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Professor in actuarial data science at the University of Amsterdam (part time) and professor in actuariel science and insurance analytics at KU Leuven (main affiliation).
MSc in Mathematics (KU Leuven, 2003) and PhD in statistics and actuarial science (KU Leuven, 2007).
Campo, B., & Antonio, K. (Accepted/In press). Insurance pricing with hierarchically structured data: an illustration with a workers' compensation insurance portfolio. Scandinavian Actuarial Journal. https://arxiv.org/abs/2206.15244
Crevecoeur, J., Robben, J., & Antonio, K. (2022). A hierarchical reserving model for reported non-life insurance claims. Insurance: Mathematics & Economics, 104, 158-184. https://doi.org/10.1016/j.insmatheco.2022.02.005[details]
Deprez, L., Antonio, K., & Boute, R. (2022). Empirical risk assessment of maintenance costs under full-service contracts. European Journal of Operational Research, 304(2), 476. https://doi.org/10.1016/j.ejor.2022.03.055
Deresa, N. W., Van Keilegom, I., & Antonio, K. (2022). Copula-based inference for bivariate survival data with left truncation and dependent censoring. Insurance: Mathematics and Economics, 107, 1-21. https://doi.org/10.1016/j.insmatheco.2022.07.011[details]
Henckaerts, R., & Antonio, K. (2022). The added value of dynamically updating motor insurance prices with telematics collected driving behavior data. Insurance: Mathematics & Economics, 105, 79. https://doi.org/10.1016/j.insmatheco.2022.03.011
Henckaerts, R., Antonio, K., & Côté, M-P. (2022). When stakes are high: balancing accuracy and transparency with Model-Agnostic Interpretable Data-driven suRRogates. Expert Systems With Applications, 202(117230). https://doi.org/10.1016/j.eswa.2022.117230
Oskarsdottir, M., Ahmed, W., Antonio, K., Baesens, B., Dendievel, R., Donas, T., & Reynkens, T. (2022). Social network analytics for supervised fraud detection in insurance. Risk Analysis, 42(8), 1872. https://doi.org/10.1111/risa.13693
Robben, J., Antonio, K., & Devriendt, S. (2022). Assessing the Impact of the COVID-19 Shock on a Stochastic Multi-Population Mortality Model. Risks, 10(2), [26]. https://doi.org/10.3390/risks10020026[details]
Verbelen, R., Antonio, K., Claeskens, G., & Crevecoeur, J. (2022). Modeling the occurrence of events subject to a reporting delay via an EM algorithm. Statistical Science, 37(3), 394. https://doi.org/10.48550/arXiv.1909.08336
2021
Antonio, K., Dutang, C., & Tsanakas, A. (2021). Editorial - special issue insurance data science. Annals of Actuarial Science, 15(2), 205-206. https://doi.org/10.1017/S174849952100018X
Deprez, L., Antonio, K., & Boute, R. (2021). Pricing service maintenance contracts using predictive analytics. European Journal of Operational Research, 290(2), 530-545. https://doi.org/10.1016/j.ejor.2020.08.022
Devriendt, S., Antonio, K., Reynkens, T., & Verbelen, R. (2021). Sparse regression with Multi-type Regularized Feature modeling. Insurance: Mathematics & Economics, 96, 248-261. https://doi.org/10.1016/j.insmatheco.2020.11.010
Henckaerts, R., Côté, M-P., Antonio, K., & Verbelen, R. (2021). Boosting Insights in Insurance Tariff Plans with Tree-Based Machine Learning Methods. North American Actuarial Journal, 25(2), 255-285. https://doi.org/10.1080/10920277.2020.1745656
van Berkum, F., Antonio, K., & Vellekoop, M. (2021). Quantifying longevity gaps using micro-level lifetime data. Journal of the Royal Statistical Society. Series A: Statistics in Society, 184(2), 548-570. https://doi.org/10.1111/rssa.12631[details]
Crevecoeur, J., Antonio, K., & Verbelen, R. (2019). Modeling the number of hidden events subject to observation delay. European Journal of Operational Research, 277(3), 930-944. https://doi.org/10.1016/j.ejor.2019.02.044[details]
