Some searches may not work properly. We apologize for the inconvenience.
My bibliography Save this paperFraud detection in the era of Machine Learning: a household insurance case
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- B Baesens & T Van Gestel & S Viaene & M Stepanova & J Suykens & J Vanthienen, 2003. "Benchmarking state-of-the-art classification algorithms for credit scoring," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(6), pages 627-635, June.
- Shinichi Nakagawa, 2004. "A farewell to Bonferroni: the problems of low statistical power and publication bias," Behavioral Ecology, International Society for Behavioral Ecology, vol. 15(6), pages 1044-1045, November.
- Viaene, Stijn & Ayuso, Mercedes & Guillen, Montserrat & Van Gheel, Dirk & Dedene, Guido, 2007. "Strategies for detecting fraudulent claims in the automobile insurance industry," European Journal of Operational Research, Elsevier, vol. 176(1), pages 565-583, January.
- Bart Baesens & Rudy Setiono & Christophe Mues & Jan Vanthienen, 2003. "Using Neural Network Rule Extraction and Decision Tables for Credit-Risk Evaluation," Management Science, INFORMS, vol. 49(3), pages 312-329, March.
- Belhadji, B. & Dionne, G., 1997. "Development of an Expert System for Automatic Detection of Automobile Insurance Fraud," Ecole des Hautes Etudes Commerciales de Montreal- 97-06, Ecole des Hautes Etudes Commerciales de Montreal-Chaire de gestion des risques..
- King, Gary & Zeng, Langche, 2001. "Logistic Regression in Rare Events Data," Political Analysis, Cambridge University Press, vol. 9(2), pages 137-163, January.
- Steven B. Caudill & Mercedes Ayuso & Montserrat Guillén, 2005. "Fraud Detection Using a Multinomial Logit Model With Missing Information," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 72(4), pages 539-550, December.
- Artis, Manuel & Ayuso, Mercedes & Guillen, Montserrat, 1999. "Modelling different types of automobile insurance fraud behaviour in the Spanish market," Insurance: Mathematics and Economics, Elsevier, vol. 24(1-2), pages 67-81, March.
- Yufei Jin & Roderick Rejesus & Bertis Little, 2005. "Binary choice models for rare events data: a crop insurance fraud application," Applied Economics, Taylor & Francis Journals, vol. 37(7), pages 841-848.
- Joseph A. Atwood & James F. Robison-Cox & Saleem Shaik, 2006. "Estimating the Prevalence and Cost of Yield-Switching Fraud in the Federal Crop Insurance Program," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(2), pages 365-381.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Yankol-Schalck, Meryem, 2022. "The value of cross-data set analysis for automobile insurance fraud detection," Research in International Business and Finance, Elsevier, vol. 63(C).
- Bermúdez, Ll. & Pérez, J.M. & Ayuso, M. & Gómez, E. & Vázquez, F.J., 2008. "A Bayesian dichotomous model with asymmetric link for fraud in insurance," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 779-786, April.
- Ming-Jyh Wang & Chieh-Hua Wen & Lawrence W Lan, 2010. "Modelling Different Types of Bundled Automobile Insurance Choice Behaviour: The Case of Taiwan*," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 35(2), pages 290-308, April.
- Urbina, Jilber & Guillén, Montserrat, 2013.
"An application of capital allocation principles to operational risk,"
MPRA Paper
75726, University Library of Munich, Germany, revised Dec 2013.
- Urbina, Jilber & Guillén, Montserrat, 2013. "An application of capital allocation principles to operational risk," Working Papers 2072/222201, Universitat Rovira i Virgili, Department of Economics.
- Lessmann, Stefan & Voß, Stefan, 2009. "A reference model for customer-centric data mining with support vector machines," European Journal of Operational Research, Elsevier, vol. 199(2), pages 520-530, December.
- Hoffmann, F. & Baesens, B. & Mues, C. & Van Gestel, T. & Vanthienen, J., 2007. "Inferring descriptive and approximate fuzzy rules for credit scoring using evolutionary algorithms," European Journal of Operational Research, Elsevier, vol. 177(1), pages 540-555, February.
- Blackman, Allen & Guerrero, Santiago, 2012.
"What drives voluntary eco-certification in Mexico?,"
Journal of Comparative Economics, Elsevier, vol. 40(2), pages 256-268.
- Blackman, Allen & Guerrero, Santiago, 2010. "What Drives Voluntary Eco-Certification in Mexico?," RFF Working Paper Series dp-10-26, Resources for the Future.
- Martens, David & Baesens, Bart & Van Gestel, Tony & Vanthienen, Jan, 2007. "Comprehensible credit scoring models using rule extraction from support vector machines," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1466-1476, December.
