Credit Register Research Articles

BigTech credit risk assessment for SMEs

Lending by big technology companies (BigTechs) is an important new financial innovation in the digital era. This paper attempts to evaluate robustness and special features of BigTech's credit risk assessment. Using 1.8 million loan transactions for online merchants of a leading Chinese virtue bank, we carry out a horse race analysis between the BigTech approach (i.e., big data and machine learning models) and the bank approach (i.e., traditional financial data and scorecard models) in predicting loan defaults. We show that the BigTech approach better predicts loan defaults, reflecting information and modeling advantages. Though bank approach do well for the firms which have records in credit registry, BigTech's proprietary information can complement or, where necessary, substitute for credit history in predicting defaults, especially for the unbanked borrowers. We further discuss inclusiveness feature of the BigTech approach and the implications for financial inclusion, financial intermediaries' businesses and regulators' policy.

How does credit information sharing affect trade credit? Evidence from China

AbstractThis paper investigates how credit information sharing affects corporate trade credit financing. Utilising the difference‐in‐differences method, we find a significant reduction in trade credit for infra‐marginal bank borrowers following the introduction of the Chinese National Enterprise Credit Information Publicity System (NECIPS). To reveal the mechanisms underlying the reduction in trade credit, we show that the NECIPS alleviates information asymmetry and increases formal finance access. This financing substitution effect is magnified by weak bargaining power in product markets. Our findings complement the literature on the determinants of trade credit and underscore the indispensable role of the public credit registry.

Information sharing offices and economic growth in sub‐Saharan Africa

AbstractAlthough credit availability is essential for economic growth, the information asymmetry problem inhibits the credit creation function of financial institutions. Among other means, information‐sharing offices (ISOs) have been established, including private credit bureaus and public credit registries to provide information on the financial characteristics of citizens to reduce information asymmetry. From this background, this study used an explanatory research design with a longitudinal (panel) data approach to assess whether the coverage of information by ISOs affects sectorial and overall economic growth among sub‐Saharan African (SSA) countries using the system generalized method of moments technique on data from 2005 to 2019. The results highlight that information coverage by ISOs enhances sectorial and overall economic growth by solving the information asymmetry problem. From the findings, governments in SSA countries are encouraged to support public credit registries to effectively perform their mandate while providing incentives to attract investments in private credit bureaus since they contribute to economic growth.

What If Borrowers Were Informed about Credit Reporting? Two Natural Field Experiments

ABSTRACT Using two natural field experiments, we examine how warning individual retail borrowers that their loan performance will be reported to a public credit registry before and after the loan take-up affects their borrowing behavior. We show that credit warnings reduce default rates by 3.7 to 7 percentage points and increase loan take-up rates by 4.1 percentage points, which suggests that credit warnings benefit both lenders and borrowers. The main drivers appear to be borrowers’ anticipation of a reduction in lenders’ informational rents and improved repayment incentives. Moreover, the reduction in default rates is comparable for borrowers who receive the credit warning before and after the loan take-up. As credit warnings received before but not after a loan take-up can affect the borrower pool, and thus the overall credit risk of the pool, the results suggest that credit warnings have little net effect on the pool’s credit risk due to selection. JEL Classifications: G10; G21; G23.

Capital Regulations and the Management of Credit Commitments during Crisis Times

Abstract Borrower drawdowns on credit commitments reduce a bank’s capital buffer. Using Austrian credit register data and exploiting the 2008–09 financial crisis as an exogenous shock to bank health, we provide novel evidence that capital-constrained banks manage this risk by cutting credit commitments that are not fully used. Controlling for their capital position, we find that banks also respond to liquidity problems by cutting such commitments. However, banks manage the capital and liquidity risk posed by undrawn credit in a way that limits negative macroeconomic implications: credit cuts are targeted at financially less constrained firms, and we show that borrowers of more-affected banks can substitute lost credit with credit from other banks and do not suffer real effects. Additional findings suggest that voluntary agreements between constrained banks and strong firms to reduce spare borrowing capacity can explain why strong firms experience larger credit cuts.

