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CENTRO STUDI DI ECONOMI A E FI NANZA

CENTRE FOR STUDIES IN ECONOMICS AND FINANCE

DI PARTI MENTO DI SCI ENZE ECONOMI CHE UNI VERSI TÀ DEGLI STUDI DI SALERNO

Information sharing in credit markets: a survey Tullio Jappelli - Marco Pagano

Conference on The Economics of Consumer Credit:  European Experience and Lessons from the US

European University Institute, 13/14 May 2003

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Outline

A. The role of credit information systems• Reducing adverse selection• Disciplinary effect of default disclosure• Preventing over-borrowing by multiple lenders

B. Empirical evidence• Historical• Macro• Micro• When is public intervention useful?

C. Issues in the design of credit information systems (transition economies)

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Asymmetric information in credit markets

• The data needed to screen credit applications and to monitor borrowers are not freely available to banks. In their absence, banks face adverse selection and moral hazard problems.

• Adverse selection arises when the lender does not observe some characteristics of the borrower. Moral hazard when he does not observe certain actions by the borrower, which affect the probability of repayment: for instance, the borrower’s effort to manage his project and avoid default

• In either case, asymmetric information between borrowers and lenders can prevent the efficient allocation of credit.

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How can banks mitigate adverse selection and moral hazard problems?

• Collateral• Large equity stakes• Reputation• Acquisition of information … but how?

Alternatives:1. Acquire information directly by spending resources, or2. Acquire it by exchanging it with other lenders.

Exchange what?• Credit history• Amount of debt• Other information

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Information sharing arrangements

• Private Credit Bureaus (especially in Anglo-Saxon countries). Principle of reciprocity. They collect, file and distribute data supplied voluntarily by members

• Public Credit Registers (PCR) managed by central banks (Continental Europe and Latin America). Their data are compulsorily reported by lenders. Universal coverage of banking institutions.

• Credit bureaus focus on consumer and small business loans, which are generally ignored by PCR.

• Conversely, PCR often provide a more complete picture of large corporate loans.

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Type of information shared

• Black or negative information: defaults and arrears.

 

• White or positive information:

- debtor’s current overall loan exposure and guarantees

- past credit history other than defaults and arrears

- other characteristics, such as employment, income or line of business.

 

• Often credit bureaus process these data, assigning a credit score to borrowers based on statistical risk analysis.

 

• There is great international variability in the type of data reported and distributed by private credit bureaus and PCR.

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The World Bank survey of credit information sharing

• In 1999-2001 the World Bank conducted a survey of credit bureaus and PCR.

• PCR: 41 countries out of 77 who replied to the survey operate a PCR. Most Latin American countries, 7 European, many former socialist countries. Mostly in the 1990s. Oldest in Germany (1934), France (1946), Italy and Spain (1962).

• Prevalence of minimum reporting threshold in PCR, with wide international variability

• Private credit bureaus: Anglo-Saxon countries, Europe, East-Asia.

• Market segmentation in the US: Dun and Bradstreet for commercial loans, specialized credit bureaus for consumers. Not elsewhere.

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The four effects of information sharing

1. Credit bureaus improve banks’ knowledge of applicants’ characteristics and permit more accurate prediction of repayment probability.

2. Credit bureaus reduce the informational rents that banks could otherwise extract from their customers.

3. Credit bureaus work as a borrower discipline device: every borrower knows that a default damages his reputation with other potential lenders, cutting him off from future credit or making it more expensive.

4. Credit bureaus eliminate the incentive to over-borrow when borrowers draw credit simultaneously from many banks without any of them realizing.

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 1. Reducing adverse selection

• Information sharing allows banks to improve statistical risk management, and make more accurate predictions about repayment probabilities of credit applicants, partly overcoming adverse selection problems.

Better knowledge of borrowers’ characteristics leads to safer lending and lower defaults.

• The effect on lending is ambiguous. The increase in lending to safe borrowers may not compensate for the reduction in lending to risky borrowers.

• Kalberg and Udell (2003) capture the economies of scale associated with information exchange from multiple sources on each borrower. The use of more than one source increases the precision of the signal about the borrower.

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2. Reducing borrowers’ holdup • In segmented credit markets banks have private information on borrowers. This

informational advantage confers to banks market power over their customers and generates a hold-up problem: borrowers anticipate that banks will charge predatory rates in the future and exert low effort to perform.

  If they commit to exchange information about borrowers’ types, banks restrain their own future ability to extract informational rents. A larger portion of the total surplus is left to entrepreneurs. 

• Borrowers have a greater incentive to invest effort in their project to ensure their success. This reduces defaults and increases lending.

