| Detection of automobile insurance fraud with discrete choice models and misclassified claims M Artís, M Ayuso, M Guillén Journal of Risk and Insurance 69 (3), 325-340, 2002 | 264 | 2002 |
| Predicting motor insurance claims using telematics data—XGBoost versus logistic regression J Pesantez-Narvaez, M Guillen, M Alcañiz Risks 7 (2), 70, 2019 | 237 | 2019 |
| Kernel density estimation for heavy-tailed distributions using the Champernowne transformation T Buch-Larsen, JP Nielsen, M Guillén, C Bolancé Statistics 39 (6), 503-516, 2005 | 229 | 2005 |
| Predictive modeling applications in actuarial science EW Frees, RA Derrig, G Meyers Cambridge University Press, 2014 | 224 | 2014 |
| Modelling different types of automobile insurance fraud behaviour in the Spanish market M Artıs, M Ayuso, M Guillen Insurance: Mathematics and Economics 24 (1-2), 67-81, 1999 | 197 | 1999 |
| Employing transaction aggregation strategy to detect credit card fraud S Jha, M Guillen, JC Westland Expert systems with applications 39 (16), 12650-12657, 2012 | 191 | 2012 |
| Improving automobile insurance ratemaking using telematics: incorporating mileage and driver behaviour data M Ayuso, M Guillen, JP Nielsen Transportation 46 (3), 735-752, 2019 | 186 | 2019 |
| Risk classification for claim counts: A comparative analysis of various zeroinflated mixed Poisson and hurdle models JP Boucher, M Denuit, M Guillén North American Actuarial Journal 11 (4), 110-131, 2007 | 173 | 2007 |
| Strategies for detecting fraudulent claims in the automobile insurance industry S Viaene, M Ayuso, M Guillen, D Van Gheel, G Dedene European journal of operational research 176 (1), 565-583, 2007 | 162 | 2007 |
| The use of telematics devices to improve automobile insurance rates M Guillen, JP Nielsen, M Ayuso, AM Pérez‐Marín Risk analysis 39 (3), 662-672, 2019 | 147 | 2019 |
| Beyond value‐at‐risk: GlueVaR distortion risk measures J Belles‐Sampera, M Guillén, M Santolino Risk Analysis 34 (1), 121-134, 2014 | 141 | 2014 |
| Number of accidents or number of claims? An approach with zero‐inflated Poisson models for panel data JP Boucher, M Denuit, M Guillen Journal of Risk and Insurance 76 (4), 821-846, 2009 | 141 | 2009 |
| Kernel density estimation of actuarial loss functions C Bolancé, M Guillen, JP Nielsen Insurance: Mathematics and Economics 32 (1), 19-36, 2003 | 138 | 2003 |
| Uplift random forests L Guelman, M Guillén, AM Pérez-Marín Cybernetics and Systems 46 (3-4), 230-248, 2015 | 136 | 2015 |
| Models of insurance claim counts with time dependence based on generalization of Poisson and negative binomial distributions JP Boucher, M Denuit, M Guillén Variance 2 (1), 135-162, 2008 | 130 | 2008 |
| de Catalunya DS de la Generalitat Rapid diagnostic circuit (CDR) of lung, colorectal, breast, bladder and …, 2005 | 130 | 2005 |
| Percepción del estado de salud en varones y mujeres en las últimas etapas de la vida E Séculi, J Fusté, P Brugulat, S Juncá, M Rué, M Guillén Gaceta sanitaria 15 (3), 217-223, 2001 | 128 | 2001 |
| The impact of traffic violations on the estimated cost of traffic accidents with victims M Ayuso, M Guillén, M Alcañiz Accident Analysis & Prevention 42 (2), 709-717, 2010 | 122 | 2010 |
| Bringing cost transparency to the life annuity market C Donnelly, M Guillén, JP Nielsen Insurance: Mathematics and Economics 56, 14-27, 2014 | 119 | 2014 |
| Time-varying effects in the analysis of customer loyalty: A case study in insurance M Guillén, JP Nielsen, TH Scheike, AM Pérez-Marín Expert systems with Applications 39 (3), 3551-3558, 2012 | 119 | 2012 |
