The value of qualitative information in SME Risk Management

Original by Altman, Sabato, Wilson, 2008, 40 pages 

This summary note was Posted on

The Journal of Credit Risk (1–33) Volume 6/Number 2, Summer 2010

  • Shumway (2001) argues that the use of static models with multi-period data leads to estimates which are biased, inconsistent and inefficient and proposes the use of discrete time hazard model
  • B.Headd (2003) finds that only one-third of new businesses (33%) closed under circumstances that owners considered unsuccessful
  • Hudson (1987) studying UK companies between 1978-1981 find that young companies form the majority of the liquidated companies and that a company needs at least 9 years to be regarded as established. Point out that newly formed company is most likely to have a honey moon period of around 2 years before being in real risk
  • Use total asset values to control for company size
  • Rather than using industrial sector dummy variables use weight of evidence variable which expresses the previous years’ sector failure rate
  • Addition of non-accounting (qualitative) data to the basic Z-score model significantly improves the classification performance
  • The late filing of accounts is associated with a higher probability of failure. (variable no cash flow statement)
  • Subsidiaries are less likely than non-subsidiaries because they have access to the financial and other resources of the parent company and can survive poor financial performance for longer than non-subsidiaries
  • There is a non-linearity between probability of insolvency and size as measured by asset value
  • Control of industry factor is significant and picks up the effects of average sector level failure
  • Having liquidity and cash is associated with lower PD
  • Smaller subsidiaries are not supported by parent in the same way as larger ones
  • The addition of qualitative information improved accuracy by 13% (AUC 0.67->0.76)
  • Can update qualitative information frequently to better re-estimate the PD over time