create a website

Policyholder cluster divergence based differential premium in diabetes insurance. (2021). Qin, Yifang ; Tang, Qing ; Bashir, Muhammad Farhan ; Ma, Benjiang.
In: Managerial and Decision Economics.
RePEc:wly:mgtdec:v:42:y:2021:i:7:p:1793-1807.

Full description at Econpapers || Download paper

Cited: 4

Citations received by this document

Cites: 51

References cited by this document

Cocites: 31

Documents which have cited the same bibliography

Coauthors: 0

Authors who have wrote about the same topic

Citations

Citations received by this document

  1. How energy transition and environmental innovation ensure environmental sustainability? Contextual evidence from Top-10 manufacturing countries. (2023). Shahbaz, Muhammad ; Pan, Yanchun ; Ghosh, Sudeshna ; Bashir, Muhammad Farhan.
    In: Renewable Energy.
    RePEc:eee:renene:v:204:y:2023:i:c:p:697-709.

    Full description at Econpapers || Download paper

  2. Dynamic correlated effects of electricity prices, biomass energy, and technological innovation in Tunisias energy transition. (2023). Sadiq, Muhammad ; Bashir, Muhammad Farhan ; Si, Kamel ; Cifuentes-Faura, Javier ; Talbi, Besma ; Li, Siying.
    In: Utilities Policy.
    RePEc:eee:juipol:v:82:y:2023:i:c:s0957178723000334.

    Full description at Econpapers || Download paper

  3. Transition to greener electricity and resource use impact on environmental quality: Policy based study from OECD countries. (2023). Raza, Syed ; Bashir, Muhammad Farhan ; Mentel, Grzegorz ; Amin, Fouzia ; Dengfeng, Zhao.
    In: Utilities Policy.
    RePEc:eee:juipol:v:81:y:2023:i:c:s0957178723000309.

    Full description at Econpapers || Download paper

  4. Research Trends of Board Characteristics and Firms’ Environmental Performance: Research Directions and Agenda. (2022). Xie, Siman ; Lin, Sha ; Eldin, Sayed M ; Khan, Riaz M ; Ali, Rashid ; Sadiq, Muhammad ; Bashir, Muhammad Farhan ; Shahzad, Luqman ; Lei, Jingsheng ; Amin, Ali H.
    In: Sustainability.
    RePEc:gam:jsusta:v:14:y:2022:i:21:p:14296-:d:960476.

    Full description at Econpapers || Download paper

References

References cited by this document

  1. Amsler, M. H. (1968). Les Chaines De Markov Des Assurances Vie, Invalidité Et Maladie. In Transactions of the 18th international congress of actuaries (Vol. 5, pp. 731–746). München: Springer.
    Paper not yet in RePEc: Add citation now
  2. Ang, J. C., Mirzal, A., Haron, H., & Hamed, H. N. (2016). Supervised, unsupervised, and semi‐supervised feature selection: A review on gene selection. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 13, 971–989. https://doi.org/10.1109/TCBB.2015.2478454.
    Paper not yet in RePEc: Add citation now
  3. Ayuso, M., Guillen, M., & Nielsen, J. P. (2019). Improving automobile insurance ratemaking using telematics: Incorporating mileage and driver behaviour data. Transportation, 46, 735–752. https://doi.org/10.1007/s11116-018-9890-7.

  4. Baione, F., & Levantesi, S. (2014). A health insurance pricing model based on prevalence rates: Application to critical illness insurance. Insurance: Mathematics & Economics, 58, 174–184.

  5. Barry, L., & Charpentier, A. (2020). Personalization as a promise: Can big data change the practice of insurance? Big Data & Society, 7, 205395172093514. https://doi.org/10.1177/2053951720935143.
    Paper not yet in RePEc: Add citation now
  6. Bolón‐Canedo, V., & Alonso‐Betanzos, A. (2019). Ensembles for feature selection: A review and future trends. Information Fusion, 52, 1–12. https://doi.org/10.1016/j.inffus.2018.11.008.
    Paper not yet in RePEc: Add citation now
  7. Boodhun, N., & Jayabalan, M. (2018). Risk prediction in life insurance industry using supervised learning algorithms. Complex & Intelligent Systems, 4, 145–154. https://doi.org/10.1007/s40747-018-0072-1.
    Paper not yet in RePEc: Add citation now
  8. Boone, J. (2015). Basic versus supplementary health insurance: Moral Hazard and adverse selection. Journal of Public Economics, 128, 50–58. https://doi.org/10.1016/j.jpubeco.2015.05.009.