• Gehrig and Stenbacka (2003) consider a situation in which banks are already competing. In the presence of switching costs, future informational rents are a stimulus to competition. Information sharing avoids these rents, thus reducing competition. In this sense, information sharing is an anti-competitive device.

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3. Disciplinary effect of default disclosure

Sharing black information disciplines borrowers. Borrowers try to avoid the implied loss of reputation and the penalty of higher interest rates. They exert more effort to avoid default, interest rates fall and lending increases.

However:

1. Exchanging other data may reduce this disciplinary effect. A high-quality borrower will not be concerned about his default being reported to outside banks if these are also told that he is a high-quality client.

2. Over time, creditors learn more about their borrowers, reducing the value of each additional piece of negative information, so incentives to comply are also reduced (Vercammen, 1995).

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4. Eliminating incentives to over-borrow from multiple lenders

• The literature on information sharing is mostly based on single-lender, bilateral information exchange. Multiple bank relationships are commonplace in most countries. In the absence of information sharing, multiple lending creates an incentive to over-borrow.

• Anticipating this moral hazard, lenders might ration the amount of credit supplied, require a higher interest rate, or deny all credit unless assisted by collateral.

• Exchanging positive information on borrowers’ debt level eliminates this problem, and improves the terms offered by lenders. The supply of lending and/or the interest rates offered to credit seekers improves.

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Summary of theoretical predictions • The incentive to share information depends on borrowers’ mobility, heterogeneity

of the population, degree of competition of the banking sector.

• Exchanging different types of information address different information problems in the credit market:

• Information about borrower characteristics relieves adverse selection problems.

• Sharing default information tends to correct moral hazard problems.

• Information about borrowers’ debt exposure removes the particular form of moral hazard deriving from borrowers’ ability to borrow from multiple lenders.

• All models predict that information sharing reduces default rates, whereas the prediction concerning its effect on lending is less clear-cut. Some models predict that a more competitive banking structure leads to less information sharing, others that it leads to more sharing.

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Empirical questions

• What are lenders’ incentives to promote the exchange of information? Why do credit bureaus operate in some countries but not in others?

• Can we expect credit bureaus to increase lending activity? Will better risk management reduce the default rate? Are credit bureaus ultimately beneficial to economic activity and welfare?

• If credit bureaus do not emerge spontaneously in the market, should governments promote the exchange of information between lenders? And even granted that government should have a role, what is the best way to intervene and to enforce information sharing?

• Historical evidence

• Macroeconomic evidence

• Microeconomic evidence

• Causality issue: one the one hand, information sharing can increase lending. On the other, higher lending increases the incentive to exchange information.

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The appearance of credit bureaus

• The incentive to share credit data should correlate with:

• Mobility of borrowers between various lenders.

• Heterogeneity of borrowers.

• The size of the loan market.

• Technical innovation.

• Regulation (Privacy Laws)

• The group of countries where credit bureaus are more active also exhibits high mobility of borrowers and deep consumer credit markets.

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Borrowers’ mobility and information sharing

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Figure 3. Credit Reports and Residential Mobility

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The effect of information sharing: descriptive statistics

Variable Total Sample 

No Information Sharing

  

Black Information Only

Black and White Information

Bank Lending / GDP (%) 60.53 31.10 67.57 66.42

Credit Risk 7.77 15.20 5.11 7.14

Log GDP 7.19 5.96 6.77 7.79

GDP Growth Rate (%) 3.45 4.53 2.87 3.38

Rule of Law 7.24 4.80 8.14 7.59

Creditor Rights 2.15 3.14 2.20 1.83

French Origin 0.40 0.43 0.20 0.48

German Origin 0.12 0.00 0.00 0.22

Scandinavian Origin 0.10 0.00 0.30 0.04

English Origin 0.37 0.57 0.50 0.26

         

Number of observations 40 7 10 23

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Effect of information sharing on Bank Lending / GDP

Variable Ordinary Least Squares 

TrimmedRegression

Robust Regression

  (1) (2) (3) (4) (5)

GDP Growth Rate 2.61(0.85)

2.93(0.89)

2.17(0.62)

0.30(0.15)

-1.19(-0.68)

Log GDP 5.30(1.73)

4.96(1.51)

2.23(0.61)

5.08(2.17)

5.34(2.00)

Rule of Law 7.47(3.14)

6.25(2.46)

7.72(3.64)

4.90(3.94)

4.87(2.89)

Creditor Rights 6.58(2.12)

8.32(2.76)

5.27(1.07)

8.57(2.55)

9.96(3.23)

French Origin     -7.01(-0.65)

0.80(0.12)

2.46(0.31)

German Origin     26.67(1.24)

19.83(1.82)

14.66(1.42)

Scandinavian Origin     -44.46(-3.18)

