Lender Perspectives on Credit

Reporting

Originations / Acquisitions2

Global Learning Opportunities1Originations / Acquisitions2

Account Management3

Negative,

Bureau Development Path

Demographics

Demographics

+ Criteria

Generic /

Custom

Scorecards

TimeNo bureau

Negative only

Negative + positive

Negative, positive, scorecards, non-bank data

3

Demographics

Emerging Markets Themes

• Governments interested in growing consumer economies

• Poor understanding of consumer behavior (repayment,

revenue, collections) restrains consumer opportunites &

bank growth

• Taking cues / approaches from advanced economies• Taking cues / approaches from advanced economies

• Key constraint: lack of formal economy

– Cash, barter and other styles of non-digital transaction

– Consumers avoiding tax & traceability via cash

• Countries have unique approaches, but can fall within

regional themes

4

Country Variety; Regional Themes

DevelopedPrivacy

Focused

Government /

Private

5

Private

Industry

Emerging

Private

Inside North America

• Private Bureau usage: competitive requirement– Prescreening / Marketing, Originations, Account Management

• Generic scores gamed by consumers– Consumers gaining bargaining power to lower interest rates & fees

– Increases need for custom models

• Current focus on collections, risk management• Current focus on collections, risk management– Validation discipline

– Generic odds charts vs. analysis for cutoff selection

• Longer term challenge: growing beyond the well

banked– New data vectors from alternative sources

– Cross border connections for immigrant populations

– How can we do verifications on consumer volunteered data?

6

Developing World Challenges

• Data sharing constraints by local champions (anti-competitive, anti-consumer)

• Data cost leads to lack of use

– Originations filtering

– Account management only in extreme cases

• Lack of infrastructure

– No address standardization– No address standardization

– Use of National ID (SSN, SIN) can be tricky

• Lack of Government support & understanding

– Aggregated vs. private credit information not recognized as distinct

– Need to create digital records, possibly via preferential tax treatments

• Name & account matching algorithms unique by country:

(India: V.S. Balakrishnasubramaniam; China: Lim, Im;

Latin America: Mother-Father vs. Father-Mother)

7

Emerging Market Bureaus

• All too often – negative only bureaus

– Low Hit rates, less predictive of loss, revenue, & other behaviors

– Partial, skewed, view consumer’s financial picture

– Risk management screen only, useless for finding & rewarding

responsible consumers

– Invasion of consumer privacy with no benefit to consumer

– Does not encourage consumer spending or economic growth

• Lack of understanding of bureau predictive power by banks

– Originations risk management focused on demographics

– Account management batch data: too expensive?

– Central bank regulators unaware / less aware of utility

• Too little consumer information, influence, or participation

8

Inside Asia

• India & China just getting started

–India CIBIL started 2005, now Experian, Equifax and Innovis

entering market

– Beijing and Shanghai regional bureaus, national to come?

• Japan and Korea fragmented, but fully functional

– Hard to gather complete picture of consumer’s financial picture– Hard to gather complete picture of consumer’s financial picture

• Name and trade line matching processes hard and

vary by country

• Lack of digital transactions from cash / barter / informal

economy restrains lender understanding of consumer

behavior

• Digital risk management culture emerging, but new in

all but most advanced economies

9

Developing World Originations

• Heavy focus on upper income customers

– Bank conservatism

– Frequently a high fraction of GDP informal – hence no data on

middle & lower income consumers

• Bureaus frequently ordered only on high / middle scoring applicants after they’ve passed an app. score, not generally on all applicants after they’ve passed an app. score, not generally on all applicants due to cost. (cents in USA, up to several Euros outside)

• Marketing often done to consumer’s employer or other group underwriting filter – self-employed ignored too often

• Country dependent, originations frequently focused on socio-demographic (application) data

• Information is applicant-volunteered, time & money spent confirming with onsite & phone verifications