  9. Bouktif, S., Fiaz, A., Ouni, A., & Serhani, M. A. (2018). Optimal deep learning Lstm model for electric load forecasting using feature selection and genetic algorithm: Comparison with machine learning approaches. Energies, 11, 1636–1655. https://doi.org/10.3390/en11071636.

  10. Boyer, M. M., & Peter, R. (2020). Insurance fraud in a Rothschild‐Stiglitz world. The Journal of Risk and Insurance, 87, 117–142. https://doi.org/10.1111/jori.12264.

  11. Cather, D. A. (2020). Reconsidering insurance discrimination and adverse selection in an era of data analytics. Geneva pap. Risk Insurance‐Issues Practice, 45, 426–456.

  12. Cattell, R. B. (1966). The scree test for the number of factors. Multivariate Behavioral Research, 1, 245–276.
    Paper not yet in RePEc: Add citation now
  13. Chowdhary, C. L., & Acharjya, D. P. (2017). Clustering algorithm in Possibilistic exponential fuzzy C‐mean segmenting medical images. Journal of Biomimetics Biomaterials and Biomedical Engineering, 30, 12–23.
    Paper not yet in RePEc: Add citation now
  14. Christiansen, M. C. (2012). Multistate models in health insurance. AStA ‐ Advances in Statistical Analysis, 96, 155–186.

  15. Cohen, A., & Siegelman, P. (2010). Testing for adverse selection in insurance markets. The Journal of Risk and Insurance, 77, 39–84. https://doi.org/10.1111/j.1539-6975.2009.01337.x.

  16. Deng, X., Li, Y., Weng, J., & Zhang, J. (2018). Feature selection for text classification: A review. Multimedia Tools and Applications, 78, 3797–3816.
    Paper not yet in RePEc: Add citation now
  17. Fleischmann, A. (2015). Calibrating intensities for long‐term care multiple‐state Markov insurance model. European Actuarial Journal, 5, 327–354. https://doi.org/10.1007/s13385-015-0117-4.
    Paper not yet in RePEc: Add citation now
  18. Gunnsteinsson, S. (2020). Experimental identification of asymmetric information: Evidence on crop Insurance in the Philippines. Journal of Development Economics, 144, 102414. https://doi.org/10.1016/j.jdeveco.2019.102414.

  19. Hernández‐Pereira, E., Bolón‐Canedo, V., Sánchez‐Maroño, N., Álvarez‐Estévez, D., Moret‐Bonillo, V., & Alonso‐Betanzos, A. (2016). A comparison of performance of K‐complex classification methods using feature selection. Information Sciences, 328, 1–14.
    Paper not yet in RePEc: Add citation now
  20. Hofmann, A., Häfen, O. V., & Nell, M. (2018). Optimal insurance policy indemnity schedules with Policyholders' limited liability and background risk. The Journal of Risk and Insurance, 86, 973–988.
    Paper not yet in RePEc: Add citation now
  21. Huang, Y., & Meng, S. (2019). Automobile insurance classification ratemaking based on telematics driving data. Decision Support Systems, 127, 113156. https://doi.org/10.1016/j.dss.2019.113156.
    Paper not yet in RePEc: Add citation now
  22. Jain, A. K. (2010). Data clustering: 50 years beyond K‐means. Pattern Recognition Letters, 31, 651–666. https://doi.org/10.1016/j.patrec.2009.09.011.
    Paper not yet in RePEc: Add citation now
  23. Jain, R., Alzubi, J. A., Jain, N., & Joshi, P. (2019). Assessing risk in life insurance using ensemble learning. Journal of Intelligent Fuzzy Systems, 37, 2969–2980. https://doi.org/10.3233/JIFS-190078.
    Paper not yet in RePEc: Add citation now
  24. Jolliffe, I. T., & Cadima, J. (2016). Principal component analysis: A review and recent developments. Philosophical Transactions of the Royal Society a: Mathematical, Physical & Engineering Sciences, 374, 2065–2080.
    Paper not yet in RePEc: Add citation now
  25. Khanmohammadi, S., Adibeig, N., & Shanehbandy, S. (2017). An improved overlapping K‐means clustering method for medical applications. Expert Systems with Applications, 67, 12–18.
    Paper not yet in RePEc: Add citation now
  26. Knight, T. O., Coble, K. H., Goodwin, B. K., Rejesus, R. M., & Seo, S. (2010). Developing variable unit‐structure premium rate differentials in crop insurance. American Journal of Agricultural Economics, 92, 141–151. https://doi.org/10.1093/ajae/aap002.

