Bankruptcy Prediction of Small and Medium Enterprises Using a Flexible Binary Generalized Extreme Value Model

We introduce a binary regression accounting-based model for bankruptcy prediction of small and medium enterprises (SMEs). The main advantage of the model lies in its predictive performance in identifying defaulted SMEs. Another advantage, which is especially relevant for banks, is that the relationship between the accounting characteristics of SMEs and response is not assumed a priori (e.g., linear, quadratic or cubic) and can be determined from the data. The proposed approach uses the quantile function of the generalized extreme value distribution as link function as well as smooth functions of accounting characteristics to flexibly model covariate effects. Therefore, the usual assumptions in scoring models of symmetric link function and linear or pre-specied covariate-response relationships are relaxed. Out-of-sample and out-of-time validation on Italian data shows that our proposal outperforms the commonly used (logistic) scoring model for different default horizons

Determinants of voluntary audit and voluntary full accounts in micro- and non-micro small companies in the UK

This is an Author's Accepted Manuscript of an article published in Accounting and Business Research, 42(4), 441 - 468, 2012, copyright Taylor & Francis, available online at: http://www.tandfonline.com/10.1080/00014788.2012.667969.This study investigates the link between the auditing and filing choices made by a sample of 592 small private companies, which includes 419 micro-companies. It examines decisions made in connection with the 2006 accounts following UK's adoption of the maximum EU size thresholds in 2004, and the impact of the proposed Directive on the annual accounts of micro-companies. The research extends the model of cost, management and agency factors associated with voluntary audit, and develops a complementary model for voluntary full accounts. The results show the benefits of placing full audited accounts on public record that outweigh the costs for a significant proportion of companies. In non-micro small companies, voluntary audit is determined by cost and agency factors, whereas in micro-companies it is driven by cost, management and agency factors. In both groups, the predictors of voluntary full accounts include management and agency factors, and choosing voluntary audit is one of the key factors. The study provides models that can be tested in other jurisdictions to provide evidence of the needs of micro-companies, and the discussion of the methodological challenges for small company researchers in the UK makes further contribution to the literature

Improving bankruptcy prediction in micro-entities by using nonlinear effects and non-financial variables

The use of non-parametric methodologies, the introduction of non-financial variables, and the development of models geared towards the homogeneous characteristics of corporate sub-populations have recently experienced a surge of interest in the bankruptcy literature. However, no research on default prediction has yet focused on micro-entities (MEs), despite such firms’ importance in the global economy. This paper builds the first bankruptcy model especially designed for MEs by using a wide set of accounts from 1999 to 2008 and applying artificial neural networks (ANNs). Our findings show that ANNs outperform the traditional logistic regression (LR) models. In addition, we also report that, thanks to the introduction of non-financial predictors related to age, the delay in filing accounts, legal action by creditors to recover unpaid debts, and the ownership features of the company, the improvement with respect to the use of solely financial information is 3.6%, which is even higher than the improvement that involves the use of the best ANN (2.6%)

Modeling SMEs Credit Default Risk: The Case of Saudi Arabia

This study assesses the credit risk of small and medium-sized enterprises (SMEs) to minimize unexpected risk events. We construct a hybrid statistical model based on factor analysis and logistic regression to predict enterprise default on loans and determine the factors predicting SMEs default. We assess the credit risk of SMEs listed on the Saudi stock market. The results indicate that the SMEs acid-test ratios are the most influential factors in predicting SMEs credit risk. Therefore, the designed logistic model can be used by financial institutions during the decision-making process of granting loans to SMEs. This study sheds light on challenging access to bank credits due to the lack of financial transparency of most Saudi SMEs

Research on the Application of Blockchain in SMEs Credit Risk

The credit of an enterprise is related to its own development. This paper mainly discusses the relationship between the credit risk of small and medium enterprises (SMEs) and the application degree of blockchain. 64 listed companies with block chain technology as the core theme are selected to analyze their comprehensive financial data. Factor analysis is used to quantitatively evaluate the application degree of blockchain in SMEs, and then the Logistic model is used to evaluate the credit risk of SMEs. Finally, combining the application degree of blockchain in small and medium-sized enterprises and the credit risk assessment of these two groups of data. It confirms the conclusion that the higher the degree of blockchain application, the closer the supply chain finance relationship, and the better the credit status

Hybrid model using logit and nonparametric methods for predicting micro-entity failure

