© 2019 fair isaac corporation. confidential. this ... scores throug… · only and cannot be...

© 2019 Fair Isaac Corporation. Confidential. This presentation is provided for the recipient

only and cannot be reproduced or shared without Fair Isaac Corporation’s express consent. 1

© 2019 Fair Isaac Corporation. Confidential.

This presentation is provided for the recipient only and cannot be reproduced or shared without Fair Isaac Corporation’s express consent.



© 2019 Fair Isaac Corporation. Confidential.

This presentation is provided for the recipient only and cannot be reproduced or shared without Fair Isaac Corporation’s express consent.

Through the Cycle FICO® Score Trends

And What They Tell Us About the Road Ahead

Ethan Dornhelm

VP – Scores and Predictive Analytics, FICO





“Sometimes the future is like the past,And sometimes it is not.But when it comes to what we know,The past is all we’ve got.”

– Karl Case



• What is Driving Shifts in the

FICO Score Distribution?

• What is Driving Shifts in the

Odds-to-Score relationship?

Key FICO® Score Through-the-Cycle Questions



National Average FICO® Score 8 Has Steadily Risen Over Past Decade



FICO Scorable Population Shows Improvement in Key Credit Metrics Over Past Decade

Credit Dimension

Credit MetricAs of:

Relative % Difference

Apr-09 Apr-19 2009 - 2019

Payment History % of population 30+ Days Past Due in Last Year 25.2 19.7 -22%

Payment History% of population 90+ Days Past Due on Auto Finance

Loans in Last 2 Years6.5 5.6 -14%

Payment History% of population 90+ Days Past Due on Bankcards in Last 2

Years12.9 8.6 -33%

Payment History% of population 90+ Days Past Due on Real Estate Loans

in Last 2 Years7.2 2.8 -61%

Amounts Owed Average Credit Card Utilization 46.4 33.5 -28%

Amounts Owed Average Credit Card Balances $6,947 $6,595 -5%

Length of Credit History

Average age of oldest trade 204 222 9%

New Credit % of population with 1+ inquiries in the past year 47.8 41.0 -14%



FICO Scorable Population Shows Improvement in Key Credit Metrics Over Past Decade

But Also Deterioration in Several Metrics Between 2014-2019

Credit Dimension

Credit MetricAs of:

Relative % Difference

Apr-09 Apr-14 Apr-19 2009 - 2019

Payment History % of population 30+ Days Past Due in Last Year 25.2 20.9 19.7 -22%

Payment History% of population 90+ Days Past Due on Auto Finance

Loans in Last 2 Years6.5 4.5 5.6 -14%

Payment History% of population 90+ Days Past Due on Bankcards in

Last 2 Years12.9 7.3 8.6 -33%

Payment History% of population 90+ Days Past Due on Real Estate

Loans in Last 2 Years7.2 6.4 2.8 -61%

Amounts Owed Average Credit Card Utilization 46.4 38.7 33.5 -28%

Amounts Owed Average Credit Card Balances $6,947 $5,911 $6,595 -5%

Length of Credit History

Average age of oldest trade 204 216 222 9%

New Credit % of population with 1+ inquiries in the past year 47.8 44.0 41.0 -14%



Are Credit Inactives and/or New Entrants The Key Driver in Average FICO® Score Change Over the Past Decade?

