The purpose of the present study is the development of classification models that could be used in the identification of acquirers and targets in the Asian banking sector. We use a sample of 52 targets and 47 acquirers that were involved in acquisitions in 9 Asian banking markets during...

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...

The present study investigates the efficiency of four classification techniques, namely discriminant analysis, logit analysis, UTADIS multicriteria decision aid, and nearest neighbours, in the development of classification models that could assist auditors during the examination of Asian...

In this paper we use a sample of 894 banks from 79 countries to develop a multicriteria decision aid model, for the classification of banks in three groups on the basis of their soundness. The model is developed with the UTADIS method, through a ten-fold cross-validation procedure using six...

This study investigates the efficiency of k-Nearest Neighbours (k-NN) in developing models for estimating auditors' opinion, as opposed to models developed with discriminant and logit analyses. The sample consists of 5,276 financial statements, out of which 980 received a qualified audit...

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...

All UK companies are required by company law to prepare financial statements that must comply with law and accounting standards. With the exception of very small companies, financial accounts must then be audited by UK registered auditors who must express an opinion on whether these statements...

In this paper, we investigate the relative performance of both linear and non-linear support vector machines (SVMs) models with a polynomial and an RBF kernel in the development of classification models for the prediction of EU bank acquisition targets. The training sample consists of 274 banks,...

We propose a holistic evaluation framework that banks could adopt when screening corporate entities. The framework is based on the development of a composite indicator of social, environmental and financial performance. This integrated view of evaluation is conceptually aligned with ISO...