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Identifying Key Fraud Indicators in the Automobile Insurance Industry Using SQL Server Analysis Services Cover

Identifying Key Fraud Indicators in the Automobile Insurance Industry Using SQL Server Analysis Services

By: Botond Benedek and  Ede László  
Open Access
|Sep 2019

References

  1. Abdallah A., Maarof M.A., Zainal A. (2016) Fraud detection system: A survey, Journal of Network and Computer Applications, 68, 90-113.10.1016/j.jnca.2016.04.007
  2. Balakrishnan P., Kumar S., Han P. (2011) Dual objective segmentation to improve targetability: An evolutionary algorithm approach, Decision Sciences, 42(4), 831-857.10.1111/j.1540-5915.2011.00333.x
  3. Bermúdez L., 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, 42(2), 779-786.10.1016/j.insmatheco.2007.08.002
  4. Bodon F., (2010) Adatbányászati algoritmusok, [Online] Available at: www.cs.bme.hu/~bodon/magyar/adatbanyaszat/tanulmany/adatbanyaszat.pdf [Accessed 06 01 2019].
  5. Dowling G.R., Midgley, D.F. (1988) Identifying the coarse and fine structures of market segments, Decision Sciences, 19(4), 830-847.10.1111/j.1540-5915.1988.tb00306.x
  6. Fan B., Zhang P. (2009) Spatially enabled customer segmentation using a data classification method with uncertain predicates, Decision Support Systems, 47(4), 343-353.10.1016/j.dss.2009.03.002
  7. Frank R.E., Strain C.E., (1972) A segmentation research design using consumer panel data, Journal of Marketing Research, 385-390.10.1177/002224377200900404
  8. Han S., Ye Y., Fu X., Chen Z. (2014) Category role aided market segmentation approach to convenience store chain category management, Decision Support Systems, 57 296-308.10.1016/j.dss.2013.09.017
  9. Green P.E., (1977) A new approach to market segmentation, Business Horizons, 20(1), 61-73.10.1016/0007-6813(77)90088-X
  10. Hassan A.K.I., Abraham A. (2016) Modeling insurance fraud detection using imbalanced data classification, Cham, Springer, 117-127.10.1007/978-3-319-27400-3_11
  11. Holsheimer M., Siebess A. (1996) Data mining: The search for knowledge in databases, Amsterdam: Centrum voor Wiskunde en Informatica.
  12. Huerta-Munoz D.L., Rios-Mercado R.Z., Ruiz R. (2017) An iterated greedy heuristic for a market segmentation problem with multiple attributes, European Journal of Operational Research, 261(1), 75-87.10.1016/j.ejor.2017.02.013
  13. Kiang M.Y., Hu M.Y., Fisher D.M. (2006) An extended self-organizing map network for market segmentation - a telecommunication example, Decision Support Systems, 42(1), 36-47.10.1016/j.dss.2004.09.012
  14. Kotler P., Armstrong G. (2010) Principles of marketing, Pearson Education.
  15. Insurance Fraud Bureau, 2015. Cutting corners to get cheaper motor insurance backfiring on thousands of motorists warns the ABI. [Interactiv] Available at:https://www.insurancefraudbureau.org/media-centre/news/2015/cutting-corners-to-get-cheaper-motor-insurance-backfiring-on-thousands-of-motorists-warns-the-abi/ [Accesat 01 09 2018].
  16. Li Y., Yan C., Liu W., Li, M. (2018) A principle component analysis-based random forest with the potential nearest neighbor method for automobile insurance fraud identification, Applied Soft Computing, Volumul 70, 1000-1009.10.1016/j.asoc.2017.07.027
  17. Liu J., Liao X., Huang W., Liao X. (2019). Market segmentation: A multiple criteria approach combining preference analysis and segmentation decision, Omega, 83, 1-3110.1016/j.omega.2018.01.008
  18. Liu Y., Ram S., Lusch R.F., Brusco M. (2010) Multicriterion market segmentation: a new model, implementation, and evaluation, Marketing Science, 29(5), 880-894.10.1287/mksc.1100.0565
  19. Nian K., Zhang H., Tayal A., Coleman T., Li, Y. (2016) Auto insurance fraud detection using unsupervised spectral ranking for anomaly, The Journal of Finance and Data Science, 2(1), 58-75.10.1016/j.jfds.2016.03.001
  20. Pathak J., Vidyarthi N., Summers S.L. (2005) A fuzzy-based algorithm for auditors to detect elements of fraud in settled insurance claims, Managerial Auditing Journal, 20(6), 632-644.10.1108/02686900510606119
  21. Phua C., Alahakoon D., Lee, V. (2004) Minority report in fraud detection: classification of skewed data, Acm sigkdd explorations newsletter, 6(1), 50-59.10.1145/1007730.1007738
  22. Pinquet J., Ayuso M., Guillén M. (2007) Selection bias and auditing policies for insurance claims, Journal of Risk and Insurance, 74(2), 425-440.10.1111/j.1539-6975.2007.00219.x
  23. Šubelj L., Furlan Š., Bajec M., (2011) An expert system for detecting automobile insurance fraud using social network analysis, Expert Systems with Applications, 38(1), 1039-1052.10.1016/j.eswa.2010.07.143
  24. Sundarkumar G.G., Ravi V. (2015) A novel hybrid undersampling method for mining unbalanced datasets in banking and insurance, Engineering Applications of Artificial Intelligence, Volumul 37, 368-377.10.1016/j.engappai.2014.09.019
  25. Tao H., Zhixin L., Xiaodong S. (2012) Insurance fraud identification research based on fuzzy support vector machine with dual membership. s.l., IEEE, 457-460.
  26. Tsafarakis S., Grigoroudis E., Matsatsinis N. (2008) Targeting the undecided customer, In Proceedings of the 37th EMAC Conference.
  27. Wang Y., Xu W (2018). Leveraging deep learning with LDA-based text analytics to detect automobile insurance fraud, Decision Support Systems, Volumul 105, 87-95.10.1016/j.dss.2017.11.001
  28. Wedel M., Kamakura W.A. (2012) Market segmentation: Conceptual and methodological foundations, volume 8. Springer Science and Business Media.
  29. Wind Y. (1978) Issues and advances in segmentation research, Journal of marketing research, 317-337.10.1177/002224377801500302
  30. Xu W., Wang S., Zhang D., Yang, B. (2011) Random rough subspace based neural network ensemble for insurance fraud detection. s.l., IEEE, 1276-1280.10.1109/CSO.2011.213
Language: English
Page range: 53 - 71
Published on: Sep 9, 2019
Published by: Babeș-Bolyai University
In partnership with: Paradigm Publishing Services
Publication frequency: 3 issues per year

© 2019 Botond Benedek, Ede László, published by Babeș-Bolyai University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.