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This paper investigates the effect of entrepreneurial orientation (EO) on small- and medium-sized enterprises' (SMEs) access to credit. Starting with the idea that SMEs' strategy-making process, structures and behaviour can favour credit access, the authors also explore the moderating role of bank lending technologies in shaping this relationship.

This study relies on a unique survey of Austrian and Italian SMEs which contains detailed information on access to credit, EO dimensions, relationship lending and firm-level characteristics. The authors perform stepwise logistic regressions to assess whether EO interacts with SME's access to finance, and how relationship lending enhances this relationship.

Proactiveness, autonomy and competitive aggressiveness are important constructs for improving access to bank financing. Those dimensions became more important when a relationship bank is involved, suggesting a role for relationship lending in overcoming SMEs' opaqueness. In addition, relationship lending is crucial for innovative SMEs in overcoming credit denial rates.

The small sample did not allow to analyse the effect of EO on discouraged borrowers. Furthermore, alternative measures of relationship lending (such as geographical proximity or the length of the relationship) and the share of credit granted by the relationship bank would have been interesting to further validate our results.

This study shows that EO dimensions and the type of lending technology are relevant for the financial success of SMEs. More precisely, the authors show that diversity within the banking system helps innovative, autonomous, proactive and competitive SMEs. These important pieces of soft information are injected into the final lending decision when a relationship bank is involved. The evidence suggests the need for SMEs to interact with local banks to fully exploit their EO posture.

To the authors' knowledge, this paper is the first attempt to analyse whether relationship lending can affect the EO–credit access relation.

This study aims to investigate whether social capital mediates the impact of financial capital on business performance in Cameroon.

The study uses quantitative data collected from 370 small businesses in Yaoundé and Douala in Cameroon. All businesses in the sample are formally registered and are in the services sector. A structural equation modelling (SEM) approach is used for the analysis.

Structural and relational capital constraints are significant mediators of formal and informal finance. The magnitude effects of relational capital are the largest, underlining information's importance in resolving small and medium enterprises’ (SMEs') financial constraints. In addition, the effect of informal finance constraints on business performance is larger in magnitude, confirming the substantial impact of informal finance on SME operations.

The paper confirms that relational and structural social capital are vital in business. However, the study did not investigate the disaggregated effects of these dimensions of social capital. Furthermore, how SMEs transition between formal and informal finance could provide further understanding of the role of social capital. A disaggregated and panel data set would help to provide additional insights.

Social capital emerges as a pivotal factor in enhancing SME access to finance. The results, therefore, confirm the relevance of a holistic approach to easing financial capital constraints for SMEs and enabling small businesses to connect more to various stakeholders to amplify business performance. In addition, the findings identified some intervention points for the governments in Cameroon as it seeks to use SMEs as its pivot for development and to catapult itself to emerging economy status in its Cameroon 2035 vision.

The value of the study lies in assessing the mediating effect of cognitive, relational and structural social capital constraints on business performance and comparing the effect of formal and informal financial constraints on business performance.

The National Pension Service (NPS) of Korea suddenly announced that they would suspend their stock lending business from October 22, 2018. Using this ideal setting, the authors investigate the effects of this suspension on market quality and short-selling activities. The authors find that stock return does not increase after the suspension of stock lending for both the KOSPI and KOSDAQ markets. However, the returns of stocks with NPS ownership decline less than those without NPS ownership. The authors also find that the institutional and foreign investors' short sales did not increase in both markets after the lending business suspension by the NPS. In addition, the effect of suspension of stock lending on market quality is mixed, so the authors cannot conclude that market quality has improved. Overall, the authors’ results indicate that the stock market, especially for short-sales activity, has not been affected by the suspension of the stock lending service by the NPS.

Decentralized finance (DeFi), enabled by blockchain, could bring about a new financial system, where peers will interact directly, with little or no place for traditional intermediation. However, some crucial tasks cannot be left solely to an algorithm and, consequently, most DeFi applications still require human decisions. The aim of this research is to assess the role of intermediation in the light of DeFi, analysing how humans and algorithms will interact.

The authors based their work on a twofold qualitative methodology, first analysing publicly available secondary data, particularly from white papers and DeFi Pulse (a website providing data on DeFi solutions) and then running two focus group discussions.

DeFi does not eliminate financial intermediation, but enables it to be performed in new ways, where decentralization means that no single entity can hold too much power or monopoly. DeFi has, however, inherited risks from the underlying technologies that unintentionally facilitate illegal behaviour and can hamper the authorities’ supervision. The complex duality algorithm- vs human-based actions will not be solved indisputably in favour of the former, as DeFi solutions can range from requiring algorithms to play a dominant role, to enabling greater human interaction by actively involving more people.

This research contributes to the emerging debate between algorithm- and human-based intermediation, especially in relation to the standing literature on financial intermediation, where considerations made in the light of the newest theories on blockchain and DeFi are still scarce.

The purpose of this study is to document how a central bank can perform its primary and secondary functions in a Sharīʿah-compliant manner. It also seeks to investigate the outcomes of the experiments of Muslim-majority countries in this regard.

As a first step, a detailed review of existing literature is conducted, which discusses the views of scholars and practitioners on the central banking mechanism in a fully Sharīʿah-compliant financial system. Moving further, the case studies of Iran, Sudan and Pakistan are presented to highlight experiences of regulators from three Muslim-majority countries, which aimed to achieve full compliance with Sharīʿah (Islamic law) principles related to Islamic finance. To evaluate their models, an assessment of their practices is performed in the light of Sharīʿah rules and principles based on existing literature. Finally, the issues involved in establishing a Sharīʿah-compliant central bank (SCCB) are discussed and improvements are suggested.