Credit Inactives

Scorable Throughout

New Entrants/Re-Entrants

April 2009

Scorable

Scorable

Not Scorable

April 2019

Not Scorable

Scorable

Scorable



Credit Inactives*: A Tale of Two Profiles

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

18.0%

20.0%

300-499 500-549 550-599 600-649 650-699 700-749 750-799 800-850

FICO® Score 8 Distribution April 2009

Scorable as of 2009, Credit Inactive as of 2019 Total U.S. Population

Sizing: ~40M consumer files

Average FICO® Score 8: 660

Voluntary vs Involuntary Inactives

*As of 2019, no updated credit account(s) in past 6 months



0%

5%

10%

15%

20%

25%

300-499 500-549 550-599 600-649 650-699 700-749 750-799 800-850

FICO® Score 8 Distribution April 2019

Unscorable as of 2009, Scorable as of 2019 Total U.S. Population

New Entrants/Re-Entrants Skew Lower Than National Population


Average FICO® Score 8: 657

Median Age as of April 2019 = 27



0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

300-499 500-549 550-599 600-649 650-699 700-749 750-799 800-850

FICO® Score 8 Distribution On Files Scorable in Both 2009 and 2019

April 2009 April 2019

Scoreable Throughout: Key Population Driving Score Distribution Upwards


Average FICO® Score 8 (2009): 694

Average FICO® Score 8 (2019): 723

29 Point Increase in Avg FICO Over Past Decade



• National Consumer Assistance Plan

(NCAP)

• FCRA-mandated Delinquency Purge

Impact of Deleted Negative Credit Data on FICO® Scores



National Consumer Assistance Plan (NCAP) and Impact on FICO®

Score

NCAP requires a minimum set of personally-identifiable

information (PII) on public records

• Impacted civil judgments and tax liens; no impact to bankrupt

public records

• Criteria initially implemented at all three CRAs by July 2017

• By mid-2018, all civil judgments and tax liens had been purged by

the three CRAs



NCAP Public Record Study Findings

No observed material impact to FICO® Score on the

total population

• Score distributions, risk prediction & odds-to-score

relationship unaffected

Modest impact to FICO® Score on the ~6% of the total FICO

scorable population that had a judgment or tax lien purged from

their file as a result of the NCAP criteria

• Median pre-NCAP FICO® Score 8 for this population is

562



Observed No Material Impact to FICO® Score 8 Cumulative Distribution

0

10

20

30

40

50

60

70

80

90

100

250 -499

500 -519

520 -539

540 -559

560 -579

580 -599

600 -619

620 -639

640 -659

660 -679

680 -699

700 -719

720 -739

740 -759

760 -779

780 -799

800 -819

820 -839

840 -900

Cu

mu

lative

Pe

rce

nt

Score

FICO® Score 8 PreNCAP FICO® Score 8 PostNCAP



Few Consumers Swap Above Cut-offs as a Result of NCAP

For cutoffs across the score spectrum, less than 0.25% of credit files are swapping above when comparing the Pre- and Post-NCAP scores