  27. Lam B. S. Y., & Choy S. K. (2019). A trimmed clustering‐based L1‐principal component analysis model for image classification and clustering problems with outliers. Applied Sciences, 9, 1562–1586. https://doi.org/10.3390/app9081562.
    Paper not yet in RePEc: Add citation now
  28. Liu, X., Zhou, Y., & Zongrun, W. (2020). Can the development of a Patient's condition be predicted through intelligent inquiry under the E‐health business mode? Sequential feature map‐based disease risk prediction upon features selected from cognitive diagnosis big data. International Journal of Information Management, 50, 463–486. https://doi.org/10.1016/j.ijinfomgt.2019.05.006.
    Paper not yet in RePEc: Add citation now
  29. Lu, Z. Y., Meng, S. W., Liu, L. P., & Han, Z. Q. (2018). Optimal insurance design under background risk with dependence. Insurance: Mathematics & Economics, 80, 15–28.

  30. Ma, Y.‐L., Zhu, X., Hu, X., & Chiu, Y.‐C. (2018). The use of context‐sensitive insurance telematics data in auto insurance rate making. Transportation Research: Part A‐Policy Practice, 113, 243–258. https://doi.org/10.1016/j.tra.2018.04.013.
    Paper not yet in RePEc: Add citation now
  31. Majid, A., Khan, M. A., Yasmin, M., Rehman, A., Yousafzai, A., & Tariq, U. (2020). Classification of stomach infections: A paradigm of convolutional neural network along with classical features fusion and selection. Microscopy Research and Technique, 83, 562–576. https://doi.org/10.1002/jemt.23447.
    Paper not yet in RePEc: Add citation now
  32. Miotto, R., Li, L., Kidd, B. A., & Dudley, J. T. (2016). Deep patient: An unsupervised representation to predict the future of patients from the electronic health records. Scientific Reports, 6, 26094. https://doi.org/10.1038/srep26094.
    Paper not yet in RePEc: Add citation now
  33. Nandi, R. J., Nandi, A. K., Rangayyan, R. M., & Scutt, D. (2006). Classification of breast masses in mammograms using genetic programming and feature selection. Medical & Biological Engineering & Computing, 44, 683–694. https://doi.org/10.1007/s11517-006-0077-6.
    Paper not yet in RePEc: Add citation now
  34. Nijpels, G., Beulens, J. W., van der Heijden, A. A., & Elders, P. J. (2019). Innovations in personalised diabetes care and risk management. European Journal of Preventive Cardiology, 26, 125–132. https://doi.org/10.1177/2047487319880043.
    Paper not yet in RePEc: Add citation now
  35. Nilashi, M., Ibrahim, O. B., Ahmadi, H., & Shahmoradi, L. (2017). An analytical method for diseases prediction using machine learning techniques. Computers and Chemical Engineering, 106, 212–223. https://doi.org/10.1016/j.compchemeng.2017.06.011.
    Paper not yet in RePEc: Add citation now
  36. Shi, X., Guo, Z., Nie, F., Yang, L., You, J., & Tao, D. (2016). Two‐dimensional whitening reconstruction for enhancing robustness of principal component analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38, 2130–2136.
    Paper not yet in RePEc: Add citation now
  37. Sideris, C., Pourhomayoun, M., Kalantarian, H., & Sarrafzadeh, M. (2016). A flexible data‐driven comorbidity feature extraction framework. Computers in Biology and Medicine, 73, 165–172. https://doi.org/10.1016/j.compbiomed.2016.04.014.
    Paper not yet in RePEc: Add citation now
  38. Soika, S. (2018). Moral Hazard and advantageous selection in private disability insurance. Geneva Papers on Risk Insurance‐Issues Practice, 43, 97–125. https://doi.org/10.1057/s41288-017-0055-2.

