scorex PLUS

75.7%

69.8%

5.9 %

Lift over

Scorex PLUS

Statistics Overall Bankcard Mortgage Auto

KS 63.4 65.7 61.7 59.5

GINI 79.2 81.3 77.8 75.4

Bads captured

in lowest 20% 75.8% 80.8% 75.3% 72.3%

CRC = Credit Reporting Companies


VantageScore® 3.0 Universe expansion

U.S. consumers (millions)

Scoreable Universe

VantageScore® 3.0 newly scored

Legacy models *

170

35

VantageScore® 3.0 includes traditionally excluded consumers:

► Infrequent credit users

► New entrants

► No recent activity

► No open trades

VantageScore® 3.0 scores 30–35 million

more consumers over conventional models

*= Based to published exclusion criteria


VantageScore® 3.0 utilizes familiar 300–850 scale

Scaled to accommodate existing systems

Research was conducted with both lenders and consumers, with each audience indicating a preference for the 300–850 scale

While lenders individually determine their own credit quality cutoffs, the credit tier breakdown below is offered only as an approximation:

► 781–850 Super prime

► 661–780 Prime

► 601–660 Non-prime

► 500–600 Subprime

► 300–499 Deep subprime

VantageScore® 3.0 Score ranges

Prime: 661 and above

Non-prime: Below 660


Population distribution of scoreable consumers

5%

27%

13%

34%

21%

0%

5%

10%

15%

20%

25%

30%

35%

40%

300-499 500-600 601-660 661-780 781-850

VantageScore® 3.0 population distribution

Implementing a 631 score cut, the interval bad rate is <8%,

encompassing 62% of the population


All numeric adverse action codes; fewer than 80 definitions

Adverse action codes rewritten to be more consumer-friendly and understandable

► Clear understanding of what impacts a consumer’s VantageScore® credit score

► ReasonCode.org website is an educational resource for consumers

VantageScore® 3.0 Easier to adopt adverse action codes


Expand your consumer

universe and improve

profitability with

VantageScore® 3.0


Analytical objective

To answer the following: How many applicant records can be scored using VantageScore® 3.0, where my traditional model was not able to provide a valid score?

► Who are these consumers?

► How do these new consumers perform?

► How many of these consumers can I approve given my current approval criteria?

VantageScore® 3.0 Analysis overview


Analysis overview

Review of existing and new consumer accounts

► Retail new account acquisition

► Bankcard existing account portfolio management

VantageScore® 3.0 Analysis overview


Model performance

Performance

definitions

Bad

Consumers 90+ days

delinquent or worse

Good

Consumers current or 30

days delinquent (<60 DPD)

Indeterminate

Consumers 60 days

delinquent (<90 DPD)

Dec 2011 Observation date

Dec 2013

24-month performance window

Performance

Existing account management

Dec 2011

Date opened

Jan. – Mar.

Dec 2013

21- to 23-month performance window

Performance

New account acquisition

Observation date


Bankcard – existing account management Scoring totals

99.33% scoreable using

VantageScore® 3.0 as compared

to 98.36% scoreable using a

competitive score

Sample: National

randomly selected –

6,524,894 records

VantageScore® 3.0

Total

6,481,377

Good

5,956,009

Bad

431,869

Indeterminate

93,499

Competing risk score

Total

6,417,611

Good

5,898,930

Bad

426,075

Indeterminate

92,606


Let’s first look at the population scoreable by both models

Bankcard – existing account management Accounts scored by both models

VantageScore® 3.0

Total

6,481,377


Total

6,417,611

Scoreable by both models

Total

6,417,584

Good

5,898,910

Bad

426,070

Indeterminate

92,604


Bankcard – existing account management KS comparison Accounts scored by both models

62.67

59.19

55

60

65

KS

sta

tisti

c

VantageScore® 3.0


Vantage Score® 3.0 shows better separation

of good and bad accounts (higher KS)


Bankcard – existing account management Cumulative bad lift chart Accounts scored by both models

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Cu

mu

lati

ve %

of

bad

acco

un

ts

Cumulative % of accounts

VantageScore® 3.0 Competing risk score Baseline

VS3 KS:

62.67

Other KS:

59.19


Bankcard – existing account management Percent bad capture Accounts scored by both models

The ability of a model to

push the largest percent of

bads to the lowest scoring

ranges is a hallmark of

scorecard performance.

