Transcript Lessons for Information Sharing Standards in APEC

Asia-Pacific
Credit Coalition
Lessons for Information Sharing
Standards in APEC
By Michael Turner
Presentation for 4th SEACEN-ABAC/ABA/PECC
Public-Private Dialogue for the Asia Pacific Region
Westin Kuala Lumpur
18-19 August 2008
About APCC


The Asia Pacific Credit Coalition, an affiliate of the non-profit
Political and Economic Research Council (PERC), is committed to

The promotion of credit reporting standards within APEC

Showing value proposed reporting standards
In pursuit of goal, APCC

Hosts seminars with national regulators and policy makers.

Reaches out to APEC staff, media, industry execs and governments

Conduct research demonstrating need for standard
2
Policy Position for
Common Standard (I)
Support the standard of full-file (positive and
negative payment) and comprehensive (across
many sectors) reporting to a private bureau based
on results that it:
 increases lending to the private sector, especially lowincome groups, women; and,
 results in better loan performance.
3
Policy Position for
Common Standard (II)
Develop standard that meets OECD Fair Information Practices
(1980), providing to data subjects rights of:






notice
access
choice
notification of adverse action
dispute
correction
Ensures that only responsible and experienced actors such as
Experian will collect and maintain the data
4
Common Findings
Long history of investigation and study of
information sharing. Results are full-file and
comprehensive reporting:
 increases lending to the private sector especially among
lower social segments more than other reporting regimes;
and,
 results in better loan performance than segmented and
negative-only reporting.
 Private bureaus with comprehensive data
increase lending to the private sector.
5
Consequences of Full-file Vs.
Negative-only I: (US Data)
Table 1: Acceptance Rates for a Targeted Performance Level
using Full -File versus Negative-Only Reporting
Target
Full -file, comprehensive
Negative-only
default rate
reporting (%)
reporting (%)
(%)
3%
74.8%
39.8%
4
83.2
73.7
5
88.9
84.6
6
93.1
90.8
7
95.5
95.0
Source: John M . Barron and M ichael Staten, “The Value of Comprehensive Credit Reports:
Lessons from the U.S. Experience,” in M argaret M . M iller ed., Credit Reporting Systems
and the International Economy¸ 273-310 (Cambridge, M A: MIT Press. 2003).
Results on
acceptance rates

acceptance rates climb as
information moves from
full-file to negative-only in
all cases
Table 2: Acceptance Rates by Targeted Performance
Level with Full-File versus Negative-Only Reporting (U.S.
Commercial Scoring Models)
Full -file,
Target default
comprehensive
Negative-only
rate (%)
reporting (%)
reporting (%)
2%
41.9%
28.5%
3
49.2
40.0
4
55.6
47.2
5
60.4
55.5
6
63.7
60.4
7
66.4
64.1
Source: M ichael Turner et al., The Fair Credit Reporting Act: Access,
Efficiency, and Opportunity (Washington, DC: The National Chamber
Foundation, June 2003).
6
Consequences of Full-file Vs.
Negative-only for Performance
20%
30%
40%
1.84
(170%)
50%
60%
1.45
(76%)
70%
75%
80%
90%
0.8
(62%)
0.6
(33%)
0.3
(10%)
0.4
(8%)
0
(0%)
4.94
(140%)
4.94
(120%)
8.96
(183%)
8.54
(146%)
8.1
(113%)
0.92
(60%)
1.48
(114%)
0.57
(108%)
0.83
(28%)
1.53
(83%)
0.72
(61%)
0.18
(43%)
0.19
(36%)
0.24
(35%)
0.26
(27%)
Remova l
of
Telecom
Data
Turner, Lee et al., using U.S.
files
Turner, Lee et al., using U.S.
files
Turner, using Canadian files
Barron and Staten, using U.S.
files
Majnoni et al., using Brazilian
Files
Majnoni et al. using
Argentinean files
Turner and Varghese, using
Colombian files
Turner et al., using U.S. files
Acceptan ce
Rate
Barron and Staten, using
U.S. files
Percentage Point Change in the Defaul t Rate i n Reporting Regime Switch
(pe rcentage change shown in par entheses)
Remova l
Comp rehensive
of
to Segmented
Uti lity
Full-file to Negative Only
Repor ting
Data
0.2
(22%)
0.3
(25%)
0.5
(28%)
1.2
(40%)
2.7
(50%)
0.2
(18%)
0.5
(29%)
1.3
(39%)
2.7
(36%)
3.8
(31%)
4.3
(45%)
3.9
5
(31%)
3.4
(28%)
(19%)
Results on loan portfolio
performance
 default
rates climb as information
moves from full-file to negativeonly in all cases


good risks are confused for bad ones
bad risks confused for good ones
 Data


sharing
improves quality of information for risk
provisioning, allowed under Basel II
with lower defaults, small capital
requirements, lower credit constraints
0.84
(39%)
1.03
(34%)
0.96
(19%)
0.86
(30%)
0.68
(47%)
2.83
(11 4
%)
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Distributional Consequences of
Full-file vs. Negative Only
Effects on Acceptance Rates for a 3 Percent Targeted Default Rate between
Full-file Reporting and Negative-only Reporting, by Demographic
Characteristics (US Data)
Negative-only
(index = 100)
Full-file
(index = 100)
Race-Ethnicity
Caucasian, Non-Hispanic
100
121.8
African American
100
127.9
Latinos
100
136.8
All Minority
100
135.5
Gender
Female
100
121.8
Male
100
123.0
Age
<36
100
147.1
36-45
100
121.8
46-55
100
121.2
56-65
100
119.8
66-75
100
117.9
76+
100
119.9
Household Income (US$)
< 15,000
100
135.9
15,000 -29,000
100
129.7
30,000 -49,000
100
124.2
50,000 -99,000
100
120.6
>100,000
100
117.8
Source: Michael Turner et al., The Fair Credit Reporting Act: Access, Efficiency, and Opportunity
(Washington, DC: The National Chamber Foundation, June 2003) .
Results on demography
using real credit files
 disadvantaged
social segment
gain greater access than
others



racial-ethnic minorities
young
low-income groups
 Colombian


simulations
under negative-only, 33% of
acceptances women
under full-file, 47% are women
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Growth and Equality
Comprehensive reporting promotes economic growth by
enabling an increase in lending to the private sector by as
much as 45% of GDP.