-29.98(-2.52)

-29.22(-2.59)

Black Information Only   24.77(1.52)

29.38(1.82)

36.42(4.90)

36.46(3.50)

Black and White Information   23.18(2.38)

15.65(1.43)

26.95(5.00)

27.23(2.92)

Constant -54.86(-2.71)

-67.93(-3.03)

-42.65(-1.22)

-60.02(-3.32)

-60.64(-2.96)

           

Adjusted R square 0.46 0.50 0.67 0.81 -.-

Number of observations 40 40 40 36 40

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Effect of information sharing on Credit Risk Variable Ordinary Least Squares Trimmed

RegressionRobust Regression

  (1) (2) (3) (4)

GDP Growth Rate (%) -0.63(-2.05)

-0.56(-1.97)

-0.63(-2.59)

-0.61(-2.06)

Log GDP -0.57(-1.21)

-0.34(-0.74)

-0.04(-0.14)

-0.21(-0.43)

Rule of Law -1.65(-4.31)

-1.67(-4.74)

-1.88(-8.34)

-1.71(-5.45)

Creditor Rights -0.45(-1.07)

-0.09(-0.17)

-0.17(-0.47)

-0.09(-0.17)

French Origin   0.90(0.73)

1.33(1.41)

1.04(0.70)

German Origin   -2.76(-2.32)

-1.96(-1.81)

-2.46(-1.41)

Scandinavian Origin   2.19(1.42)

2.62(1.78)

2.23(1.18)

Black Information Only -4.26(-1.91)

-4.54(-2.15)

-3.08(-1.75)

-3.78(-1.89)

Black and White Information

-2.99(-1.76)

-2.40(-1.37)

-2.15(-1.65)

-2.22(-1.23)

Constant 30.59(9.67)

27.51(8.90)

26.27(9.74)

26.49(7.09)

         

R square 0.78 0.84 0.90 -.-

Number of observations 35 35 30 35

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Microeconomic evidence

• Some papers analyze the predictive power of credit scoring tools, generally finding that credit report are an important tool for assessing consumer credit risk (Chandler and Parker, 1992; Barron and Staten, 2003).

• Kalberg and Udell (2003) show that trade credit history in D&B reports improves default predictions relative to financial statements alone.

• Galindo and Miller (2001) find a positive relation between access to finance (debt) and an index of information sharing in the Worldscope database: well performing credit registries reduce the sensitivity of investment to cash flows.countries with better information sharing

•

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When is public intervention useful?

• Information sharing arrangements do not guarantee an efficiency gain under all circumstances. Their ability to increase efficiency depends on the way they are designed.

 • In some situations, sharing information about defaults may elicit a

level of effort by borrowers above the socially efficient level. In others, it falls short of it.

 • The social efficiency of information sharing also depends on the type

of information shared and, more generally, on the design of the sharing mechanism.

• Compulsory information sharing may discourage banks from searching new information, reduce screening and monitoring, and kill relationship lending.

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Reasons for creating a Public Credit Register

1. Antitrust policy• If information sharing depends on the banks’ initiative, they may

not implement it even if it is socially efficient for fear of increased competition.

• Policy intervention in these cases could be justified as any antitrust policy.

2. Enhance banking stability and supervision.• Bank managers may take too much risk. A public register helps

supervision and prudential intervention.

3. Help conglomerate banks• Information sharing can help conglomerate banks to figure out

their own consolidated liability position.

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Determinants of the Presence of Public Credit Registers

Descriptive Statistics

Variable Total Sample 

PCR Present PCR Absent

Creditor Rights 2.14 1.59 2.50

Rule of Law 7.08 6.67 7.34

Pre-existence of a Private Credit Bureau 0.51 0.29 0.65

English Origin 0.38 0.12 0.54

French Origin 0.39 0.71 0.19

German Origin 0.14 0.11 0.15

Scandinavian Origin 0.09 0.06 0.12

       

Number of observations 43 17 26

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Explaining the presence of PCR

Variable Probit Regressions 

Tobit Regressions

  (1) (2) (3) (4)

Creditor Rights -0.16(-2.37)

-0.07(-0.81)

4,312.77(2.16)

2,199.30(0.95)

Rule of Law -0.01(-0.11)

-0.01(-0.09)

-118.17(-0.12)

366.06(0.36)

Pre-existence of a Private Credit Bureau

-0.39(-2.24)

-0.41(-2.04)

12,437.21(2.30)

13,143.05(2.13)

French Origin   0.49(3.35)

  -11,988.05(-1.65)

German Origin   0.566(1.77)

  -15,801.16(-1.72)

Scandinavian Origin   0.476(1.16)

  -10,216.27(-0.96)

         

Number of observations 43 43 41 41

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Summary of empirical evidence • Credit is positively correlated with the presence of information

sharing arrangements (also controlling for country size, growth, and variables capturing respect for the law and protection of creditor rights)

 • Public and private information sharing mitigates defaults. • PCR are introduced to compensate, at least partly, for the weak

protection that the state offered to creditors’ interests.

