شناسایی و اولویت‌بندی تقلب‌ها و تخلف‌های بیمه‌ای و پیشایندهای مؤثر بر آنها در حوزۀ بیمه‌های تکمیلی درمان: مطالعه در بیمۀ دانا استان سیستان و بلوچستان
محورهای موضوعی : مدیریتعلیرضا سرگلزایی 1 , سحر منوچهری 2 , حمیدرضا خدادادی دیدانی 3
1 - گروه مدیریت، دانشکده علوم انسانی، دانشگاه آزاد اسلامی واحد زاهدان، زاهدان، ایران
2 - دانشجوی دکتری مدیریت دولتی، دانشکده مدیریت و علوم انسانی، دانشگاه آزاد اسلامی واحد زاهدان، ایران.
3 - دانشجوی دکتری مدیریت دولتی، دانشکده مدیریت و علوم انسانی، دانشگاه آزاد اسلامی واحد زاهدان، ایران.
کلید واژه: روش دلفی فازی, تخلف‌های بیمه‌ای, بیمه‌های تکمیلی درمان, بیمه دانا,
چکیده مقاله :
باوجود پیشرفت‌های فراوان در شناسایی تقلب‌های بیمه‌ای، هزینه ایجاد شده در اثر این کلاهبرداری‌ها، برای شرکت‌های بیمه‌ای هم چنان درحال افزایش است. این پژوهش درپی شناسایی و اولویت‌بندی تقلبات و تخلفات بیمه‌ای و پیشایندهای مؤثر بر آنها در حوزه بیمه‌های تکمیلی درمان (بیمۀ دانا استان سیستان و بلوچستان) است. روش مطالعه حاضر، در مرحله اول جمع‌آوری داده‌ها، اکتشافی و در مرحله دوم جمع‌آوری داده‌ها، پیمایشی می‌باشد. داده‌ها و اطلاعات مورد نیاز ابتدا از طریق مطالعات کتابخانه ای و مصاحبه و در ادامه از طریق پرسشنامه‌های متناسب با هر قسمت جمع‌آوری گردیده است. پرسشنامه‌ها براساس روش دلفی فازی سنتی تحلیل گردید. در جهت شناسایی تقلبات و تخلفات بیمه‌های تکمیلی درمان و پیشایندهای مرتبط با آن تعداد 16 نفر از خبرگان این حوزه به‌صورت غیر تصادفی مشخص شده و از آنها نظرخواهی انجام گرفت. نتایج با استفاده از نرم افزارهای SPSS و Excell تحلیل شد. نتایج این تحقیق نشان داد که شرکت‌های بیمه به منظور جلوگیری از بروز تقلبات و تخلفات بیمه‌ای می‌توانند ضمن شناسایی مهم‌ترین علل ایجاد تخلفات با اعتبارسنجی دقیق نمایندگان و مشتریان، افزایش منابع انسانی، ایجاد امتیاز برای نمایندگان فاقد تخلفات و تعیین قوانین سختگیرانه در صنعت بیمه به کاهش تقلب و تخلف در شرکت‌های بیمه کمک شایانی برسانند.
Despite many advances in identifying insurance frauds, the cost caused by these frauds is still increasing for insurance companies. This research seeks to identify and prioritize insurance frauds and violations and the antecedents affecting them in the field of supplementary medical insurance (Dana insurance of Sistan and Baluchistan province). The method of this study is exploratory in the first stage of data collection and survey in the second stage of data collection. The required data and information have been collected first through library studies and interviews, and then through questionnaires appropriate to each part. The questionnaires were analyzed based on the traditional fuzzy Delphi method. In order to identify the frauds and violations of supplementary medical insurances and related antecedents, 16 experts in this field were identified non-randomly and their opinions were asked. The results were analyzed using SPSS and Excel software. The results of this research showed that in order to prevent insurance frauds and violations, insurance companies can identify the most important causes of violations by carefully validating agents and customers, increase human resources, create points for agents without violations, and determine strict rules in the insurance industry to reduce Fraud and violations in insurance companies can help.