Production and Financial Networks in Interplay: Crisis Evidence from Supplier-Customer and Credit Registers

Production and Financial Networks in Interplay: Crisis Evidence from Supplier-Customer and Credit Registers

Дослідження впливу кваліфікуючих факторів на інвестиційно-інноваційні процеси в умовах сучасних викликів

This article explores the influence of qualifying factors on investment and innovation processes in the face of modern challenges. The influence of Ukraine's positioning in world rankings on the dynamics of investment and innovation processes is determined, which determines the degree of confidence of a foreign investor and highlights the main obstacles to the formation of an innovation-active environment within the country according to the structural components of the indices. Attention is paid to the scientific discussion of the issue of protecting the rights of minority shareholders, which has become aggravated with the implementation of the principle of liberalization of the Ukrainian financial market. The tendencies of the increase in the cost of borrowed resources within the country in connection with the policy of inflation targeting are considered, which reveals the difference between the planned and actual inflation target, since an increase in the discount rate is a managerial lever for reducing inflation. Attention is focused on a fairly high share of NPL loans in the structure of the loan portfolio of commercial banks, which necessitated improving access to credit information through the creation of a new public credit registry based on the NBU. The need has been identified for increasing the volume of the resource base, in particular with increasing the share of external sources of financing, which will help ensure competitive conditions for the implementation of the financial and economic activities of national producers. The expediency of introducing managerial financial and economic levers for the development of medium- and long-term financial instruments in the context of financing investment and innovation processes is substantiated.

Credit booms and bank risk in Southeast Asian countries: does credit information sharing matter?

PurposeThis study investigates the relationship between credit booms and bank risk in Association of Southeast Asian Nations (ASEAN) countries, with credit information sharing acting as a moderator.Design/methodology/approachThe authors use a two-step System Generalized Method of Moments (SGMM) estimator on a sample of 79 listed banks in 5 developing ASEAN countries: Indonesia, Philippines, Malaysia, Thailand and Vietnam in the period 2006–2019. In addition, the authors perform robustness tests with different proxies for credit booms and bank risk. The data are collected on an annual basis.FindingsBank risk is positively related to credit booms and is negatively associated with credit information sharing. Further, credit information sharing reduces the detrimental effect of credit booms on bank stability. The authors find that both public credit registries and private credit bureaus are effective in enhancing bank stability in ASEAN countries. These results are robust to regression models with alternative proxies for credit booms and bank risk.Research limitations/implicationsBanks in ASEAN countries tend to have strong lending growth to support the economy, but this could be detrimental to stability of the sector. Credit information sharing schemes should be encouraged because these schemes might enable growth of credit without compromising bank stability. Therefore, policymakers could promote private credit bureaus (PCB) and public credit registries (PCR) to realize their benefits. The authors' research focuses on developing ASEAN countries, but future research could provide more evidence by expanding this study to other emerging economies. In-depth interviews and surveys with bankers and regulatory bodies about these concerns could provide additional insights in the future.Originality/valueThe study is the first to examine the role of PCB and PCR in alleviating the negative impact of credit booms on bank risk. Furthermore, the authors use both accounting-based and market-based risk measures to provide a fuller view of the impact. Finally, there is little evidence on the link between credit booms, credit information sharing and bank risk in ASEAN, so the authors aim to fill this gap.

Borrowers’ discouragement and creditor information

Bank discouragement is one of the most important factors preventing firms from accessing credit. This discouragement stems from strong information asymmetry between firm and bank. To reduce this asymmetry, the latter can either gather information from the firm or access public information on the firm through credit databases. We argue that the presence of credit bureaus, set up by the regulator, which reduces information asymmetry, helps reduce banking discouragement. More specifically, this study is the first to use credit registries to capture the occurrence of screening errors. Our results clearly suggest that the probability of being discouraged decreases when creditor information is available. This phenomenon is even more obvious in regard to more opaque structures, such as risky firms or small and medium-sized firms. In contrast, relationship lending reduces the importance of external creditor information in determining the extent to which borrowers are discouraged. Our results are consistent with previous research on information asymmetry in financial intermediation and show the importance of the legal environment in which firms operate for their financial decisions.