Following the calls from literature on bankruptcy, a parsimonious hybrid bankruptcy model is developed in this paper by combining parametric and non-parametric approaches.To this end, the variables with the highest predictive power to detect bankruptcy are selected using logistic regression (LR). Subsequently, alternative non-parametric methods (Multilayer Perceptron, Rough Set, and Classification-Regression Trees) are applied, in turn, to firms classified as either “bankrupt” or “not bankrupt”. Our findings show that hybrid models, particularly those combining LR and Multilayer Perceptron, offer better accuracy performance and interpretability and converge faster than each method implemented in isolation. Moreover, the authors demonstrate that the introduction of non-financial and macroeconomic variables complement financial ratios for bankruptcy prediction

An empirical study on credit evaluation of SMEs based on detailed loan data

Small and micro-sized Enterprises (SMEs) are an important part of Chinese economic system.The establishment of credit evaluating model of SMEs can effectively help financial intermediaries to reveal credit risk of enterprises and reduce the cost of enterprises information acquisition. Besides it can also serve as a guide to investors which also helps companies with good credit. This thesis conducts an empirical study based on loan data from a Chinese bank of loans granted to SMEs. The study aims to develop a data-driven model that can accurately predict if a given loan has an acceptable risk from the bank’s perspective, or not. Furthermore, we test different methods to deal with the problem of unbalanced class and uncredible sample. Lastly, the importance of variables is analyzed. Remaining Unpaid Principal, Floating Interest Rate, Time Until Maturity Date, Real Interest Rate, Amount of Loan all have significant effects on the final result of the prediction.The main contribution of this study is to build a credit evaluation model of small and micro enterprises, which not only helps commercial banks accurately identify the credit risk of small and micro enterprises, but also helps to overcome creditdifficulties of small and micro enterprises.As pequenas e microempresas constituem uma parte importante do sistema económico chinês. A definição de um modelo de avaliação de crédito para estas empresas pode ajudar os intermediários financeiros a revelarem o risco de crédito das empresas e a reduzirem o custo de aquisição de informação das empresas. Além disso, pode igualmente servir como guia para os investidores, auxiliando também empresas com bom crédito. Na presente tese apresenta-se um estudo empírico baseado em dados de um banco chinês relativos a empréstimos concedidos a pequenas e microempresas. O estudo visa desenvolver um modelo empírico que possa prever com precisão se um determinado empréstimo tem um risco aceitável do ponto de vista do banco, ou não. Além disso, são efetuados testes com diferentes métodos que permitem lidar com os problemas de classes de dados não balanceadas e de amostras que não refletem o problema real a modelar. Finalmente, é analisada a importância relativa das variáveis. O montante da dívida por pagar, a taxa de juro variável, o prazo até a data de vencimento, a taxa de juro real, o montante do empréstimo, todas têm efeitos significativos no resultado final da previsão. O principal contributo deste estudo é, assim, a construção de um modelo de avaliação de crédito que permite apoiar os bancos comerciais a identificarem com precisão o risco de crédito das pequenas e micro empresas e ajudar também estas empresas a superarem as suas dificuldades de crédito

A Comprehensive Survey on Enterprise Financial Risk Analysis: Problems, Methods, Spotlights and Applications

Enterprise financial risk analysis aims at predicting the enterprises' future financial risk.Due to the wide application, enterprise financial risk analysis has always been a core research issue in finance. Although there are already some valuable and impressive surveys on risk management, these surveys introduce approaches in a relatively isolated way and lack the recent advances in enterprise financial risk analysis. Due to the rapid expansion of the enterprise financial risk analysis, especially from the computer science and big data perspective, it is both necessary and challenging to comprehensively review the relevant studies. This survey attempts to connect and systematize the existing enterprise financial risk researches, as well as to summarize and interpret the mechanisms and the strategies of enterprise financial risk analysis in a comprehensive way, which may help readers have a better understanding of the current research status and ideas. This paper provides a systematic literature review of over 300 articles published on enterprise risk analysis modelling over a 50-year period, 1968 to 2022. We first introduce the formal definition of enterprise risk as well as the related concepts. Then, we categorized the representative works in terms of risk type and summarized the three aspects of risk analysis. Finally, we compared the analysis methods used to model the enterprise financial risk. Our goal is to clarify current cutting-edge research and its possible future directions to model enterprise risk, aiming to fully understand the mechanisms of enterprise risk communication and influence and its application on corporate governance, financial institution and government regulation