Chakrabarty, D. (2009). Market for private health insurance in a developing economy: A cross-country analysis. SSRN Electronic Journal, 1, 45-57. https://doi.org/10.2139/ssrn.1520119
Chang, P.-L., Hsu, C.-W., & Chang, P.-C. (2011). Fuzzy Delphi method for evaluating hydrogen production technologies. International Journal of Hydrogen Energy, 36(11), 14172-14179. https://doi.org/10.1016/j.ijhydene.2011.05.045
Danesh Dehkordi, N. (2004). Global health perspective from the point of view of law (1 ed.). Health insurance organization. [In Persian]
Derrig, R. A., Johnston, D. J., & Sprinkel, E. A. (2006). Auto insurance fraud: Measurements and efforts to combat it. Risk Management & Insurance Review, 9(2), 109–130. https://doi.org/10.1111/j.1540-6296.2006.00089.x
Dionne, G. (2012). Risk Classification in Insurance Contracting. Wellesley College, Pendleton Hall East.
Farshbaf Maharian, J., & Lalianpour, N. (2017). Identifying factors affecting fraud and violations in Iran's insurance industry using the fuzzy Delphi method. International Conference on Insurance and Development, Iran. [In Persian]
Firoozi, M., Shakoori, M., Kazemi, l., & Zahedi, S. (2011). Fraud detection in car insurance using data mining methods. Insurance Research Journal(3), 103-128. [In Persian]
Gencer, C., & Gürpinar, D. (2007). Analytic Network Process in supplier selection: A case study in an electronic firm. Applied Mathematical Modelling, 31(11), 2475–2486. https://doi.org/10.1016/j.apm.2006.10.002
Ghafouri, M. (2004). Investigating factors affecting the satisfaction of health insurance policyholders of Dana Insurance Company. Insurance Industry Quarterly(3), 33-48. [In Persian]
Hsu, T. H., & Yang, T. H. (2000). Application of Fuzzy Analytic Hierarchy Process in the Selection of Advertising Media. Journal of Management and Systems, 7.
I.R.I. (2008). performance of the insurance industry by insurance disciplines in 2007. Insurance Research Institute. [In Persian]
Khaleq Nejad, A. (2000). The Position of Health Insurance in Social Security (1 ed.). Social Research Institute. [In Persian]
Kianpour, S., & Rezaei Azandriani, H. (2018). Microeconomics (1 ed.). Comprehensive publications, Iran. [In Persian]
Kuo, Y.-F., & Chen, P.-C. (2008). Constructing performance appraisal indicators for mobility of the service industries using Fuzzy Delphi method. Expert Systems with Applications, 35(4), 1930–1939. https://doi.org/10.1016/j.eswa.2007.08.068
Macedo, A. M., Viana Cardoso, C., Marques Neto, J. S., & Amaral da Costa Brás da Cunha, C. (2021). Car insurance fraud: The role of Vehicle Repair Workshops. International Journal of Law, Crime and Justice, 65. https://doi.org/10.1016/j.ijlcj.2021.100456
Mariner, W. (2013). The Affordable Care Act and Health Promotion: The Role of Insurance in Defining Responsibility for Health Risks and Costs. Boston University school of law public law and Legal Research, 271. https://scholarship.law.bu.edu/faculty_scholarship/363
Mohammadpour, M., Asadi, A., & Davodi, A. (2016). Identifying and ranking the factors affecting supplementary medical insurance risks using the network analysis technique (case study of Khorasan Razavi insurance companies) The second management and economics conference in the 21st century, Iran. [In Persian]
Moradi, M., & Fateminejad, S. (2017). Review and ranking of strategies to prevent the payment of unreal damages in medical insurance (case study: Sarmad Insurance Company). Management and Accounting Studies Quarterly, 3(3), 335-343. [In Persian]
