Competing Risk Model for Technology Credit Fund for Small and Medium‐Sized Enterprises

Despite the need to foster a technology‐intensive industry, most Korean SMEs (small and medium‐sized enterprises) are faced with the difficulty of raising funds. To resolve this problem, the government set up the technology credit fund to give loans to enterprises that achieve a certain technology evaluation score. However, many of the recipient SMEs fail to pay back the loans for various reasons. In this paper, we distinguish two causes of default due to owner and company, respectively, using the competing risk model. The proposed prediction models for competing defaults are expected to contribute to the healthy management of technology finance.

[1]  Abdul Aziz,et al.  Cash Flow Reporting and Financial Distress Models: Testing of Hypotheses , 1989 .

[2]  Jan Svejnar,et al.  Objectives and Constraints of Entrepreneurs: Evidence from Small and Medium Size Enterprises in Russia and Bulgaria , 2000 .

[3]  Y. Kim,et al.  Technology scoring model considering rejected applicants and effect of reject inference , 2007, J. Oper. Res. Soc..

[4]  Ben R. Craig,et al.  On Sba-Guaranteed Lending and Economic Growth , 2004 .

[5]  Tim Oates,et al.  INTRODUCTION: SPECIAL ISSUE ON APPLICATIONS OF GRAMMATICAL INFERENCE , 2008, Appl. Artif. Intell..

[6]  Elisa Lee,et al.  Statistical Methods for Survival Data Analysis: Lee/Survival Data Analysis , 2003 .

[7]  Sancho Salcedo-Sanz,et al.  Genetic programming for the prediction of insolvency in non-life insurance companies , 2005, Comput. Oper. Res..

[8]  Timothy Bates,et al.  An Analysis of Small Business Size and Rate of Discontinuance , 1990 .

[9]  J. Stiglitz,et al.  Credit Rationing in Markets with Imperfect Information , 1981 .

[10]  Sanghoon Kim,et al.  Improved technology scoring model for credit guarantee fund , 2005, Expert Syst. Appl..

[11]  Joseph D. Conklin Classical Competing Risks , 2002, Technometrics.

[12]  Abdul Aziz,et al.  BANKRUPTCY PREDICTION ‐ AN INVESTIGATION OF CASH FLOW BASED MODELS[1] , 1988 .

[13]  F. Chang A Theory of Health Investment Under Competing Mortality Risks , 2002, Journal of health economics.

[14]  Richard B. Carter,et al.  Small Firm Bankruptcy , 2006 .

[15]  Ben R. Craig,et al.  Small Firm Finance, Credit Rationing, and the Impact of SBA‐Guaranteed Lending on Local Economic Growth , 2007 .

[16]  Thomas E. McKee,et al.  Genetic programming and rough sets: A hybrid approach to bankruptcy classification , 2002, Eur. J. Oper. Res..

[17]  Marc Cowling,et al.  Is the Small Firms Loan Guarantee Scheme Hazardous for Banks or Helpful to Small Business? , 2003 .

[18]  Ingoo Han,et al.  Hybrid neural network models for bankruptcy predictions , 1996, Decis. Support Syst..

[19]  Alan E. Gelfand,et al.  Proportional hazards models: a latent competing risk approach , 2000 .

[20]  Gary Anderson,et al.  A Bayesian method on adaptive preventive maintenance problem , 2004, Eur. J. Oper. Res..

[21]  E. Deakin Discriminant Analysis Of Predictors Of Business Failure , 1972 .

[22]  So Young Sohn,et al.  Random effects logistic regression model for default prediction of technology credit guarantee fund , 2007, Eur. J. Oper. Res..

[23]  So Young Sohn,et al.  CASE-BASED REASONING FOR PREDICTING MULTIPERIOD FINANCIAL PERFORMANCES OF TECHNOLOGY-BASED SMEs , 2008, Appl. Artif. Intell..

[24]  Elisa T. Lee,et al.  Statistical Methods for Survival Data Analysis , 1994, IEEE Transactions on Reliability.

[25]  E. Altman,et al.  ZETATM analysis A new model to identify bankruptcy risk of corporations , 1977 .

[26]  P. Allison Survival analysis using the SAS system : a practical guide , 1995 .

[27]  Tim S. Campbell,et al.  The Determinants of Default on Insured Conventional Residential Mortgage Loans , 1983 .