10

Originations With Positive &

Negative Credit Bureau Criteria

<2 or >4 Revolving

>1 Revolving Accts >60 Days Past Due

Serious Delq / BK Last 18 Months

Business, Prison, P.O. Box Address

Yes

Yes

Yes

No

No

No

11

RejectRejectReject RejectAction Reject Acc’ptAcc’pt

Application Score

>5 Inquiries last 3 months

<2 or >4 Revolving Accounts

Reject Acc’ptReject

Yes

Low HighMedLow HighMed

No

Yes No

• Summarize value of bureau data into simple index

• Developing world: less useful as bureau is developing

– Big guys get in last

– Attribute counts & models less stable until they do…

Originations with Bureau Scores

High

LowCredit Bureau Score

Med High

12

Cre

dit B

ure

au S

core

Application Score

Reject Accept

Low High

High

Action

Application Score

Reject TestReject

Low HighMed

Reject Acc’ptAcc’pt

Low HighMed

Reject Acc’ptAcc’pt

Low HighMed

Emerging Account Management

• In developing countries more political will inside banks for customer level management as compared to US, - single cross-product country officer / head / leader. Not product-

focused

• Systems remain a key constraint, as in developed world

– Account focused– Account focused

– Little “talking” across products

• Strategies focus on internally available data, batch data costs often similar (or equal) to online: uneconomic to do quarterly or monthly refreshes

• Risk management culture looking at both internal & external data for account management limited

• Collections very culturally-specific on timing, scripting, contact methods, legal procedures, foreclosure/repo

13

Negative Only Credit Line Increase

Collections Acct Last 3 Months

BK / Writeoff Last 12 Months

>2 Revolving Late Payments Last 12 Mos.

Negative File Hit No Yes

Yes No

Yes No

Yes No

Action

Behavior Score

>4 Inquiries Last 60 Days

Months

Any Open Accts >60 DPD

No Action

No Action

No Action

BehScore

No Action

No Action

+10%+15%No Action

Low HighMed

Yes No

Yes No

Collections with Negative Data

External Delq

External Accts Currently Past Due

Negative File Hit

Cycles Delinquent 1

YesNo

0,12+

15

Decel

StdStdStd AccelAccelerated, Standard Decelerated

Accel LtrAccel

Behavior Score

Internal Delq Balance Amount

External Delq Balance Amount

Low HighMed

High LowHigh Low

NoneDecel

StdDecel

LowHigh

Low HighMed

High LowHigh Low

Ltr

LowHigh

Banned for Marketing?

• Frequently bureau association rules or national law prohibit

marketing uses for CB data

• How does your regulator and your lawyer feel about aggregated

CB data vs. personalized data?

• If permitted, typical uses: • If permitted, typical uses:

– Target audience selection beyond income

• The middle classes

• Self-employed, small company employees

• Underserved / recent immigrant populations

– Location of physical presence points: Sales offices,

branches, Kiosks

– Invitation to apply to a region / postcode

16

Negative Data Marketing / Promotions

Postcode High Hit Rate

%

Postcode High

Bankruptcy %

Prison, P.O. Box

Address

Yes

Yes

Yes

No

No

No

Kiosk, Branch

No Action

No Action

No ActionAction

No Action

Postcode High %

Revolving Delq

Postcode High % of 90

Days Past Due

Yes

No Action

No

Yes No

What Lenders Could Improve

• Encourage governments to formalize

economies – tax break for opening an

account?

• Use credit bureaus to move beyond

univariate approach on income + knockout univariate approach on income + knockout

rules – enfranchise consumers

• Focus on complete credit risk spectrum –

create benefits for low risk customers as

well as manage higher risk customers

• Use bureau data to make smarter line,

overlimit, collections & renewals

What Bureaus Could Improve

• Price offline data cheaper than online to

encourage analytics and account management

usage

• Give consumers a voice: actively create

opportunities to consumers to learn about, see opportunities to consumers to learn about, see

and modify their files

• Assemble data from non-bank industries that

show consumer monthly behaviors: insurance,

utility, telecomm, wireless, tax

Summing Up

• Bureaus are key piece of infrastructure for safety

& soundness & growth, but data must be

economic for lenders to use in all decision areas

• Developed markets need to move beyond

bureaus for growth – verifications, employment, bureaus for growth – verifications, employment,

customer level management

• Developing markets need more digital data on

consumers to move further into scientific risk

management