The more the better? Information sharing and credit risk

Estimating correctly the borrower credit risks is the task of particular –and growing- importance for the banks all around the globe. Formal information sharing mechanisms are aimed to reduce information asymmetry in the credit markets and to enhance the precision of those estimates. In the academic literature, however, the answer to the question of whether more detailed borrower information accumulated and shared by credit bureaus and credit registries is always associated with higher quality of bank credit portfolios and lower credit risks is not completely unambiguous. More credit information disclosed by information intermediaries tend to result into the weaker disciplinary effect of credit history, which means higher credit risks. At the same time, the accuracy of assessing the creditworthiness of borrowers grows due to an increase in the predictive power of scoring models, which leads to a reduction in credit risk. In this paper we make a first attempt to examine the nonlinearity of this effect. We study the relationship between the depth of the credit information disclosure and the stability of the banking sector in terms of credit risks. Based on data on more than 90 countries for 2004–2020, we show that the relationship between disclosure and credit risk is non-linear: we observe the lowest levels of credit risk at minimum and maximum levels of disclosure depth. We analyze the influence of the country institutional quality and financial development on the nature of the relationship. We show that credit risks decrease with increasing depth of disclosure by credit bureaus and credit registers in in a high-quality institutional environment and in well-developed financial markets.

Capital controls, domestic macroprudential policy and the bank lending channel of monetary policy

We study how capital controls and domestic macroprudential policy tame credit supply booms, either directly or by enhancing the local bank-lending channel of monetary policy. We exploit credit registry data and the introduction of capital controls on foreign exchange (FX) debt inflows and increase of reserve requirements on domestic bank deposits in Colombia during a boom. We find that capital controls strengthen the bank-lending channel. Increasing the local monetary policy rate widens the interest rate differential with the U.S.; hence, relatively more FX-indebted banks carry-trade cheap FX-funds with expensive peso lending, especially towards riskier firms. Capital controls tax FX-debt and break the carry-trade. Differently, raising reserve requirements on domestic deposits directly reduces credit supply, particularly for riskier firms, rather than enhancing the bank-lending channel. Importantly, banks differentially finance credit with domestic vis-à-vis FX-financing; hence, capital controls and domestic macroprudential policy complementarily mitigate the credit boom and related bank risk-taking.

Credit Information Sharing and Firm Innovation: An Empirical Evidence

This paper investigates the effect of credit information sharing (CIS) on borrower’s innovation activities. On the foundation of unique dataset from developed and developing countries, we find that public credit registries (PCRs) have significant positive relationship with firms’ innovation. These findings contract the facilitative role of CIS in lowering firm’s cost of capital and boost efficiency. Out findings are robust to different specifications and alternative measures. After the establishment of PCRs, firms may benefit more if these firms have more power in enforcing the contracts and have dispersed banking environment. These findings are aligned with the perspective that improvements in creditors’ information sets leads to innovative portfolios and better financing opportunities.

Measuring Heterogeneity in Banks’ Interest Rate Setting in Russia

ABSTRACT We use credit registry data on all corporate loans issued by Russian banks since 2017 to decompose bank interest spreads into a common factor, borrower- and lender-specific components. We find that the variation in loan rates associated with lender-specific factors (heterogeneity of banks) and borrower-specific factors (heterogeneity of borrowers) is substantial. We use the bank-specific components identified to measure the fragmentation of the corporate credit market in Russia. The results indicate that heterogeneity in banks’ interest rate setting is high and increased in the early stage of the pandemic. Finally, our results suggest that banks tightened non-interest loan conditions during the pandemic.

