Information asymmetries and the resulting adverse selection and moral hazard problems are one of the biggest obstacles in credit markets (Stiglitz and Weiss 1981) , especially for smaller enterprises that suffer traditionally from financing constraints (Siedschlag et al. 2014, Stanisic et al. 2015). Credit information sharing through public credit registries and private credit bureaus is seen as a critical policy tool to overcome the ensuing market frictions and inefficiencies, and has been advocated by international financial institutions over the past two decades (CGAP and IFC 2011). But which borrowers are most likely to gain from having their credit information shared? Which financial institutions are most likely to use the newly available credit information?
In a recent paper (Beck et al. 2023), we use the lowering of the threshold above which lenders have to report credit individual borrower exposures to the Central Bank of Brazil’s credit registry to explore the impact of information sharing on borrowers of different risk profiles and lenders of different sizes and ownership. The rich data allow us to explore not only the impact on access to external funding and loan conditionality but also on labour market outcomes.
Theory and existing literature
Sharing credit information can have a disciplining effect on borrowers: by sharing default information with other lenders, banks can incentivise borrowers to reduce default probability. At the same time, information from credit registries can improve the screening process of banks, again with dampening repercussions for their default ratio. Sharing also positive (in addition to default) information about borrowers can increase competition between lenders and increase overall lending if asymmetric information is very pronounced (Pagano and Jappelli 1993). This competition effect can also reduce hold-up problems for opaque borrowers limited to one specific lender (Sharpe 1990, Rajan 1992, von Thadden 2004).
Theory also predicts an important heterogeneity effect across borrowers of different quality: while high-quality borrowers should benefit from information sharing, low-quality borrowers might see a reduction in access to credit or significantly adverse loan contract terms. It is therefore ex ante not clear whether the sharing of information will, on average and in the aggregate, result in an increase in lending and an easing of loan contract terms such as a reduction in interest rates or collateral requirements.
There are a number of papers exploring the effects of credit information sharing for borrowers. Most studies show a reduction in loan defaults, but also an increase in loan application rejections (e.g. Albertazzi et al. 2017, De Haas et al. 2016, 2021).
The policy change
The Central Bank of Brazil created its own credit registry in 1997, with the objective to support banking supervision. Since then, every financial institution in Brazil must report monthly to the Credit Information System (SCR) detailed information on all outstanding loans of firms and individuals if the total exposure of each firm or individual is above a certain threshold.
In December 2011, the Central Bank of Brazil issued a new regulation lowering the threshold from 5,000 BRL (approximately US$2,000 at the time) to 1,000 BRL ($400 at the time), and established April and July 2012 as the deadlines for banks and credit unions, respectively, to send information in accordance with the new threshold. The largest banks in the country were swift to respond, and 90% of the increase in the pool of borrowers in the credit registry happened in January 2012.
The reduction of the new threshold to 1,000 BRL allows us to identify firms in the SCR in 2012 that were not visible before the lowering of the threshold and observe their loans granted in an environment with no information sharing to thus compare them to loans granted after they became visible in the credit registry and compared to firms that were visible before and after the change in the threshold. We can also distinguish between risky, safe and very safe borrowers according to their repayment history
as well as between banks of different ownership in Brazil.
Comparing firms newly included (treated) in the SCR to already included (control) firms and (where possible) before and after the policy change, we find:
- Relative to pre-treatment trends and control groups, riskier borrowers increase their number of lenders. The results suggest that privately owned lenders use the newly available information to start relationships with risky and relatively safe borrowers, while foreign-owned and top five lenders use the newly available information to start relationships with risky, but not with very safe or relatively safe borrowers.
- We find an increase of the average loan amount of 74% for risky, 109% for relatively safe, and 68% for very safe borrowers after inclusion in the credit registry relative to already visible borrowers, resulting in an inverted U-shaped effect. This increase comes primarily from new rather than existing lending relationships.
- We find that newly included borrowers experience lower interest rates, with the relationship being U-shaped in risk profile – that is, relatively safe borrowers seeing the largest decline, followed by very safe and then risky borrowers. The lower interest rates are mostly driven by existing lending relationships, pointing to competition effects of information sharing.