- Casado Yusta, Silvia & Nœ–ez Letamendía, Laura & Pacheco Bonrostro, Joaqu’n Antonio, 2018. "Predicting Corporate Failure: The GRASP-LOGIT Model || Predicci—n de la quiebra empresarial: el modelo GRASP-LOGIT," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 26(1), pages 294-314, Diciembre.
- Jing Ai & Patrick L. Brockett & Linda L. Golden & Montserrat Guillén, 2013. "A Robust Unsupervised Method for Fraud Rate Estimation," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 80(1), pages 121-143, March.
- Berkin, Anil & Aerts, Walter & Van Caneghem, Tom, 2023. "Feasibility analysis of machine learning for performance-related attributional statements," International Journal of Accounting Information Systems, Elsevier, vol. 48(C).
- E Lima & C Mues & B Baesens, 2009. "Domain knowledge integration in data mining using decision tables: case studies in churn prediction," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(8), pages 1096-1106, August.
- Chengbin Wang & Kuangnan Fang & Chenlu Zheng & Hechao Xu & Zewei Li, 2021. "Credit scoring of micro and small entrepreneurial firms in China," International Entrepreneurship and Management Journal, Springer, vol. 17(1), pages 29-43, March.
- Dejaeger, Karel & Goethals, Frank & Giangreco, Antonio & Mola, Lapo & Baesens, Bart, 2012.
"Gaining insight into student satisfaction using comprehensible data mining techniques,"
European Journal of Operational Research, Elsevier, vol. 218(2), pages 548-562.
- K. Dejeager & F. Goethals & A. Giangreco & L. Mola & B. Baesens, 2012. "Gaining insight into student satisfaction using comprehensible data mining techniques," Post-Print hal-00787269, HAL.
- Karel Dejaeger & Frank Goethals & Antonio Giangreco & Lapo Mola & Bart Baesens, 2012. "Gaining insight into student satisfaction using comprehensible data mining techniques," Post-Print halshs-01929190, HAL.
- Sharma, Sankalp & Walters, Cory G., 2018.
"Influence of Farm and Lease Type on Crop Insurance Returns,"
2018 Annual Meeting, August 5-7, Washington, D.C.
273881, Agricultural and Applied Economics Association.
- Sharma, S. & Walters, C., 2018. "Influence of Farm and Lease Type on Crop Insurance Returns," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277399, International Association of Agricultural Economists.
- Pulina, Manuela & Paba, Antonello, 2010. "A discrete choice approach to model credit card fraud," MPRA Paper 20019, University Library of Munich, Germany.
- Gestel, Tony Van & Baesens, Bart & Suykens, Johan A.K. & Van den Poel, Dirk & Baestaens, Dirk-Emma & Willekens, Marleen, 2006.
"Bayesian kernel based classification for financial distress detection,"
European Journal of Operational Research, Elsevier, vol. 172(3), pages 979-1003, August.
- T. Van Gestel & B. Baesens & J. A.K. Suykens & D. Van Den Poel & D.-E. Baestaens & Bm. Willekens, 2004. "Bayesian Kernel-Based Classification for Financial Distress Detection," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/247, Ghent University, Faculty of Economics and Business Administration.
- Andersson, Jonas & Olden, Andreas & Rusina, Aija, 2020. "Fraud detection by a multinomial model: Separating honesty from unobserved fraud," Discussion Papers 2020/15, Norwegian School of Economics, Department of Business and Management Science.
- B Baesens & T Van Gestel & M Stepanova & D Van den Poel & J Vanthienen, 2005.
"Neural network survival analysis for personal loan data,"
Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(9), pages 1089-1098, September.
- B. Baesens & T. Van Gestel & M. Stepanova & D. Van Den Poel, 2004. "Neural Network Survival Analysis for Personal Loan Data," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/281, Ghent University, Faculty of Economics and Business Administration.
- B Baesens & C Mues & D Martens & J Vanthienen, 2009. "50 years of data mining and OR: upcoming trends and challenges," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 16-23, May.
More about this item
Keywords
; Fraud detection; Household insurance; Machine learning; Logistic LASSO; XGBoost; Imbalanced data; SHAP;All these keywords.
NEP fields
This paper has been announced in the following NEP Reports:- NEP-BIG-2021-11-22 (Big Data)
- NEP-CMP-2021-11-22 (Computational Economics)
- NEP-IAS-2021-11-22 (Insurance Economics)
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:leo:wpaper:2904. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sébastien Galanti (email available below). General contact details of provider: https://edirc.repec.org/data/leorlfr.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.