  39. Speiser, J. L., Miller, M. E., Tooze, J., & Ip, E. (2019). A comparison of random Forest variable selection methods for classification prediction modeling. Expert Systems with Applications, 134, 93–101. https://doi.org/10.1016/j.eswa.2019.05.028.
    Paper not yet in RePEc: Add citation now
  40. Steinley, D. (2006). K‐means clustering: A half‐century synthesis. The British Journal of Mathematical and Statistical Psychology, 59, 1–34. https://doi.org/10.1348/000711005X48266.
    Paper not yet in RePEc: Add citation now
  41. Tsai, C.‐F., & Sung, Y.‐T. (2020). Ensemble feature selection in high dimension, low sample size datasets: Parallel and serial combination approaches. Knowledge‐Based Systems, 203, 106097. https://doi.org/10.1016/j.knosys.2020.106097.
    Paper not yet in RePEc: Add citation now
  42. Uğuz, H. (2011). A two‐stage feature selection method for text categorization by using information gain, principal component analysis and genetic algorithm. Knowledge‐Based Systems, 24, 1024–1032.
    Paper not yet in RePEc: Add citation now
  43. Vadori, N., & Swishchuk, A. (2015). Strong law of large numbers and central limit theorems for Functionals of inhomogeneous semi‐Markov processes. Stochastic Analysis and Applications, 33, 213–243.
    Paper not yet in RePEc: Add citation now
  44. van Winssen, K. P. M., van Kleef, R. C., & van de Ven, W. (2018). Can premium differentiation counteract adverse selection in the Dutch supplementary health insurance? A simulation study. The European Journal of Health Economics, 19, 757–768. https://doi.org/10.1007/s10198-017-0918-2.

  45. Woodard, J. D. (2016). Integrating high resolution soil data into Federal Crop Insurance Policy: Implications for policy and conservation. Environmental Science & Policy, 66, 93–100. https://doi.org/10.1016/j.envsci.2016.08.011.

  46. Xie, X. L., & Beni, G. (1991). A validity measure for fuzzy clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(8), 841–847. https://doi.org/10.1109/34.85677.
    Paper not yet in RePEc: Add citation now
  47. Xu, R., Damelin, S., Nadler, B., & Wunsch, D. C. 2nd (2010). Clustering of high‐dimensional gene expression data with feature filtering methods and diffusion maps. Artificial Intelligence in Medicine, 48, 91–98. https://doi.org/10.1016/j.artmed.2009.06.001.
    Paper not yet in RePEc: Add citation now
  48. Xue, Y., Zhang, L., Wang, B., Zhang, Z., & Li, F. (2018). Nonlinear feature selection using Gaussian kernel Svm‐Rfe for fault diagnosis. Applied Intelligence, 48, 3306–3331. https://doi.org/10.1007/s10489-018-1140-3.
    Paper not yet in RePEc: Add citation now
  49. Yang, X., Chen, J., Pan, A., Wu, J. H. Y., Zhao, F., Xie, Y., Wang, Y., Ye, Y., Pan, X. F., & Yang, C. X. (2020). Association between higher blood pressure and risk of diabetes mellitus in middle‐aged and elderly Chinese adults. Diabetes and Metabolism Journal, 44, 436–445.
    Paper not yet in RePEc: Add citation now
  50. Yi, S., Lai, Z., He, Z., Cheung, Y.‐M., & Liu, Y. (2017). Joint sparse principal component analysis. Pattern Recognition, 61, 524–536. https://doi.org/10.1016/j.patcog.2016.08.025.
    Paper not yet in RePEc: Add citation now
  51. Yuvaraj, N., & SriPreethaa, K. R. (2017). Diabetes prediction in healthcare systems using machine learning algorithms on Hadoop cluster. Cluster Computing, 22, 1–9.
    Paper not yet in RePEc: Add citation now