55.4%

76.4%

87.1%

51.1%

72.8%

84.4%

40%

50%

60%

70%

80%

90%

100%

10% 20% 30%

% b

ad

acco

un

ts

Worst scoring

VantageScore® 3.0 Competitive score


Bankcard – existing account management Rank ordering Accounts scored by both models

0%

10%

20%

30%

40%

50%

60%

5% 25% 45% 65% 85%

Inte

rval

bad

rate

VantageScore® 3.0 Competing risk score

Overall bad rate: 6.64%

Bad rate should steadily increase as you move into lower scoring

intervals, creating a smooth, monotonic progression. This is a measure

of model performance, as well as scorecard stability.

Twentiles Best scoring Worst scoring


Now, let’s look at the population uniquely scoreable by VantageScore® 3.0

Bankcard – existing account management Accounts only scored by VantageScore® 3.0 (unique)

VantageScore® 3.0

Total

6,481,377


Total

6,417,611

Uniquely scoreable by VantageScore® 3.0

Total

63,793

Good

57,099

Bad

5,799

Indeterminate

895


Bankcard – existing account management Lift chart Accounts only scored by VantageScore® 3.0

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Cu

mu

lati

ve %

of

bad

acco

un

ts


VantageScore® 3.0 Baseline

KS score:

48.53


Bankcard – existing account management Percent bad capture Accounts only scored by VantageScore® 3.0

33.1%

59.9%

73.3%

0%

10%

20%

30%

40%

50%

60%

70%

80%

10% 20% 30%

% b

ad

acco

un

ts

Worst scoring

VantageScore® 3.0


push the largest percent of

bads to the lowest scoring

ranges is a hallmark of

scorecard performance.


Bankcard – existing account management Rank ordering Accounts only scored by VantageScore® 3.0

0%

10%

20%

30%

40%

50%

10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Inte

rval

bad

rate

VantageScore® 3.0

Deciles Best scoring Worst scoring






Bankcard – existing account management Comparing the consumers scoreable only by VantageScore® 3.0 to those scoreable by both models

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Scored by both models Uniquely scored by VS3



Bankcard – existing account management Comparing the consumers scoreable only by VantageScore® 3.0 to those scoreable by both models

0%

10%

20%

30%

40%

50%

60%

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Scored by both models Uniquely scored by VS3 Int. bad rate scored by both models

Int. bad rate scored by VS Overall bad rate

42% of the population, traditionally not scored, can be approved



Retail – new account origination Scoring totals

99.64% scoreable using

VantageScore® 3.0

as compared to 97.4% scoreable

using a competitive score

Sample: National

randomly selected –

410,685 records

VantageScore® 3.0

Total

409,200

Good

383,613

Bad

20,101

Indeterminate

5,486


Total

400,024

Good

375,922

Bad

18,850

Indeterminate

5,252


Let’s first look at the population scoreable by both models

Retail – new account origination Accounts scored by both models

VantageScore® 3.0

Total

409,200


Total

400,024

Scoreable by both models

Total

400,013

Good

375,917

Bad

18,846

Indeterminate

5,250


Retail – new account origination KS comparison Accounts scored by both models

52.74

50.76

45

50

55

KS

sta

tisti

c

VantageScore® 3.0


Vantage Score® 3.0 shows better separation

of good and bad accounts (higher KS)


Retail – new account origination Cumulative bad lift chart Accounts scored by both models

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Cu

mu

lati

ve %

of

bad

acco

un

ts


VantageScore® 3.0 Competing risk score Baseline

VS3 KS:

52.74

Other KS:

50.76


Retail – new account origination Percent bad capture Accounts scored by both models

43.3%

65.1%

79.6%

39.6%

62.4%

77.3%

30%

40%

50%

60%

70%

80%

90%

10% 20% 30%

% b

ad

acco

un

ts

Worst scoring

VantageScore® Competitive score

The ability of a model

to push the largest

percentage of bads

to the lowest scoring

ranges is a hallmark

of scorecard

performance.