FICO® Score 8 Pre-NCAP

Above Cutoff Below Cutoff% Swapped Above with FICO® Score 8

Post-NCAP

580 83.4% 16.6% 0.21%

620 75.4% 24.6% 0.18%

660 66.5% 33.5% 0.22%

700 56.7% 43.3% 0.23%

740 44.7% 55.3% 0.18%



Bad Rates in Bankcard Originations Higher for NCAP-Impacted Population

Not Impacted

FICO® Score 8 Post-NCAP

% of New Bankcard Pop

90+ Bad Rate

< 500 1% 43.3%

500-519 1% 38.4%

520-539 1% 36.5%

540-559 2% 34.1%

560-579 3% 31.2%

580-599 3% 27.0%

600-619 4% 20.4%

620-639 5% 14.4%

640-659 6% 10.2%

660-679 7% 7.1%

680-699 8% 5.2%

700-719 8% 3.6%

720-739 8% 2.3%

740-759 8% 1.5%

760-779 8% 0.9%

780-799 8% 0.5%

800+ 20% 0.2%

Grand Total 100% 7.1%



Bad Rates in Bankcard Originations Higher for NCAP-Impacted Population

Not Impacted Impacted

FICO® Score 8

Post-NCAP% of New

Bankcard Pop90+ Bad Rate % of New

Bankcard Pop90+ Bad Rate % Increase in

Bad Rate

< 500 1% 43.3% 5% 48.0% 11%

500-519 1% 38.4% 4% 41.0% 7%

520-539 1% 36.5% 6% 38.4% 5%

540-559 2% 34.1% 9% 37.1% 9%

560-579 3% 31.2% 11% 34.5% 11%

580-599 3% 27.0% 12% 29.1% 8%

600-619 4% 20.4% 12% 22.8% 12%

620-639 5% 14.4% 11% 15.4% 7%

640-659 6% 10.2% 9% 11.2% 9%

660-679 7% 7.1% 7% 7.9% 11%

680-699 8% 5.2% 5% 6.2% 19%

700-719 8% 3.6% 3% 5.1% 44%

720-739 8% 2.3% 2% 3.8% 67%

740-759 8% 1.5% 2% 2.8% 91%

760-779 8% 0.9% 1% 2.2% 157%

780-799 8% 0.5% 1% 1.1% 137%

800+ 20% 0.2% 1% 0.9% 376%

Grand Total 100% 7.1% 100% 23.4%

Particularly

for those

with Prime

“Post-NCAP”

Scores



41.3%

16.5%

13.5%

11.1%9.2% 8.6% 8.1%

4.4%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

40.0%

45.0%

0-11 12-23 24-35 36-47 48-59 60-71 72-83 No Delinquency

Bad R

ate

(B

ad =

90+

dp

din

subsequent

24 m

onth

s)

# of Months Since Most Recent Delinquency*

*Delinquency = 30+ days past due

Years-Old Delinquency Data Still Materially Differentiates Risk

FCRA: Trade line delinquencies must be purged from file after 7 years



Study: FICO® Score Dynamics of Great Recession-Era Delinquent Consumers

FICO® Score 8 dynamics examined over time on three populations

2017

Recession-era missed payments purged per FCRA

Population #2:

“Fully Recovered”• ~4 million consumers

• Subset of Population #1

• No derogatory information

still on file as of April 2017

Population #1:

“Recession Delinquency”• ~28 million consumers

• 1+ serious (90+ dpd) delinquency

Population #3:

Total Population• All FICO® Scorable U.S.

Consumers

2009/2010

Recession era



Delinquency Aging Drives Score Increases for “Recession Delinquency” Pop

FICO® Score 8 Distribution – Recession Delinquency Population

0

10

20

30

40

50

60

70

80

90

100

300 -499

500 -519

520 -539

540 -559

560 -579

580 -599

600 -619

620 -639

640 -659

660 -679

680 -699

700 -719

720 -739

740 -759

760 -779

780 -799

800 -850

Cum

ula

tive P

erc

ent

FICO® Score 8

April 2011 April 2013 April 2015 April 2017 April 2019



Even More Substantial Score Increases for “Fully Recovered” Population

FICO® Score 8 Distribution – “Fully Recovered” Population

0

10

20

30

40

50

60

70

80

90

100

300 -499

500 -519

520 -539

540 -559

560 -579

580 -599

600 -619

620 -639

640 -659

660 -679

680 -699

700 -719

720 -739

740 -759

760 -779

780 -799

800 -850

Cum

ula

tive P

erc

ent

FICO® Score 8

April 2011 April 2013 April 2015 April 2017 April 2019

Especially between 2015 and 2017 when recession-related delinquencies were purged



Odds-to-Score Alignment Consistent Prior to the 7-year Purge Mark

Repayment Odds Across All Credit Accounts, April 2015-2017

0.1

1

10

100

1000

480 530 580 630 680 730 780

Odds (

bads

= 9

0+

dpd

over

24 m

onth

s)

FICO® Score 8 Recession Delq Total Population



Misalignment After Purge for the “Fully Recovered” Population

Repayment Odds Across All Credit Accounts, April 2017-2019

0.1

1

10

100

1000

480 530 580 630 680 730 780

Od

ds (

bad

s =

90+

dpd

ove

r 2

4 m

onth

s)

FICO® Score 8

Recession Delq Recession Delq - Fully Recovered Total Population



FICO® Score Distribution Shifts Through the Cycle:

Key Takeaways and Opportunities

Consumer credit profiles

stronger across all key

FICO® Score drivers

relative to a decade ago,

driving 20 point uptick in

avg FICO Score.