Cocites

Documents in RePEc which have cited the same bibliography

  1. A Contractarian Approach to Actuarial Fairness. (2025). Teira, David ; Pradier, Pierre-Charles ; Heras, Antonio J.
    In: Journal of Business Ethics.
    RePEc:kap:jbuset:v:196:y:2025:i:3:d:10.1007_s10551-023-05602-x.

    Full description at Econpapers || Download paper

  2. The use of IoT sensor data to dynamically assess maintenance risk in service contracts. (2025). Boute, Robert N ; Loeys, Stijn ; Antonio, Katrien.
    In: European Journal of Operational Research.
    RePEc:eee:ejores:v:324:y:2025:i:2:p:454-465.

    Full description at Econpapers || Download paper

  3. In a world of Open Finance, are customers willing to share data? An analysis of the data-driven insurance business. (2024). Grassi, Laura.
    In: Eurasian Business Review.
    RePEc:spr:eurasi:v:14:y:2024:i:3:d:10.1007_s40821-024-00263-w.

    Full description at Econpapers || Download paper

  4. How to design subsidy policies to better encourage travelers to use car-sharing instead of private cars? An evolutionary game study. (2024). Li, Zixun ; Zong, Gang ; Sun, Yue ; Dong, Xianlei.
    In: PLOS ONE.
    RePEc:plo:pone00:0308622.

    Full description at Econpapers || Download paper

  5. Understanding intention to adopt telematics-based automobile insurance in an emerging economy: a mixed-method approach. (2024). Choudhary, Vipin ; Chauhan, Vikas ; Joshi, Rohit.
    In: Journal of Financial Services Marketing.
    RePEc:pal:jofsma:v:29:y:2024:i:3:d:10.1057_s41264-023-00253-5.

    Full description at Econpapers || Download paper

  6. Difference-in-Difference models to estimate causal effects on auto insurers behavior. (2024). Orteu, Anna-Patrcia ; Prez-Marn, Ana M ; Guillen, Montserrat ; Bolanc, Catalina.
    In: IREA Working Papers.
    RePEc:ira:wpaper:202411.

    Full description at Econpapers || Download paper

  7. Analyzing the Influence of Telematics-Based Pricing Strategies on Traditional Rating Factors in Auto Insurance Rate Regulation. (2024). Xie, Shengkun.
    In: Mathematics.
    RePEc:gam:jmathe:v:12:y:2024:i:19:p:3150-:d:1494357.

    Full description at Econpapers || Download paper

  8. Enhancing claim classification with feature extraction from anomaly‐detection‐derived routine and peculiarity profiles. (2023). Pigeon, Mathieu ; Boucher, Jeanphilippe ; Duval, Francis.
    In: Journal of Risk & Insurance.
    RePEc:bla:jrinsu:v:90:y:2023:i:2:p:421-458.

    Full description at Econpapers || Download paper

  9. Bivariate Poisson credibility model and bonus-malus scale for claim and near-claim events. (2023). Simon, Pierre-Alexandre ; Denuit, Michel ; Trufin, Julien.
    In: LIDAM Discussion Papers ISBA.
    RePEc:aiz:louvad:2023014.

    Full description at Econpapers || Download paper

  10. Segmentation and estimation of claim severity in motor third-party liability insurance through contrast analysis. (2022). Oltesova, Tatiana ; Zelinova, Silvia ; Komara, Silvia ; Reiff, Marian.
    In: Equilibrium. Quarterly Journal of Economics and Economic Policy.
    RePEc:pes:ierequ:v:17:y:2022:i:3:p:803-842.