Retail – new account origination Rank ordering Accounts scored by both models

0%

5%

10%

15%

20%

25%

30%

35%

5% 15% 25% 35% 45% 55% 65% 75% 85% 95%

Inte

rva

l b

ad

ra

te

VantageScore®3.0 Competing risk score




intervals creating a smooth, monotonic progression. This is a measure

of model performance as well as scorecard stability.


Now, let’s look at the population uniquely scoreable by VantageScore® 3.0

Retail new account origination Accounts only scored by VantageScore®

VantageScore® 3.0

Total

409,200


Total

400,024

Uniquely scoreable by VantageScore® 3.0

Total

9,187

Good

7,696

Bad

1,255

Indeterminate

236


Retail – new account origination (unique) Lift chart Accounts only scored by VantageScore®

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Cu

mu

lati

ve %

of

bad

acco

un

ts


VantageScore® 3.0 Baseline

KS score:

30.29


Retail – new account origination (unique) Percent bad capture Accounts only scored by VantageScore®

21.0%

35.8%

51.8%

0%

10%

20%

30%

40%

50%

60%

10% 20% 30%

% b

ad

acco

un

ts

Worst scoring

VantageScore®


push the largest percent

of bads to the lowest

scoring ranges is a

hallmark of scorecard

performance.


Retail – new account origination (unique) Rank ordering Accounts only scored by VantageScore® 3.0

0%

10%

20%

30%

40%

10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Inte

rval

bad

rate

VantageScore® 3.0

Deciles Best scoring Worst scoring






Retail – new account origination Comparing the consumers scoreable only by VantageScore® 3.0 to those scoreable by both models

0%

5%

10%

15%

20%

25%

30%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Scored by both models Uniquely scored by VS3



Retail – new account origination Comparing the consumers scoreable only by VantageScore® 3.0 to those scoreable by both models

0%

5%

10%

15%

20%

25%

30%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Scored by both models Uniquely scored by VS3 Int. bad rate scored by both models

Int. bad rate scored by VS Overall bad rate

5.1% of the population, traditionally

not scored, can be approved



Comparison of uniquely scored VantageScore® 3.0 records to those scored by both models

New accounts

Unique VantageScore® 3.0

consumers

Consumers scored

by both models

Age 36 years 47 years

Homeownership 31% 58%

Length of residence 8.3 years 10.3 years

Presence of children 41% 35%

Income InsightSM (Credit) $42,228 $87,705

Existing accounts

Unique VantageScore® 3.0

consumers

Consumers scored

by both models

Age 57 years 51 years

Homeownership 47% 63%

Length of residence 11.7 years 11.6 years

Presence of children 26% 31%

Income InsightSM (Credit) $46,490 $98,265


Bankcard – account management

VantageScore® 3.0 scores 1% more accounts than the competing risk score

6% lift in Kolmogorov-Smirnov (KS) performance

3.2% lift in bads captured in worst scoring 30%

Retail – account acquisition

VantageScore® 3.0 scores 2.3% more accounts than the competing risk score

3.9% lift in Kolmogorov-Smirnov (KS) performance

3.0% lift in bads captured in the worst scoring 30%

VantageScore® 3.0 vs. competing risk score Summary


For additional information, please contact:

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Economy & Finance

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timeframes vantagescore

deep subprime vantagescore

consumer risk score

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open trades vantagescore