Henckaerts, R., Antonio, K., Clijsters, M., & Verbelen, R. (2018). A data driven binning strategy for the construction of insurance tariff classes. Scandinavian Actuarial Journal, 2018(8), 681-705. https://doi.org/10.1080/03461238.2018.1429300[details]
Stripling, E., vanden Broucke, S., Antonio, K., Baesens, B., & Snoeck, M. (2018). Profit maximizing logistic model for customer churn prediction using genetic algorithms. Swarm and Evolutionary Computation, 40, 116-130. https://doi.org/10.1016/j.swevo.2017.10.010[details]
Verbelen, R., Antonio, K., & Claeskens, G. (2018). Unravelling the predictive power of telematics data in car insurance pricing. Journal of the Royal Statistical Society. Series C: Applied Statistics, 67(5), 1275-1304. https://doi.org/10.1111/rssc.12283[details]
Antonio, K., Devriendt, S., de Boer, W., de Vries, R., De Waegenaere, A., Kan, H-K., Kromme, E., Ouburg, W., Schulteis, T., Slagter, E., van der Winden, M., van Iersel, C., & Vellekoop, M. (2017). Producing the Dutch and Belgian mortality projections: a stochastic multi-population standard. European Actuarial Journal, 7(2), 297-336. https://doi.org/10.1007/s13385-017-0159-x[details]
Dhaene, J., Godecharle, E., Antonio, K., Denuit, M., & Hanbali, H. (2017). Lifelong health insurance covers with surrender values: updating mechanisms in the presence of medical inflation. ASTIN Bulletin, 47(3), 803-836. https://doi.org/10.1017/asb.2017.13[details]
Reynkens, T., Verbelen, R., Beirlant, J., & Antonio, K. (2017). Modelling censored losses using splicing: a global fit strategy with mixed Erlang and extreme value distributions. Insurance: Mathematics & Economics, 77, 65-77. https://doi.org/10.1016/j.insmatheco.2017.08.005[details]
van Berkum, F., Antonio, K., & Vellekoop, M. (2017). A Bayesian joint model for population and portfolio-specific mortality. ASTIN Bulletin, 47(3), 681-713. https://doi.org/10.1017/asb.2017.17[details]
Verbelen, R., Antonio, K., & Claeskens, G. (2016). Multivariate mixtures of Erlangs for density estimation under censoring. Lifetime Data Analysis, 22(3), 429-455. https://doi.org/10.1007/s10985-015-9343-y[details]
van Berkum, F., Antonio, K., & Vellekoop, M. (2016). The impact of multiple structural changes on mortality predictions. Scandinavian Actuarial Journal, 2016(7), 581-603. https://doi.org/10.1080/03461238.2014.987807[details]
Antonio, K., Bardoutsos, A., & Ouburg, W. (2015). Bayesian Poisson log-bilinear models for mortality projections with multiple populations. European Actuarial Journal, 5(2), 245-281. https://doi.org/10.1007/s13385-015-0115-6[details]
Godecharle, E., & Antonio, K. (2015). Reserving by conditioning on markers of individual claims: a case study using historical simulation. North American Actuarial Journal, 19(4), 273-288. https://doi.org/10.1080/10920277.2015.1046607[details]
Verbelen, R., Gong, L., Antonio, K., Badescu, A., & Lin, S. (2015). Fitting mixtures of Erlangs to censored and truncated data using the EM algorithm. ASTIN Bulletin, 45(3), 729-758. https://doi.org/10.1017/asb.2015.15[details]
Antonio, K., & Zhang, Y. (2014). Linear mixed models. In E. W. Frees, R. A. Derrig, & G. Meyers (Eds.), Predictive modeling applications in actuarial science - Vol. 1: predictive modeling techniques (pp. 182-216). (International Series on Actuarial Science). New York: Cambridge University Press. [details]
Antonio, K., & Zhang, Y. (2014). Nonlinear mixed models. In E. W. Frees, R. A. Derrig, & G. Meyers (Eds.), Predictive modeling applications in actuarial science - Vol. 1: predictive modeling techniques (pp. 398-426). (International Series on Actuarial Science). New York: Cambridge University Press. [details]