    Full description at Econpapers || Download paper

  11. The impact of artificial intelligence along the insurance value chain and on the insurability of risks. (2022). Eling, Martin ; Staubli, Julian ; Nuessle, Davide.
    In: The Geneva Papers on Risk and Insurance - Issues and Practice.
    RePEc:pal:gpprii:v:47:y:2022:i:2:d:10.1057_s41288-020-00201-7.

    Full description at Econpapers || Download paper

  12. Vehicle Telematics for Safer, Cleaner and More Sustainable Urban Transport: A Review. (2022). Chapman, Sam ; Ghaffarpasand, Omid ; Burke, Mark ; Osei, Louisa K ; Ursell, Helen ; Pope, Francis D.
    In: Sustainability.
    RePEc:gam:jsusta:v:14:y:2022:i:24:p:16386-:d:996587.

    Full description at Econpapers || Download paper

  13. Safety and Economic Evaluations of Electric Public Buses Based on Driving Behavior. (2022). Chen, Zheng ; Zhou, Yiwen ; Xiong, Xuefei ; Wu, Simin ; Guo, Fengxiang ; Ni, Dingan.
    In: Sustainability.
    RePEc:gam:jsusta:v:14:y:2022:i:17:p:10772-:d:901016.

    Full description at Econpapers || Download paper

  14. Variable Selection Algorithm for a Mixture of Poisson Regression for Handling Overdispersion in Claims Frequency Modeling Using Telematics Car Driving Data. (2022). Shapovalov, Vered ; Makov, Udi ; Boris, S T ; Shamir, Ariel.
    In: Risks.
    RePEc:gam:jrisks:v:10:y:2022:i:4:p:83-:d:791726.

    Full description at Econpapers || Download paper

  15. The Impact of Aging Drivers and Vehicles on the Injury Severity of Crash Victims. (2022). Santolino, Miguel ; Ayuso, Mercedes ; Cespedes, Luis .
    In: IJERPH.
    RePEc:gam:jijerp:v:19:y:2022:i:24:p:17097-:d:1008373.

    Full description at Econpapers || Download paper

  16. Black box technology, usage-based insurance, and prediction of purchase behavior: Evidence from the auto insurance sector. (2022). Alfiero, Simona ; Battisti, Enrico ; Adjielias, Elias.
    In: Technological Forecasting and Social Change.
    RePEc:eee:tefoso:v:183:y:2022:i:c:s004016252200419x.

    Full description at Econpapers || Download paper

  17. Actuarial intelligence in auto insurance: Claim frequency modeling with driving behavior features and improved boosted trees. (2022). Huang, Yifan ; Gao, Yaqian ; Meng, Shengwang.
    In: Insurance: Mathematics and Economics.
    RePEc:eee:insuma:v:106:y:2022:i:c:p:115-127.

    Full description at Econpapers || Download paper

  18. Will claim history become a deprecated rating factor? An optimal design method for the real-time road risk model. (2022). Yu, Jiamin.
    In: Papers.
    RePEc:arx:papers:2204.11585.

    Full description at Econpapers || Download paper

  19. Acceptance of Criteria for Health and Driver Scoring In the General Public in Germany. (2021). Wagner, Gert ; Gigerenzer, Gerd ; Rebitschek, Felix G ; Gross, Christian ; Keitel, Ariane ; Sommer, Sarah.
    In: EconStor Open Access Articles and Book Chapters.
    RePEc:zbw:espost:233592.

    Full description at Econpapers || Download paper

  20. Policyholder cluster divergence based differential premium in diabetes insurance. (2021). Qin, Yifang ; Tang, Qing ; Bashir, Muhammad Farhan ; Ma, Benjiang.
    In: Managerial and Decision Economics.
    RePEc:wly:mgtdec:v:42:y:2021:i:7:p:1793-1807.