Several subpopulations

with relatively clean

credit files now are

materially riskier than

their FICO Score

cohorts:

Opportunity

• NCAP Impacted and

680+ FICO Score: ~2M

consumers

• FCRA (Recession Delq

and ‘Fully Recovered’):

~4M consumers

Through additional data

sources or profiling

analyses, identify

consumers that struggled

in past downturn

or that fit profile of those

that did, as they may

struggle again in the next

downturn.



Shifts in the Odds-to-Score Relationship Through the Cycle



620640

660

680

FICO® Scores are Designed to Rank-Order Credit Risk

* FICO® Industry Scores have a broader score range

Paid-as-agreed borrower

Delinquent borrower



Odds-To-Score Relationship Can/Does Shift Through the Cycle

550 600 650 700 750 800

Odds (

bads

= 9

0+

dpd

over

24 m

onth

s)

FICO® Score

Normal Economy Recession



Downward Shift In Odds-To-Score for Bankcard Originations Since ~2014

1.0

10.0

100.0

1000.0

550 600 650 700 750 800

Od

ds (

ba

ds

= 9

0+

dp

do

ve

r 2

4 m

on

ths)

FICO® Score 8

Odds-to-Score on New Bankcards

Oct 2007 - Oct 2009 Oct 2013 - Oct 2015

Oct 2015 - Oct 2017 Apr 2017 - Apr 2019



Downward Shift In Odds-To-Score for Auto Originations Since ~2013

1.0

10.0

100.0

1000.0

550 600 650 700 750 800

Od

ds (

ba

ds =

90

+ d

pd

ove

r 2

4 m

on

ths)

FICO® Score 8

Odds-to-Score on New Auto Loans

Oct 2007 - Oct 2009 Oct 2013 - Oct 2015Oct 2015 - Oct 2017 Apr 2017 - Apr 2019



0.1

1.0

10.0

100.0

1000.0

550 600 650 700 750 800

Od

ds (

ba

ds

= 9

0+

dp

do

ve

r 2

4 m

on

ths)

FICO® Score 8

Odds-to-Score on New Mortgages

Oct 2007 - Oct 2009 Oct 2013 - Oct 2015Oct 2015 - Oct 2017 Apr 2017 - Apr 2019

Downward Shift In Odds-To-Score for Mortgage Originations Since ~2016



• No ‘silver bullet’!

• FICO odds-to-score has shifted similarly

for key credit subsegments: thick/clean,

thin/new-to-credit/clean, and subprime

• Other theories tested, without compelling

conclusions:

• Regional drivers

• Age-based drivers

• High levels of product-specific

(e.g. student loan) debt

What is Driving the Downward Shift in Odds-to-Score ?



• Investigated differences in credit profile of consumers that

opened a bankcard in the following two originations windows:

• May 2013-July 2013

• May 2017-July 2017

• Built classification model to predict whether a given credit file

was from the 2013 or 2017 origination vintage

• Built separate models for different score bands to control for

FICO® Score:

• 595-605

• 635-645

• 675-685

• 750-770

Profiling 2013 vs. 2017 Bankcard Vintages



Notable shift towards consumers with less bankcard experience in 2017 vintage

Distribution of average months in file on bankcards as time of origination, for consumers with FICO® Score 8 = 595-605

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

18.0%

% o

f B

an

kca

rd O

rig

ina

tio

ns C

on

su

me

rs

Average Months in File - Bankcard

Apr-13 Apr-17



Less Bankcard Experience Means Higher Repayment Risk

Subsequent bankcard originations bad rates, for consumers with FICO® Score 8 = 595-605

15.0%

20.0%

25.0%

30.0%

35.0%

40.0%

45.0%

50.0%

Ba

d R

ate

(B

ad

= 9

0+

dp

din

su

bse

qu

en

t 2

4 m

on

ths)