Antonio, K., Shi, P., & van Berkum, F. (2014). Longitudinal data and experience rating. In A. Charpentier (Ed.), Computational actuarial science with R (pp. 511-542). (Chapman & Hall/CRC The R Series). Boca Raton: CRC Press. [details]
Pigeon, M., Antonio, K., & Denuit, M. (2013). Individual loss reserving with the multivariate skew normal framework. ASTIN Bulletin, 43(3), 399-428. https://doi.org/10.1017/asb.2013.20[details]
Vercruysse, W., Dhaene, J., Denuit, M., Pitacco, E., & Antonio, K. (2013). Premium indexing in lifelong health insurance. Far East Journal of Mathematical Sciences, Special Volume(4), 365-384. http://www.pphmj.com/abstract/7855.htm[details]
2012
Antonio, K., & Valdez, E. (2012). Statistical concepts of a priori and a posteriori risk classification in insurance. AStA-Advances in Statistical Analysis, 96(2), 187-224. https://doi.org/10.1007/s10182-011-0152-7[details]
Antonio, K., & Beirlant, J. (2008). Issues in claims reserving and credibility: a semiparametric approach with mixed models. The Journal of Risk and Insurance, 75(3), 643-676. https://doi.org/10.1111/j.1539-6975.2008.00278.x[details]
Antonio, K., & Beirlant, J. (2008). Risk classification in nonlife insurance. In E. L. Melnick, & B. S. Everitt (Eds.), Encyclopedia of quantitative risk analysis and assessment. - Vol. 4 (pp. 1530-1535). Chichester [etc.]: Wiley. [details]
van Calster, H., Endels, P., Antonio, K., Verheyen, K., & Hermy, M. (2008). Coppice management effects on experimentally established populations of three herbaceous layer woodland species. Biological Conservation, 141(10), 2641-2652. https://doi.org/10.1016/j.biocon.2008.08.001[details]
Antonio, K., Beirlant, J., Hoedemakers, T., & Verlaak, R. (2006). Lognormal mixed models for reported claims reserves. North American Actuarial Journal, 10(1), 30-48. https://doi.org/10.1080/10920277.2006.10596238
2005
Antonio, K., Beirlant, J., & Hoedemakers, T. (2005). Discussion on 'A Bayesian generalized linear model for the Bornhuetter-Ferguson method of claims reserving'. North American Actuarial Journal, 9(3), 143-145.
2004
Antonio, K., Goovaerts, M., & Hoedemakers, T. (2004). On the distribution of Discounted Loss Reserves. Medium Econometrische Toepassingen, 12(3), 12-16. [details]
Antonio, K., & Charpentier, A. (2017). La tarification par genre en assurance: corrélation ou causalité? Risques, 109, 107-110. [details]
2015
Antonio, K., & Devriendt, S. (2015). Lang leven in België: een nieuwe prognose. (Leuvense Economische Standpunten; No. LES 2015/151). Leuven: KU Leuven. [details]
2013
Antonio, K., & Plat, R. (2013). Stochastische schadereservering op microniveau. In F. Thooft (Ed.), 50 jaar ASTIN: verleden, heden en toekomst (pp. 28-31). Utrecht: Koninklijk Actuarieel Genootschap. [details]
2012
Antonio, K. (2012). Bijlage bij prognosetafel AG2012-2062: sluiten van de periodetafel GBM/V 2005-2010. Utrecht: Actuarieel Genootschap & Actuarieel Instituut. [details]
Antonio, K., & Plat, R. (2012). Schadereservering anders?: van driehoeken naar micro-data. Actuaris, 19(6), 32-34. [details]
Antonio, K., van der Heijden, A. M. J. H., Meijer, R. E. V., Smit, C. T., Tornij, J. H., de Vries, R. W. J., ... van Zijp, P. P. C. (2012). Prognosetafel AG 2012-2062. Utrecht: Het Actuarieel Genootschap / Actuarieel Instituut. [details]
2010
Antonio, K., & Dannenburg, D. (2010). Credibiliteit 2.0. Actuaris, 17(5), 32-35. [details]
Antonio, K., & Plat, R. (2010). Micro-level stochastic loss reserving. Aenorm, 18(69), 15-17. [details]
2008
Antonio, K. (2008). Statistical tools for non-life insurance. Aenorm, 59, 5-9. [details]
2018
van Berkum, F. (2018). Models for population-wide and portfolio-specific mortality. [details]
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