Liesbeth Bruynseels
Katholieke Universiteit Leuven
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Featured researches published by Liesbeth Bruynseels.
decision support systems | 2008
David Martens; Liesbeth Bruynseels; Bart Baesens; Marleen Willekens; Jan Vanthienen
The auditor is required to evaluate whether substantial doubt exists about the client entitys ability to continue as a going concern. Accounting debacles in recent years have shown the importance of proper and thorough audit analysis. Since the 80s, many studies have applied statistical techniques, mainly logistic regression, as an automated tool to guide the going concern opinion formulation. In this paper, we introduce more advanced data mining techniques, such as support vector machines and rule-based classifiers, and empirically investigate the ongoing discussion concerning the sampling methodology. To provide specific audit guidelines, we infer rules with the state-of-the-art classification technique AntMiner+, which are subsequently converted into a decision table allowing for truly easy and user-friendly consultation in every day audit business practices.
decision support systems | 2018
Jasmien Lismont; Eddy Cardinaels; Liesbeth Bruynseels; Sander De Groote; Bart Baesens; Wilfried Lemahieu; Jan Vanthienen
Abstract This study predicts tax avoidance by means of social network analytics. We extend previous literature by being the first to build a predictive model including a larger variation of network features. We construct a network of firms connected through shared board membership. Then, we apply three analytical techniques, logistic regression, decision trees, and random forests; to create five models using either firm characteristics, network characteristics or different combinations of both. A random forest including firm characteristics, network characteristics of firms and network characteristics of board members provides the best performance with a minimal increase of 7 pp in AUC. Hence, including network effects significantly improves the predictive ability of tax avoidance models, implying that board members exhibit specific knowledge which can carry over across firms. We find that having board members with no connections to low-tax companies lowers the likelihood of being a low-tax firm. Similarly, the higher the average tax rate of the companies a board member is connected to, the lower the chance of being low-tax. On the other hand, being connected to more low-tax firms increases the probability of being low-tax. Consistent with prior literature on firm-specific variables, PP&E has a positive influence on the probability of being low-tax, while EBITDA has a negative effect. Our results are informative for companies as to the director expertise they want to attract in their boards. Additionally, financial analysts and regulatory agencies can use our insights to predict which firms are likely to be low-tax and potentially at risk.
The Accounting Review | 2014
Liesbeth Bruynseels; Eddy Cardinaels
Auditing-a Journal of Practice & Theory | 2011
Liesbeth Bruynseels; W. Robert Knechel; Marleen Willekens
Accounting Organizations and Society | 2012
Liesbeth Bruynseels; Marleen Willekens
Archive | 2006
Liesbeth Bruynseels; Marleen Willekens
Auditing-a Journal of Practice & Theory | 2013
Liesbeth Bruynseels; W. Robert Knechel; Marleen Willekens
Archive | 2009
Liesbeth Bruynseels; Marleen Willekens
The Accounting Review | 2018
Mathijs Van Peteghem; Liesbeth Bruynseels; Ann Gaeremynck
Proceedings of 31st European Accounting Association Annual Conference.31st European Accounting Association Annual Conference | 2007
Liesbeth Bruynseels; W. Robert Knechel; Luk Warlop; Marleen Willekens