Statistical tests show that an increase in private sector lending
by 30% of GDP can yield:
o
o
o

an increase in GDP growth rates of 1%;
an increase in productivity growth of 0.75%; and
an increase in capital stock growth of 0.75%.
An increase in private sector claims by 50% of GDP:
o
o
o
lowers the growth of the Gini coefficient (an inequality measure) by at
least 0.25%, and more by some estimates.
lowers the growth of the percentage of the population living under $1 per
day by 2%, and more by some estimates.
increases the growth of the lowest (poorest) quintile’s income share by at
least 0.45%, and more by some estimates.
Source: Ross Levine, “Financial Development and Economic Growth: Views and Agenda” Journal of Economic
Literature, Vol. 25(June 1997), pp. 688–726; Thorsten Beck, Asli Demirguc-Kunt and Ross Levine, “Finance,
Inequality and the Poor.”
www.econ.brown.edu/fac/Ross_Levine/Publication/Forthcoming/Forth_3RL_Fin%20Inequalily%20Poverty.pdf.
9
Background: The Financial Sector
East Asia:
Healthy private sector lending in few countries
120%
100%
80%
60%
40%
20%
0%
NA/E/ANZ
North
America
(N=16)
Europe
Aust/NZ (N=16)
EA (N=5)
East Asia
(N=5)
1995
Source: International Financial Statistics, IMF
MENA
(N=5)
Middle
East
N. Africa
(N=5)
1996
1997
EE Europe
(N=8)
E.
(N=8)
LA (N =18)
SA
S. (N=3)
Asia
(N=3)
Latin
America
Afr (N=12)
Sub-Saharan
Africa
(N=12)
(N=18)
1998
1999
2000
2001
2002
2003
2004
10
Legal Rights of Creditors and
Credit Information by Region
Credit Information Index and Legal Rights in Collateral &
Bankruptcy Index by Region, 2007
7
6
Index Score
5
4
3
2
1
0
OECD
APEC
Eastern Europe
& Central Asia
Latin America
& Caribbean
Legal Rights Index (0 to 10 scale)
Middle East &
North Africa
East Asia &
Pacific
Sub-Saharan
Africa
Credit Information Index (0 to 6 scale)
Wealthier regions have both, strong legal rights
and extensive credit information
Source: Doing Business Database, World Bank
South Asia
11
Legal Rights of Creditors & Credit
Information by APEC Member
Credit Information Index and Legal Rights in Collateral &
Bankruptcy Index by APEC Member, 2007
10
9
Index Score
8
7
6
5
4
3
2
1
C
an
ad
a
Ja
p
an
M
al
ay
si
a
M
ex
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o
U
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it
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u
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ta
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A
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H
ra
on
lia
g
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on
h
ile
g,
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h
in
a
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ew
or
Ze ea
Ta
al
iw
an an
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h
Th ina
ai
la
n
d
C
h
in
a
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u
ss
S
in
ia
g
ap
In
o
do re
n
P
e
h
ili sia
pp
in
es
V
ie
tn
am
B
P
ru
ap
C
am ne
u
i
a
b
N
e w od
ia
G
u
in
ea
0
Legal Rights Index (0 to 10 scale)
Credit Information Index (0 to 6 scale)
Wealthier economies in APEC have both, strong legal rights
and extensive credit information
Source: Doing Business Database, World Bank
12
APEC Full-file & Comprehensive
Reporting Coverage by Ownership
Australia
Brunei
Cambodia
Canada
Chile
China
Hong Kong, China
Indonesia
Japan
Korea
Malaysia
Mexico
New Zealand
Papua New Guinea
Peru
Philippines
Russia
Singapore
Taiwan, China
Thailand
United States
Vietnam
Full-file
No
Comprehensive
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
No
Yes
No
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Public
registry
coverage
(% adults)
0
0
0
0
26.2
49.2
0
20.5
0
0
44.5
0
0
0
20.7
0
0
0
0
0
0
9.2
Private
bureau
coverage
(% adults)
100
0
0
100
33.5
0
64.7
0.2
68.3
74.2
61.2
100
0
33
5.5
4.4
42.7
67.1
27.9
100
0
13
Source: Doing Business Database, World Bank
What You Can Do
Much work remains to be done, and help
is needed. If you are interested you can:
o
Assist in the formulation of standards for APEC, by
helping to take local concerns into account
o
Participate in local and country area outreach
efforts, sharing experiences of best practices and
methods of engaging press and policymakes
o
Join APCC coalition to may it wider, broader, and
more multinational.
14
For more information
Dr. Michael Turner
Asia-Pacific Credit Coalition
100 Europa Drive, Suite 403
Chapel Hill, NC 27517
www.apeccredit.org
Phone: +1 919 338 2798