[28]  Ingoo Han,et al.  The discovery of experts' decision rules from qualitative bankruptcy data using genetic algorithms , 2003, Expert Syst. Appl..

[29]  So Young Sohn,et al.  Technology credit scoring model considering both SME characteristics and economic conditions: The Korean case , 2010, J. Oper. Res. Soc..

[30]  T. W. Faulkner Applying ‘Options Thinking’ To R&D Valuation , 1996 .

[31]  Graham Bannock,et al.  Uk Small Business Statistics and International Comparisons , 1985 .

[32]  Ingoo Han,et al.  A case-based reasoning with the feature weights derived by analytic hierarchy process for bankruptcy prediction , 2002, Expert Syst. Appl..

[33]  Maria Stepanova,et al.  Survival Analysis Methods for Personal Loan Data , 2002, Oper. Res..

[34]  Marnik G. Dekimpe,et al.  A modeling framework for analyzing retail store durations , 1991 .

[35]  Michael Svarer,et al.  Mortality and socio-economic differences in Denmark: a competing risks proportional hazard model. , 2005, Economics and human biology.

[36]  Edward I. Altman,et al.  FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY , 1968 .

[37]  So Young Sohn,et al.  Technology scoring model for reflecting evaluator's perception within confidence limits , 2008, Eur. J. Oper. Res..

[38]  Pauline Coolen-Schrijner,et al.  Nonparametric predictive inference in reliability , 2002, Reliab. Eng. Syst. Saf..

[39]  James A. Ohlson FINANCIAL RATIOS AND THE PROBABILISTIC PREDICTION OF BANKRUPTCY , 1980 .

[40]  N. Taneichi,et al.  Semiparametric estimation based on parametric modeling of the cause-specific hazard ratios in competing risks , 2003 .

[41]  P. Pompe,et al.  The prediction of bankruptcy of small- and medium-sized industrial firms , 2005 .

[42]  John Banasik,et al.  Not if but when will borrowers default , 1999, J. Oper. Res. Soc..

[43]  Jim Everett,et al.  Small Business Failure and External Risk Factors , 1998 .

[44]  Pamela K. Coats,et al.  A neural network for classifying the financial health of a firm , 1995 .

[45]  G. Hall,et al.  Factors Associated with Insolvency amongst Small Firms , 1991 .

[46]  B. Scholtens,et al.  Analytical Issues in External Financing Alternatives for SBEs , 1999 .

[47]  Edward I. Altman,et al.  THE PREDICTION OF CORPORATE BANKRUPTCY: A DISCRIMINANT ANALYSIS* , 1968 .

[48]  H NOH,et al.  Prognostic personal credit risk model considering censored information , 2005, Expert Syst. Appl..

[49]  Robert A. Peterson,et al.  Perceived Causes of Small Business Failures: A Research Note , 1983 .

[50]  M. Williams,et al.  Measuring business starts, success and survival: Some database considerations , 1993 .

[51]  So Young Sohn,et al.  Technology credit rating system for funding SMEs , 2011, J. Oper. Res. Soc..

[52]  S. Y. Sohn,et al.  The risk management for technology credit guarantee fund , 2008, J. Oper. Res. Soc..

[53]  Kaplan-Meier representation of competing risk estimates , 1999 .

[54]  M. Zmijewski METHODOLOGICAL ISSUES RELATED TO THE ESTIMATION OF FINANCIAL DISTRESS PREDICTION MODELS , 1984 .

[55]  Bart Baesens,et al.  Using Neural Network Rule Extraction and Decision Tables for Credit - Risk Evaluation , 2003, Manag. Sci..

[56]  David J. Hand,et al.  Lookahead scorecards for new fixed term credit products , 2001, J. Oper. Res. Soc..

[57]  J. Hanley,et al.  The meaning and use of the area under a receiver operating characteristic (ROC) curve. , 1982, Radiology.

[58]  Bert van Wegen,et al.  Understanding and valuing knowledge assets: Overview and method , 1997 .

[59]  M. T Elhadi Bankruptcy support system: taking advantage of information retrieval and case-based reasoning , 2000 .

[60]  D. Kundu,et al.  Analysis of Incomplete Data in Presence of Competing Risks , 2000 .

[61]  G. Mitchell,et al.  Managing R&D as A Strategic Option , 1988 .