    Full description at Econpapers || Download paper

  21. Acceptance of criteria for health and driver scoring in the general public in Germany. (2021). Wagner, Gert ; Gigerenzer, Gerd ; Rebitschek, Felix G ; Gross, Christian ; Keitel, Ariane ; Sommer, Sarah.
    In: PLOS ONE.
    RePEc:plo:pone00:0250224.

    Full description at Econpapers || Download paper

  22. Knowledge Learning of Insurance Risks Using Dependence Models. (2021). Zhao, Zifeng ; Feng, Xiaoping ; Shi, Peng.
    In: INFORMS Journal on Computing.
    RePEc:inm:orijoc:v:33:y:2021:i:3:p:1177-1196.

    Full description at Econpapers || Download paper

  23. Improving Explainability of Major Risk Factors in Artificial Neural Networks for Auto Insurance Rate Regulation. (2021). Xie, Shengkun.
    In: Risks.
    RePEc:gam:jrisks:v:9:y:2021:i:7:p:126-:d:587826.

    Full description at Econpapers || Download paper

  24. Synthetic Dataset Generation of Driver Telematics. (2021). Boucher, Jean-Philippe ; Valdez, Emiliano A ; So, Banghee.
    In: Risks.
    RePEc:gam:jrisks:v:9:y:2021:i:4:p:58-:d:523212.

    Full description at Econpapers || Download paper

  25. Micro-level parametric duration-frequency-severity modeling for outstanding claim payments. (2021). Pigeon, Mathieu ; Yanez, Juan Sebastian.
    In: Insurance: Mathematics and Economics.
    RePEc:eee:insuma:v:98:y:2021:i:c:p:106-119.

    Full description at Econpapers || Download paper

  26. Black boxes and market efficiency: the effect on premiums in the Italian motor-vehicle insurance market. (2020). porrini, donatella ; Magazzino, Cosimo ; Fusco, Giulio.
    In: European Journal of Law and Economics.
    RePEc:kap:ejlwec:v:49:y:2020:i:3:d:10.1007_s10657-020-09657-3.

    Full description at Econpapers || Download paper

  27. Number and severity of BI victims, assuming dependence between vehicles involved in the crash. (2020). Santolino, Miguel ; Ayuso, Mercedes.
    In: IREA Working Papers.
    RePEc:ira:wpaper:202018.

    Full description at Econpapers || Download paper

  28. A Longitudinal Analysis of the Impact of Distance Driven on the Probability of Car Accidents. (2020). Turcotte, Roxane ; Boucher, Jean-Philippe.
    In: Risks.
    RePEc:gam:jrisks:v:8:y:2020:i:3:p:91-:d:407128.

    Full description at Econpapers || Download paper

  29. Bivariate Mixed Poisson and Normal Generalised Linear Models with Sarmanov Dependence—An Application to Model Claim Frequency and Optimal Transformed Average Severity. (2020). Rodrigo, Roberto ; Alemany, Ramon ; Vernic, Raluca ; Bolance, Catalina.
    In: Mathematics.
    RePEc:gam:jmathe:v:9:y:2020:i:1:p:73-:d:472799.

    Full description at Econpapers || Download paper

  30. A Sarmanov Distribution with Beta Marginals: An Application to Motor Insurance Pricing. (2020). Guillen, Montserrat ; Bolance, Catalina ; Pitarque, Albert.
    In: Mathematics.
    RePEc:gam:jmathe:v:8:y:2020:i:11:p:2020-:d:444234.

    Full description at Econpapers || Download paper

  31. On the Validation of Claims with Excess Zeros in Liability Insurance: A Comparative Study. (2019). Qazvini, Marjan.
    In: Risks.
    RePEc:gam:jrisks:v:7:y:2019:i:3:p:71-:d:244533.

    Full description at Econpapers || Download paper

Coauthors

Authors registered in RePEc who have wrote about the same topic

Report date: 2025-10-04 16:29:51 || Missing content? Let us know

CitEc is a RePEc service, providing citation data for Economics since 2001. Last updated August, 3 2024. Contact: Jose Manuel Barrueco.