Essays on SMEs insolvency risk

In light of the new Basel Capital Accord, Small and medium size enterprises (SMEs) play a fundamental role in the economic performance of major economies. Several lending communities proposed to treat SMEs as retail clients to optimize capital requirements and profitability. In this context, it is becoming critically important to have a detailed understanding of its risk behavior for appropriate pricing of credit risk. Thus, this thesis presents four essays on SMEs insolvency risk starting from chapter 3 through chapter 6 that investigates different dimensions of their default risk. My first essay makes distinction among SMEs that report operating cash flow and those which do not while modeling their default risk. However, I do not report any significant improvement in model’s classification performance when operating cash flow information is made available. Similarly, my second essay considers domestic and international SMEs separately while modelling their default risk and report almost identical classifications performance of the models’ developed for both the groups. The third essay compares the default risk attributes of micro, small and medium-sized firms respectively with SMEs. Test results suggest significant difference in the default risk attributes of only micro firms and SMEs. On a different line, my fourth essay deals with the methodological issues that have been witnessed recently in the bankruptcy literature that use hazard models for making bankruptcy predictions. This essay highlights the critical issues and provides appropriate guidance for the correct use of hazard models in making bankruptcy predictions. Here, I also propose a default definition for SMEs which considers both legal bankruptcy laws and firms’ financial health while defining the default event. Empirical results show that my default definition performs significantly better than its respective counterparts in identifying distressed firms with superior goodness of fit measures across all econometric specifications. Detailed abstract of respective essays are as follows.Evidence pertaining to SMEs financing strongly motivates me to believe that firms which are unable to generate sufficient operating cash flow (OCF) are more susceptible to bankruptcy. However, the role of OCF in bankruptcy of SMEs lacks empirical validation. Thus, my first essay (chapter 3) investigates the role of operating cash flow information as predictors in assessing the creditworthiness of SMEs. One-year distress prediction model developed using significant financial information of United Kingdom SMEs over a period of 2000 to 2009 confirm that the presence of operating cash flow information does not improve the prediction accuracy of the distress prediction model.My second essay (chapter 4) considers domestic and international small and medium-sized enterprises (SMEs) of the United Kingdom separately while modelling their default risk. To establish the empirical validation, separate one-year default prediction models are developed using dynamic logistic regression technique that encapsulates significant financial information over an analysis period of 2000 to 2009. Almost an identical set of explanatory variables affect the default probability of domestic and international SMEs, which contradicts the need for separate default risk models. However, the lower predictive accuracy measures of the model developed for international SMEs motivate me to compare the weights of regression coefficients of the models developed for domestic and international firms. Test results confirm that four out of the nine common predictors display significant statistical differences in their weights. However, these differences do not contribute to the discriminatory performance of the default prediction models, given that I report very little difference in each model’s classification performance.A huge diversity exists within the broad category of Small and medium size enterprises (SMEs). They differ widely in their capital structure, firm size, access to external finance, management style, numbers of employees etc. Thus, my third essay (chapter 5) contributes to the literature by acknowledging this diversity while modeling credit risk for them, using a relatively large UK database, covering the analysis period between 2000 and 2009. My analysis partially employs the definition provided by the European Union to distinguish between ‘micro’, ‘small’, and ‘medium’ sized firms. I use both financial and non-financial information to predict firms’ failure hazard. I estimate separate hazard models for each sub-category of SMEs, and compare their performance with a SMEs hazard model including all the three sub-categories. I test my hypotheses using discrete-time duration-dependent hazard rate modelling techniques, which controls for both macro-economic conditions and survival time. My test results strongly highlight the differences in the credit risk attributes of ‘micro’ firms and SMEs, while it does not support the need to consider ‘small’ and ‘medium’ firms’ category separately while modelling credit risk for them, as almost the same sets of explanatory variables affect the failure hazard of SMEs, ‘small’ and ‘medium’ firms.My fourth essay (chapter 6) considers all serious and neglected concerns while developing discrete and continuous time duration dependent hazard models for predicting failure of US SMEs. I compare theoretical and classification performance aspects of three popular hazard models, namely discrete hazard models with logit and clog-log links and the extended Cox model. I report that discrete hazard models are superior to extended Cox models in making default predictions. I also propose a default definition for SMEs which considers both legal bankruptcy laws and firms’ financial health while defining the default event. My empirical results show that my default definition performs significantly better than the default definitions which are only based on legal consequence or firms’ financial health in identifying distressed firms. In addition, my default definition also shows superior goodness of fit measures across all econometric specifications