- We find that incumbent lenders relax the demand of collateral, in line with the findings for interest rates. This finding could be interpreted as a device for protection from competition used by incumbent lenders, suggesting that they substitute collateral with the disciplining tool of information sharing. Here the effect is strongest for very safe borrowers, while relatively safe borrowers face higher collateral requirements when switching lenders and with certain types of new lenders.
- Following inclusion in the credit registry, borrowers face shorter maturity loans from incumbent lenders, consistent with a disciplining effect, i.e. as information sharing allows borrowers access to more lenders, incumbent lenders react by reducing loan maturity.
- Finally, we find that while there is a relatively small decline in default probability on average, there are large differences between incumbent and new lenders and between borrowers of different risk types. Risky borrowers show a decline in default probability on loans with incumbent lenders and an increase of default probability on loans with new lenders.
In summary, while there is an expansion in access to credit for newly included borrowers both along intensive and extensive margins, incumbent lenders react by changing the loan contracts offered to these borrowers, offering lower interest rates and relaxing collateral requirements but also shortening loan maturities.
We also explore the relationship between inclusion in the credit registry and labour market outcomes, combining our data with information from RAIS, the database managed by the Brazilian Ministry of Labour. Our results show an increase in employment, especially for relatively safe and risky borrowers with new lenders that are private banks or credit unions. Easing of financing constraints, especially for riskier firms, thus results in the hiring of new staff and an expansion of firms.
While the benefits of information sharing for lenders stem from their improved ability to screen and monitor borrowers’ creditworthiness, we find evidence of improved access to credit and real effects in the labour markets especially for riskier borrowers. There is also evidence that information sharing increases competition, as borrowers get better loan terms from their incumbent lenders.
The effects of credit information sharing differ by lender ownership type, which suggests that lenders use different credit technologies, and this translates into heterogeneous effects associated with an increase of available information about borrowers. Specifically, it is primary privately owned and foreign-owned banks that use credit registry information to expand their borrower population. We show that risky borrowers can benefit from credit information sharing in a market with financial institutions that use the credit registry to expand their lending portfolio, even if this comes at the risk of higher loan default, which is different from other studies in this literature.
Albertazzi, U, M Bottero and G Sene (2017), “Information externalities in the credit market and the spell of credit rationing”, Journal of Financial Intermediation 30: 61-70.
Beck, T, P Behr and R Oliveira (2023), “Information Sharing, Access to Finance, Loan Contract Design, and the Labor Market”, CEPR Discussion Paper 18131.
CGAP and IFC – Consultative Group to Assist the Poor and International Financial Corporation (2011), Credit Reporting at the Base of the Pyramid: Key Issues and Success Factors.
De Haas, R, M Millone and J W B Bos (2016), “Bank lending and the sharing of borrower information”, VoxEU.org, 22 March.
De Haas, R, M Millone and J W B Bos (2021), “Information Sharing in a Competitive Microcredit Market”, Journal of Money, Credit and Banking 53(7): 1677-1717.
Pagano, M and T Jappelli (1993), “Information sharing in credit markets”, Journal of Finance 48(5): 1693–1718.
Rajan, R G (1992), “Insiders and Outsiders: The Choice between Informed and Arm’s Length Debt”, Journal of Finance 47(4): 1367-1400.
Sharpe, S (1990), “Asymmetric information, bank lending and implicit contracts: A stylized model of customer relationships”, Journal of Finance 45(4): 1069– 1087.
Siedschlag, I, C O’Toole, G Murphy, B O’Connell and N Kay (2014), “Do all firms have equal access to external financing?”, VoxEU.org, 29 June.
Stanisic, D, J McCahery, D Schoenmaker and F Lopez de Silanes (2015), “Estimating the financing gap of small and medium-sized enterprises”, VoxEU.org, 21 August.
Stiglitz, J E and A Weiss (1981), “Credit Rationing in Markets with Imperfect Information”, American Economic Review 71(3): 393-410.
von Thadden, E L (2004), “Asymmetric Information, Bank Lending, and Implicit Contracts: the Winner's Curse”, Finance Research Letters 1: 11-23