Average Months in File Bankcard

Apr-17



• Aimed at quantifying the prevalence of credit card debt

consolidation behavior and resultant impact on FICO® Scores

• Conducted analysis on a nationally representative,

longitudinal sample of 10+ million consumers

• Focused on consumers who consolidated debt during the

period Oct 2015 - April 2016

Credit Card Debt Consolidation Research

Background and Methodology



• No readily used/available field in the credit file to identify debt

consolidation loans

• As a result, it was necessary to define a proxy for debt

consolidator behavior

• ~0.5% of total FICO scorable population met the proxy ‘debt consolidator’ definition used for this study:

• Installment (non-auto/mortgage/student) loan opened in

six-month period between October 2015 and April 2016

• Reduction in revolving accounts with high utilization over

the same six-month period

Credit Card Debt Consolidation Research

Background and Methodology Continued



On Average, 24 Point Increase in Score Post-Debt Consolidation

Contrast to +3 Points for National Population

Average MetricDebt Consolidators Total U.S. Population

Oct-15 Apr-16 Oct-15 Apr-16

FICO® Score 8 651 676 702 704

Revolving Utilization 68% 40% 35% 34%

Credit Card Balances $9,736 $6,262 $5,744 $5,756

Highest Credit Card Utilization 104% 75% 51% 50%

Total IL Balances $28,528 $30,513 $23,353 $23,756

Total Tradeline Balances $108,920 $112,251 $87,481 $88,976



Initial Score Increase Experienced By Consolidators Regresses Some

Over Subsequent Year, Likely Driven By Re-leveraging on Credit Cards

Average MetricDebt Consolidators Total U.S. Population

Oct-15 Apr-16 Jul-16 Oct-16 Apr-17 Oct-15 Apr-16 Jul-16 Oct-16 Apr-17

FICO® Score 8 651 676 672 667 666 702 704 705 705 706

Revolving Utilization 68% 40% 45% 48% 50% 35% 34% 34% 34% 33%

Credit Card Balances

$9,736 $6,262 $7,329 $8,336 $9,295 $5,744 $5,756 $5,803 $5,931 $5,984

Highest Credit Card Utilization

104% 75% 82% 85% 86% 51% 50% 51% 51% 50%

Total IL Balances $28,528 $30,513 $31,134 $31,420 $31,445 $23,353 $23,756 $24,091 $24,352 $24,696

Total Tradeline Balances

$108,920 $112,251 $114,025 $115,145 $119,390 $87,481 $88,976 $89,328 $89,152 $92,167



Consolidator Population Gives Back Some of the Score Gains

Over Subsequent Year, Particularly in the Lower Score Range

0

10

20

30

40

50

60

70

80

90

100

300 -499

500 -519

520 -539

540 -559

560 -579

580 -599

600 -619

620 -639

640 -659

660 -679

680 -699

700 -719

720 -739

740 -759

760 -779

780 -799

800 -819

820 -840

Cum

ula

tive P

erc

ent

FICO® Score 8

Oct 2015 Apr 2016 Jul 2016 Oct 2016 Apr 2017



Debt Consolidators Riskier Relative to National PopulationMeasured on 24 Month, “All Industries/All Accounts” Outcome (bad = 90+ dpd)

1

10

100

1000

530 580 630 680 730 780

Odd

s

FICO® Score 8

National Population 'Debt Consolidators'Total Population



Coming out of Great Recession, Time to Default on Bankcards Exhibited Intuitive PatternTime to Default (in First Four Years on Books) Cleanly Rank Ordered By FICO Score

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

<6 6-8 9-11 12-14 15-17 18-20 21-23 24-26 27-29 30-32 33-35 36-38 39-41 42-44 45-47

Perc

ent

of

Defa

ults

Time To Default (in months)

Bankcard Accounts Opened May 2009-April 2010Time to Default, by FICO Score Band

[500,549] [550,599] [600,649] [650,699] [700,749] [750,799] [800,850]FICO® Score Band



