On the Evaluation of Greek Industrial SME's Performance via Multicriteria Analysis of Financial Ratios

The objective of this article is to propose a methodological framework for developing evaluation models for estimating SMEs' performance, based on financial ratio analysis. The proposed framework involves the application of a multiple criteria decision aid method, namely the UTADIS method (UTilités Additives DIScriminantes), to develop a decision model that classifies the SMEs into predefined homogeneous classes according to their performance. The applicability and the efficiency of this approach are examined using financial data on Greek industrial SMEs for the period 1988–1996. A comparison with well-known multivariate and econometric techniques (i.e., discriminant, logit, probit analysis) is also undertaken for comparative purposes.     

Using client performance measures to identify pre-engagement factors associated with qualified audit reports in Greece

The purpose of this paper is to test the extent to which client (corporate) performance measures can be used to enhance the ability to discriminate between the choice of a qualified or unqualified (clean) audit report. Audit firms face the risk of losing the client if they issue a qualification. On the other hand, failing to qualify exposes the auditor to potential lawsuits and loss of reputation. We examined the financial statements, auditors' opinions, and financial statements notes for companies in Greece that received a qualified audit report and for those that received an unqualified audit report. We modeled the auditor's qualification using a multicriteria decision aid classification method (UTADIS—UTilités Additives Discriminates) and compared it with other multivariate statistical techniques such as discriminant and logit analysis. The qualification decision is explained by financial ratios and by nonfinancial information such as the client litigation. The developed models are accurate in classifying the total sample correctly with rates of almost 80%.     

A comparison of nearest neighbours,discriminant and logit models for auditing decisions

This study investigates the efficiency of k-nearest neighbours (k-NN) in developing models for estimating auditors' opinions, as opposed to models developed with discriminant and logit analyses. The sample consists of 5276 financial statements, out of which 980 received a qualified audit opinion, obtained from 1455 private and public UK companies operating in the manufacturing and trade sectors. We develop two industry-specific models and a general one using data from the period 1998–2001, which are then tested over the period 2002–2003. In each case, two versions of the models are developed. The first includes only financial variables. The second includes both financial and non-financial variables. The results indicate that the inclusion of credit rating in the models results in a considerable increase both in terms of goodness of fit and classification accuracies. The comparison of the methods reveals that the k-NN models can be more efficient, in terms of average classification accuracy, than the discriminant and logit models. Finally, the results are mixed concerning the development of industry-specific models, as opposed to general models. Copyright © 2007 John Wiley & Sons, Ltd.     

The impact of bank regulations, supervision, market structure, and bank characteristics on individual bank ratings: A cross-country analysis

We use country level data and bank level data from 71 countries and 857 banks to investigate the impact of bank regulations, supervision, market structure, and bank characteristics on individual bank ratings. The results indicate that less cost efficient banks, with higher than average levels of provisions relatively to their income, and lower liquidity tend to have lower ratings. Larger and more profitable banks tend to obtain higher ratings. Higher equity to assets ratio results in higher ratings only when we do not control for bank supervision and regulations. Capital requirements, restrictions on bank activities, official disciplinary power, explicit deposit insurance scheme, higher deposit insurer power, liquidity and diversification guidelines, entry requirements, fraction of entries denied, and economic freedom have a significant impact on ratings in all of our specifications. Disclosure requirements and foreign banks entry have a significant impact on ratings only when we simultaneously control for the regulatory environment and the market structure, while auditing requirements have a significant impact only when we control for the regulatory environment alone. Finally, banks in developed countries are assigned higher ratings. However, this impact disappears when we include the regulatory and supervision variables in the models.     

Regulations, Supervision Approaches and Acquisition Likelihood in the Asian Banking Industry

We investigate the association between the regulatory and supervision framework and the likelihood of being involved in acquisitions either as acquirer or target in the Asian banking industry over the period 1998–2004. The sample consists of 473 commercial banks operating in 9 markets, a total of 2,693 yearly observations. We use information from the new database of the World Bank and examine various regulations such as the level of accounting and information disclosure requirements, the restrictions on bank activities, the degree of official disciplinary power, and capital adequacy requirements. Our results suggest that the latter two influenced the probability of becoming a target or acquirer; however, restriction on activities and disclosure requirements had no impact on the acquisition likelihood.     

Detecting falsified financial statements: a comparative study using multicriteria analysis and multivariate statistical techniques

Falsifying financial statements involves the manipulation of financial accounts by overstating assets, sales and profit, or understating liabilities, expenses or losses. This paper explores the effectiveness of an innovative classification methodology in detecting firms that issue falsified financial statements (FFS) and the identification of the factors associated to FFS. The methodology is based on the concepts of multicriteria decision aid (MCDA) and the application of the UTADIS classification method (UTilités Additives DIScriminantes). A sample of 76 Greek firms (38 with FFS and 38 non-FFS) described over ten financial ratios is used for detecting factors associated with FFS. A jackknife procedure approach is employed for model validation and comparison with multivariate statistical techniques, namely discriminant and logit analysis. The results indicate that the proposed MCDA methodology outperforms traditional statistical techniques which are widely used for FFS detection purposes. Furthermore, the results indicate that the investigation of financial information can be helpful towards the identification of FFS and highlight the importance of financial ratios such as the total debt to total assets ratio, the inventories to sales ratio, the net profit to sales ratio and the sales to total assets ratio.