Digital Universal Financial Credit Risk Analysis Using Particle Swarm Optimization Algorithm with Structure Decision Tree Learning-Based Evaluation Model

Predictions of credit risk, model reliability, monitoring, and efficient loan processing are all important factors in decision-making and transparency. Machine learning method is providing these people new hope. However, it is up to banking or nonbanking institutions to determine how they will implement this advanced method in order to decrease human biases in loan decision-making. Objective. This paper proposed the novel machine learning-based credit risk analysis in the digital banking evaluation model. The purpose of this research is to compare various ML algorithms in order to develop an accurate model for credit risk assessment utilising data from a genuine credit registry dataset. Aim is to design the classification-based model using particle swarm optimization (PSO) algorithm with structure decision tree learning (SDTL) in predicting credit risk. This system has the potential to improve quality criteria such as dependability, robustness, extensibility, and scalability. Features have been extracted and classified by the proposed PSO_SL model. Experimental Results. The data have been collected based on real time for credit analysis. Simulation is carried out in Python and optimal results are obtained in comparative analysis with existing techniques. The accuracy obtained by proposed technique is enhanced and the error rate of the design is minimized.

Collateral and asymmetric information in lending markets

We study the benefits and costs of collateral requirements in bank lending markets with asymmetric information. We estimate a structural model of firms’ credit demand for secured and unsecured loans, banks’ contract offering and pricing, and firm default using credit registry data in a setting where asymmetric information problems are pervasive. We provide evidence that collateral mitigates adverse selection and moral hazard. With counterfactual experiments, we quantify how an adverse shock to collateral values propagates to credit supply, credit allocation, interest rates, default, bank profits, and document the relative importance of banks’ pricing and rationing in response to this shock.

Culture, Lending Relationships, and the Cost of Credit

AbstractWe provide evidence on how cultural differences affect loan pricing by using a unique data set from the Italian Credit Register. We show that immigrants pay more for credit compared with natives and that this difference is smaller for immigrants who have Italian parents and for those belonging to the Christian religion. Furthermore, we find that the gap between immigrants and natives narrows as the amount of information shared among lenders through the credit register increases. This suggests that most of the higher cost of credit paid by immigrants is due to statistical discrimination rather than taste-based discrimination. (JEL G21, J15, J71)

Distributional Consequences of Monetary Policy Across Races: Evidence from the U.S. Credit Register

Distributional Consequences of Monetary Policy Across Races: Evidence from the U.S. Credit Register

Gender Diversity in Bank Boardrooms and Green Lending: Evidence from Euro Area Credit Register Data

Gender Diversity in Bank Boardrooms and Green Lending: Evidence from Euro Area Credit Register Data

Gender diversity in bank boardrooms and green lending: Evidence from euro area credit register data

Gender diversity in bank boardrooms and green lending: Evidence from euro area credit register data

FINANCIAL ACCELERATOR AND BANK EXCESS LIQUIDITY IN CEMAC ZONE

In this paper, we broaden the debate on the determinants of bank excess liquidity by focusing on a new mechanism. Using time series data from six CEMAC countries and using shock simulation in a structural VAR as well as Cointegration analysis in an ARDL model, the empirical analysis shows that the financial rigidity caused by the increase in the information asymmetry premium leads to a fall in investment which weakens economic activity. The fall in economic activity amplifies the increase in information asymmetry premium resulting in an increase of free reserves. Finally when the effect of the financial accelerator is reduced by stretching the information asymmetry premium towards zero, then the refunding policy through calls to tender favors a decrease of interest rates, a profusion of credit and consequently the increase of investments and consumption. We suggest all measures aimed at reducing the asymmetry of information on the credit market, in particular, the creation of credit offices and / or public credit registers, the creation of rating agencies for companies and individuals, improvement of the quality of institutions whose poor quality leads to the camoufl age of information and moral hazards.