It is found that Iran played an effective role in pursuing broader objectives of monetary policy by setting priorities for credit allocation and assisting the government in reducing expenses; however, with respect to instruments, its experience is limited to the rebranding of conventional products. Sudan has not only used monetary policy to effectively curb inflation but also it has introduced various indirect instruments to perform monetary operations. Pakistan succeeded in formulating a theoretical roadmap to establish a SCCB but the desired objectives could not be achieved because of multiple factors.

This study has important policy implications for regulators and policymakers from Muslim countries, who can use the findings in shaping effective Sharīʿah-compliant central banking practices in their respective countries.

This study discusses the salient features of an important Islamic financial institution, the central bank and evaluates the experiments of three Muslim-majority countries in implementing Sharīʿah-compliant central banking practices. To the best of the knowledge, this evaluation has not been performed in the existing literature and the present study fills in this gap.

Banks are institutions that inject money in the economy and help to boost it when there are problems in some markets, especially in productive sectors. In this way, analysing the competition in this sector is an important tool for policymakers as non-competitive behaviour could affect the financial system and economy. The purpose of this paper is to measure the degree of competition in the Ecuadorian private banking sector divided by size, from 2000 to 2015, using panel data collected by the official regulator institution.

The authors applied the model proposed by Panzar and Rosse (1987) and its H-statistic using a reduced price and revenue equation estimated by pooled ordinary least squares, fixed effects, random effects, feasible generalised fixed effects and panel correction standard errors (PCSE).

The authors show that given the presence of some problems in data such as heteroskedasticity and autocorrelation, the most appropriate technique is PCSE. The authors also found robust evidence supporting that large banks compete in a monopolistic market, small and medium-sized banks operate in monopolistic competition, and Ecuadorian small, medium-sized and large banks stay in long-run equilibrium.

This paper contributes to the actual literature of competition degree in two ways. First, different from traditional papers, we do not control by size; so, we divided the analysis by size, because in Ecuador and also in many developing countries, bank’s competition is different for each group of size because the levels of liquidity, risk and other indicators are different from one group to another. Second, we show the robustness of the results using a scaled and unscaled equation, using many controls and using five methods to contrast the competition degree.

Loan default risk or credit risk evaluation is important to financial institutions which provide loans to businesses and individuals. Loans carry the risk of being defaulted. To understand the risk levels of credit users (corporations and individuals), credit providers (bankers) normally collect vast amounts of information on borrowers. Statistical predictive analytic techniques can be used to analyse or to determine the risk levels involved in loans. This paper aims to address the question of default prediction of short-term loans for a Tunisian commercial bank.

The authors have used a database of 924 files of credits granted to industrial Tunisian companies by a commercial bank in the years 2003, 2004, 2005 and 2006. The naive Bayesian classifier algorithm was used, and the results show that the good classification rate is of the order of 63.85 per cent. The default probability is explained by the variables measuring working capital, leverage, solvency, profitability and cash flow indicators.

The results of the validation test show that the good classification rate is of the order of 58.66 per cent; nevertheless, the error types I and II remain relatively high at 42.42 and 40.47 per cent, respectively. A receiver operating characteristic curve is plotted to evaluate the performance of the model. The result shows that the area under the curve criterion is of the order of 69 per cent.

The paper highlights the fact that the Tunisian central bank obliged all commercial banks to conduct a survey study to collect qualitative data for better credit notation of the borrowers.

El riesgo de incumplimiento de préstamos o la evaluación del riesgo de crédito es importante para las instituciones financieras que otorgan préstamos a empresas e individuos. Existe el riesgo de que el pago de préstamos no se cumpla. Para entender los niveles de riesgo de los usuarios de crédito (corporaciones e individuos), los proveedores de crédito (banqueros) normalmente recogen gran cantidad de información sobre los prestatarios. Las técnicas analíticas predictivas estadísticas pueden utilizarse para analizar o determinar los niveles de riesgo involucrados en los préstamos. En este artículo abordamos la cuestión de la predicción por defecto de los préstamos a corto plazo para un banco comercial tunecino.

Utilizamos una base de datos de 924 archivos de créditos concedidos a empresas industriales tunecinas por un banco comercial en 2003, 2004, 2005 y 2006. El algoritmo bayesiano de clasificadores se llevó a cabo y los resultados muestran que la tasa de clasificación buena es del orden del 63.85%. La probabilidad de incumplimiento se explica por las variables que miden el capital de trabajo, el apalancamiento, la solvencia, la rentabilidad y los indicadores de flujo de efectivo.

Los resultados de la prueba de validación muestran que la buena tasa de clasificación es del orden de 58.66% ; sin embargo, los errores tipo I y II permanecen relativamente altos, siendo de 42.42% y 40.47%, respectivamente. Se traza una curva ROC para evaluar el rendimiento del modelo. El resultado muestra que el criterio de área bajo curva (AUC, por sus siglas en inglés) es del orden del 69%.

El documento destaca el hecho de que el Banco Central tunecino obligó a todas las entidades del sector llevar a cabo un estudio de encuesta para recopilar datos cualitativos para un mejor registro de crédito de los prestatarios.

Curva ROC, Evaluación de riesgos, Riesgo de incumplimiento, Sector bancario, Algoritmo clasificador bayesiano.

Artículo de investigación