| Some recent developments in non-linear time series modelling, testing, and forecasting JG De Gooijer, K Kumar International Journal of Forecasting 8 (2), 135-156, 1992 | 323 | 1992 |
| Business failure prediction using decision trees A Gepp, K Kumar, S Bhattacharya Journal of forecasting 29 (6), 536-555, 2010 | 213 | 2010 |
| Artificial neural network vs linear discriminant analysis in credit ratings forecast: A comparative study of prediction performances K Kumar, S Bhattacharya Review of Accounting and Finance 5 (3), 216-227, 2006 | 183 | 2006 |
| Predicting financial distress: A comparison of survival analysis and decision tree techniques A Gepp, K Kumar Procedia Computer Science 54, 396-404, 2015 | 167 | 2015 |
| The role of survival analysis in financial distress prediction A Gepp, K Kumar International research journal of finance and economics 16 (16), 13-34, 2008 | 164 | 2008 |
| Neural vs. statistical classifier in conjunction with genetic algorithm based feature selection P Zhang, B Verma, K Kumar Pattern Recognition Letters 26 (7), 909-919, 2005 | 149 | 2005 |
| A review of money laundering literature: the state of research in key areas M Tiwari, A Gepp, K Kumar Pacific Accounting Review 32 (2), 271-303, 2020 | 96 | 2020 |
| Detection of financial distress via multivariate statistical analysis S Gamesalingam, K Kumar Managerial Finance 27 (4), 45-55, 2001 | 90 | 2001 |
| An ANN-based auditor decision support system using Benford's law S Bhattacharya, D Xu, K Kumar Decision support systems 50 (3), 576-584, 2011 | 65 | 2011 |
| Financial distress prediction of Islamic banks using tree-based stochastic techniques K Halteh, K Kumar, A Gepp Managerial Finance 44 (6), 759-773, 2018 | 59 | 2018 |
| The future of raising finance-a new opportunity to commit fraud: a review of initial coin offering (ICOs) scams M Tiwari, A Gepp, K Kumar Crime, Law and Social Change 73, 417-441, 2020 | 57 | 2020 |
| Forecasting credit ratings Using ANN and statistical techniques K Kumar, JD Haynes International journal of business studies 11 (1), 91-108, 2003 | 56 | 2003 |
| Employee perceptions of organization culture with respect to fraud–where to look and what to look for K Kumar, S Bhattacharya, R Hicks Pacific Accounting Review 30 (2), 187-198, 2018 | 53 | 2018 |
| A neural-genetic algorithm for feature selection and breast abnormality classification in digital mammography P Zhang, B Verma, K Kumar 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No …, 2004 | 45 | 2004 |
| A comparative analysis of decision trees vis-a-vis other computational data mining techniques in automotive insurance fraud detection A Gepp, JH Wilson, K Kumar, S Bhattacharya Journal of data science 10 (3), 537-561, 2012 | 44 | 2012 |
| Business failure prediction using statistical techniques: A review A Gepp, K Kumar Some recent developments in statistical theory and applications 1, 1-25, 2012 | 42 | 2012 |
| Changing the landscape of higher education: From standardized learning to customized learning SK Sharma, SCJ Palvia, K Kumar Journal of Information Technology Case and Application Research 19 (2), 75-80, 2017 | 41 | 2017 |
| On the identification of some bilinear time series models K Kumar Journal of time séries analysis 7 (2), 117-122, 1986 | 38 | 1986 |
| Credit rating forecasting using machine learning techniques M Wallis, K Kumar, A Gepp Managerial perspectives on intelligent big data analytics, 180-198, 2019 | 34 | 2019 |
| A computational exploration of the efficacy of Fibonacci Sequences in technical analysis and trading S Bhattacharya, K Kumar Annals of Economics and Finance 7 (1), 185, 2006 | 33 | 2006 |
Sukanto BhattacharyaDeakin Business School, Deakin UniversityVerified email at deakin.edu.au