Nazarzadeh Danak, A., Sabzi, M., & Khajir, F. (2017). The role of information technology in reducing insurance fraud and violations Proceedings of the 25th National Conference on Insurance and Development, Iran. [In Persian]
Nguyen, H., & Knowles, J. (2010). Demand for voluntary health insurance in developing countries: The case of Vietnam’s school-age children and Adolescent Student Health Insurance Program. Social Science & amp Medicine, 71(12), 2074–2082. https://doi.org/10.1016/j.socscimed.2010.09.033
Rahimian, N. (2011). Fraud detection. Official Accountant Quarterly, 8(13), 82-91. [In Persian]
Rashidi, R. (2010). Insurance Fraud: Concepts and Challenges (Part I). The new monthly magazine of the world, 10, 1-29. [In Persian]
Riahifar, M., Hadian, H., & Abbasi Bani, F. (2012). Examining examples of fraud in Iran's insurance market and its monitoring, detection and control strategies according to the instructions of the International Association of Insurance Supervisors (IAIS) National Insurance and Development Conference, [In Persian]
Roriz, R., & Pereira, J. L. (2019). Avoiding insurance fraud: A blockchain-based solution for the vehicle sector. Procedia Computer Science, 164, 211–218. https://doi.org/10.1016/j.procs.2019.12.174
Rottenburger, J. R., Carter, C. R., & Kaufmann, L. (2019). It's alright, it's just a bluff: Why do corporate codes reduce lying, but not bluffing? Journal of Purchasing and Supply Management, 25(1), 30-39. https://doi.org/10.1016/j.pursup.2018.02.004
Safari, M., & Safarian, M. (2015). Examining the concept, nature and conditions of concluding double insurance. Research Journal of Insurance (Insurance Industry), 31(4), 117-138. [In Persian]
Schütz, F., Rampold, F., Kalisch, A., & Masuch, K. (2023). Consumer Cyber Insurance as Risk Transfer: A Coverage Analysis. Procedia Computer Science, 219, 521-528. https://doi.org/10.1016/j.procs.2023.01.320
Sheikhan, N. (2012). Supplementary medical insurance in Iran. Social Welfare 13(48), 247-270. [In Persian]
Varahrami, V. (2010). Factors affecting the presentation of fraudulent claims in car body insurance. Insurance Industry Quarterly, 25(3), 1-26. [In Persian]
Viaene, S., Ayuso, M., Guillen, M., Van Gheel, D., & Dedene, G. (2007). Strategies for detecting fraudulent claims in the automobile insurance industry. European Journal of Operational Research, 176(1), 565–583. https://doi.org/10.1016/j.ejor.2005.08.005
Viaene, S., & Dedene, G. (2004). Insurance fraud: Issues and challenges. The Geneva Papers on Risk and Insurance - Issues and Practice, 29(2), 313–333. https://doi.org/10.1111/j.1468-0440.2004.00290.x
Wilson, H. (2003). An analytical approach to detecting insurance fraud using logistic regression. Journal of Finance and Accountancy, 1-15.
_||_Chakrabarty, D. (2009). Market for private health insurance in a developing economy: A cross-country analysis. SSRN Electronic Journal, 1, 45-57. https://doi.org/10.2139/ssrn.1520119
Chang, P.-L., Hsu, C.-W., & Chang, P.-C. (2011). Fuzzy Delphi method for evaluating hydrogen production technologies. International Journal of Hydrogen Energy, 36(11), 14172-14179. https://doi.org/10.1016/j.ijhydene.2011.05.045
Danesh Dehkordi, N. (2004). Global health perspective from the point of view of law (1 ed.). Health insurance organization. [In Persian]
Derrig, R. A., Johnston, D. J., & Sprinkel, E. A. (2006). Auto insurance fraud: Measurements and efforts to combat it. Risk Management & Insurance Review, 9(2), 109–130. https://doi.org/10.1111/j.1540-6296.2006.00089.x
Dionne, G. (2012). Risk Classification in Insurance Contracting. Wellesley College, Pendleton Hall East.