• The impact of private information sharing arrangements is similar to that of public credit registers.

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C. Issues in the architecture of credit information systems

• Relationship between private and public systems

• Dosage between black and white information

• Memory of the system

• Identifying company groups

• Cross-border lending

• Privacy protection

• Informal markets and poor protection of creditor rights

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I. Private and public information sharing: substitutes or complements?

• The case for the introduction of a PCR is stronger in countries where private information sharing arrangements do not exist or are primitive (transition economies).

 

• Public arrangements can put out of business existing credit bureaus or discourage the creation of new ones.

• The higher the minimum reporting threshold of a PCR, the larger the scope for private initiative.

 

• Credit bureaus complement PCR. They can provide greater detail than PCR, merge various types of data and provide credit-scoring services.

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II. Dosage between black and white information

• Default information is most effective in correcting moral hazard problems in the credit market.

 

• Loan information helps in estimating the total indebtedness of credit seekers. This helps to correct incentive problems connected with multiple lenders.

Is more information always better?

• A system that provides much information about borrowers’ characteristics may lead banks to identify more easily high-quality borrowers.

 

• But such borrowers will be less worried to be reported as defaulters, trusting that their reputation will not be stained by such an event. As a result, they may exert less effort to avoid default.

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III. Memory of the system

1.  How long should default records kept? 

2. Should they be removed after (late) repayment? 

• A system with infinite memory creates a high incentive to repay, but ex ante deters borrowing. The risk of being eternally black- listed may deter even borrowers with relatively solid prospects.

 

• A system where records are kept for a very short time exerts little discipline.

 

• Neither extremes are generally desirable. Memory must be set trading off borrowers’ discipline and the need to offer them a second chance (an interesting case: the Belgian Central Office for Credit to Private Individuals).

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IV. Identifying company groups

• A credit information system must identify debtors and their liabilities unambiguously. While for individuals this is a relatively simple task, this may not the case for companies, which are often parts of complex group structures.

 

• This is a very difficult practical task for two reasons.

 

1. The loans to the various subsidiaries may go undetected to a PCR because each of them does not exceed the PCR minimum reporting threshold.

2. Often corporate groups borrow heavily via foreign subsidiaries. But the latter debt is typically undetected by the group’s domestic PCR banks will not have a clear picture of the group’s total indebtedness.

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V. Cross-border lending • As companies grow integrated into world capital markets, national

credit information systems become unable to identify their total indebtedness.

 

• The credit bureaus’ response: branching abroad, buying foreign bureaus or linking up with them.

• The PCR response: coordinate national registers (difficult).

 

• European PCR feature deeply ingrained differences, and cannot agree on common rules, increasing danger of their displacement by private multinational bureaus.

New PCR have the opportunity of designing the PCR so as to ensure compatibility with the systems of their main commercial partners.

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VI. Privacy protection

• Information sharing finds an obvious limit in privacy protection. This differs widely both within Europe and between the US and Europe, and these differences appear to have affected the development of credit information systems.

 

• One should not necessarily take a negative view of the effect of privacy laws on credit information systems. Divulging certain types of information may lead people to become “too cautious”, and reduce risk taking. A moderate concern for privacy may indirectly serve also economic efficiency.

•  There is also one privacy-protection rule that improves the accuracy of the data stored by credit information systems: entitling individuals with the right to inspect and correct mistaken information.

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VII. Informal markets and protection of

creditor rights

• In developing countries the role of informal lending is larger than in developed economies. Since typically both credit bureaus and PCR base their information on data reported by formal lenders, their utility is much reduced in these countries.

• This limitation of information sharing systems could be overcome by opening access of PCR also to informal lenders.

• PCR and credit bureaus are more frequent in countries where creditor rights receive a relatively poor protection and the law is less effectively enforced. In this sense, PCR appear to act as a partial substitute for the lack of good judicial enforcement.

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Future research • The type of information exchanged and design of information sharing

mechanism matter at least as much as the decision to set up such mechanism.

• The market may not provide spontaneously the socially desirable information sharing mechanism.

• Key design issues: public vs. private mechanisms; dosage between black and white information sharing; “memory” of the system; enforcement of creditor rights and judicial efficiency.

Future research:

• Models with multiple lenders.

• Effect of privacy laws on economic efficiency.

• Microeconomic evidence on the value of information sharing.

• Effects of information sharing in other areas: labor markets / insurance markets.