Academic journal article Academy of Accounting and Financial Studies Journal

Operating Cash Flow and Creditworthiness Assessment

Academic journal article Academy of Accounting and Financial Studies Journal

Operating Cash Flow and Creditworthiness Assessment

Article excerpt


The success of a business failure prediction model lies in its ability to assess firm creditworthiness given a limited information set. In this way, these models can reduce monitoring costs (Resti, Sironi, 2007) but may cause an inadequate assessment of the potential for smaller companies (Berger and Udell, 2002). In addition, although there are numerous models of business failure prediction in the literature, only some of them specifically consider the use of cash flows to predict financial distress (Gentry et al., 1985; Gilbert et al., 1990; Charitou et al., 2004). Information related to cash flow movements provides, in effect, a dynamic vision of firm management unlike financial ratios, which show only a static point of view. The aim of this work is, therefore, to test whether the use of operating cash flow information can lead to a significant improvement in the performance of business failure prediction models, with particular reference to Italian SMEs, which constitute the backbone of the Italian economy. This research differs from prior studies in the following respects.

First, default in this study is defined as a situation of temporary and slight financial distress not serious enough to generate substandard loans and bad debts. This definition differs both from the regulatory concept of default and from the definition used by most of the models in the literature, which are related to bankruptcy, insolvency or liquidation (Altman and Hotchkiss, 2006). This choice is motivated by the fact that insolvent firms present serious liquidity problems and could, out of necessity, compensate for the reduction of net working capital flow by acting on business cycle maturities and generating variable cash flows, which are not suitable for the aim of this research.

Second, the classification of financial distress is objective, carried out by cluster analysis and is not based on the judgments of banks themselves.

The third aspect is the development of a model that combines cash flow ratios and financial ratios with reference to small- and medium-sized Italian enterprises. Logistic regression analysis is employed using a stepwise variable selection process.

The study is structured as follows. Section 2 provides a literature review. Section 3 presents the research design. Section 4 shows the empirical results, and section 5 sets out the main conclusions.


The first attempts to use the behaviour of financial ratios for predictive purposes are based on statistical univariate approaches, characterised by the separate observations of various financial ratios in the years immediately prior to the bankruptcies of companies compared with those of sound firms (Hickman, 1957; Saulnier, 1968). In this context, Beaver (1966) showed that 5 years prior to bankruptcy, insolvent companies presented a decrease in sales volume, a decrease in cash flow and income levels and growing debt compared to healthy companies. The univariate techniques' inability to simultaneously grasp the interrelationships between the various indicators led to the need to introduce multivariate statistical techniques. Altman (1968), using multivariate discriminant analysis, found that the financial ratios of healthy companies were different from those of insolvent ones and that this diversity became progressively stronger as the date of bankruptcy approached. Since the initial work of Altman, the number and complexity of studies on business failure prediction have seen an exponential increase. From the work of Beaver until 2007, there were more than 165 related models published in English alone (Bellovary et al., 2007).

Differences among the business failure prediction models can be found in a) the input variables, b) the temporal horizon, c) the statistical approaches and d) the definition of default.

With reference to the input variables, the theory does not uniquely define a framework for the financial ratios that is better able to predict default. …

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