Defaults on 2014-2015 Vintages Occurring Sooner After Account Opening

Particularly for those with Scores of 800+

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

<6 6-8 9-11 12-14 15-17 18-20 21-23 24-26 27-29 30-32 33-35 36-38 39-41 42-44 45-47

Perc

ent

of

De

faults

Time To Default (in months)

Bankcard Accounts Opened May 2014-April 2015Time to Default, by FICO Score Band

[500,549] [550,599] [600,649] [650,699] [700,749] [750,799] [800,850]FICO® Score Band



• Just as upward shift in score distribution over time not driven by a single factor, so too

with the downward trend in odds-to-score

• Downward shift in originations odds-to-score likely a product of a number of factors,

impacting different points along the FICO Score spectrum, including:

Odds-to-Score Shifts Through the Cycle: Key Takeaways

Low Scores

Increased underwriting

of less credit experienced

consumers

High Scores

NCAP-related deletions,

debt consolidators,

application fraud

Mid-range Scores

Purging of delinquencies

from Great Recession,

shifts to riskier product

terms, debt consolidators

300 850



Reactive: Identify and quantify degree of exposure to segments

already showing notable odds-to-score deterioration

• Refine portfolio management strategies and loss forecasting

accordingly

Proactive: Identify consumers who—controlling for

FICO® Score—are most likely to be sensitive to a downturn

• Attend Gerald Fahner and George Shand’s upcoming

session!

Odds-to-Score Shifts Through the Cycle: Opportunities in the face of a potential downturn



Learn More

Topic

Related Sessions

• Next Recession Prepping: Adjusting US FICO® Scores for

Consumer Economic Sensitivity

• Tues. Nov. 5th at 4:30 pm

• Room - Sutton Beekman

Solution Center • Scoring Strategies

Experts Here

• Gerald Fahner

• George Shand

• Dave Shellenberger

• Sharon Tilley

FICO Blog • Coming soon!


only and cannot be reproduced or shared without Fair Isaac Corporation’s express consent. 47© 2019 Fair Isaac Corporation. Confidential. 47

Tell us how we did!

Before you leave, please take

a couple of minutes to take our

session survey found in the

FICO World app in the session

details.



Thank You!

Ethan Dornhelm

[email protected]



Unsecured Installment Loan Originations – Repayment Odds Below 2006-2008 Period

1.0

10.0

100.0

450 500 550 600 650 700 750 800

Od

ds (

bads

= 9

0+

dpd

ove

r 2

4 m

onth

s)

FICO® Score 8

Odds-to-Score on New Unsecured ILs

Oct 2006 - Oct 2008 Oct 2010 - Oct 2012 Oct 2014 - Oct 2016 Oct 2016 - Oct 2018



Degree of Odds-to-Score Shift Can Vary Based on Factors Outside of FICO® Score

1.0

10.0

100.0

1000.0

550 570 590 610 630 650 670 690 710 730 750

Odds (

bads

= 9

0+

dpd

over

24 m

onth

s)

FICO® Auto Score 8

Odds-to-Score on New Auto Loans

Oct 2012, Terms = 36-59 months Oct 2012, Terms = 72-83 months

Oct 2016, Terms = 36-59 months Oct 2016, Terms = 72-83 months



Similar Regression in Score Observed on Consolidator Population That Subsequently Opened a New Bankcard*

0

10

20

30

40

50

60

70

80

90

100

300 -499

500 -519

520 -539

540 -559

560 -579

580 -599

600 -619

620 -639

640 -659

660 -679

680 -699

700 -719

720 -739

740 -759

760 -779

780 -799

800 -819

820 -840

Cum

ula

tive P

erc

ent

FICO® Score 8

Oct 2015 Apr 2016 Jul 2016 Oct 2016 Apr 2017* In 3 months following consolidation

© 2019 fair isaac corporation. confidential. this ... scores throug… · only and cannot be...

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