Farshbaf Maharian, J., & Lalianpour, N. (2017). Identifying factors affecting fraud and violations in Iran's insurance industry using the fuzzy Delphi method. International Conference on Insurance and Development, Iran. [In Persian]
Firoozi, M., Shakoori, M., Kazemi, l., & Zahedi, S. (2011). Fraud detection in car insurance using data mining methods. Insurance Research Journal(3), 103-128. [In Persian]
Gencer, C., & Gürpinar, D. (2007). Analytic Network Process in supplier selection: A case study in an electronic firm. Applied Mathematical Modelling, 31(11), 2475–2486. https://doi.org/10.1016/j.apm.2006.10.002
Ghafouri, M. (2004). Investigating factors affecting the satisfaction of health insurance policyholders of Dana Insurance Company. Insurance Industry Quarterly(3), 33-48. [In Persian]
Hsu, T. H., & Yang, T. H. (2000). Application of Fuzzy Analytic Hierarchy Process in the Selection of Advertising Media. Journal of Management and Systems, 7.
I.R.I. (2008). performance of the insurance industry by insurance disciplines in 2007. Insurance Research Institute. [In Persian]
Khaleq Nejad, A. (2000). The Position of Health Insurance in Social Security (1 ed.). Social Research Institute. [In Persian]
Kianpour, S., & Rezaei Azandriani, H. (2018). Microeconomics (1 ed.). Comprehensive publications, Iran. [In Persian]
Kuo, Y.-F., & Chen, P.-C. (2008). Constructing performance appraisal indicators for mobility of the service industries using Fuzzy Delphi method. Expert Systems with Applications, 35(4), 1930–1939. https://doi.org/10.1016/j.eswa.2007.08.068
Macedo, A. M., Viana Cardoso, C., Marques Neto, J. S., & Amaral da Costa Brás da Cunha, C. (2021). Car insurance fraud: The role of Vehicle Repair Workshops. International Journal of Law, Crime and Justice, 65. https://doi.org/10.1016/j.ijlcj.2021.100456
Mariner, W. (2013). The Affordable Care Act and Health Promotion: The Role of Insurance in Defining Responsibility for Health Risks and Costs. Boston University school of law public law and Legal Research, 271. https://scholarship.law.bu.edu/faculty_scholarship/363
Mohammadpour, M., Asadi, A., & Davodi, A. (2016). Identifying and ranking the factors affecting supplementary medical insurance risks using the network analysis technique (case study of Khorasan Razavi insurance companies) The second management and economics conference in the 21st century, Iran. [In Persian]
Moradi, M., & Fateminejad, S. (2017). Review and ranking of strategies to prevent the payment of unreal damages in medical insurance (case study: Sarmad Insurance Company). Management and Accounting Studies Quarterly, 3(3), 335-343. [In Persian]
Nazarzadeh Danak, A., Sabzi, M., & Khajir, F. (2017). The role of information technology in reducing insurance fraud and violations Proceedings of the 25th National Conference on Insurance and Development, Iran. [In Persian]
Nguyen, H., & Knowles, J. (2010). Demand for voluntary health insurance in developing countries: The case of Vietnam’s school-age children and Adolescent Student Health Insurance Program. Social Science & amp Medicine, 71(12), 2074–2082. https://doi.org/10.1016/j.socscimed.2010.09.033
Rahimian, N. (2011). Fraud detection. Official Accountant Quarterly, 8(13), 82-91. [In Persian]
Rashidi, R. (2010). Insurance Fraud: Concepts and Challenges (Part I). The new monthly magazine of the world, 10, 1-29. [In Persian]
Riahifar, M., Hadian, H., & Abbasi Bani, F. (2012). Examining examples of fraud in Iran's insurance market and its monitoring, detection and control strategies according to the instructions of the International Association of Insurance Supervisors (IAIS) National Insurance and Development Conference, [In Persian]
Roriz, R., & Pereira, J. L. (2019). Avoiding insurance fraud: A blockchain-based solution for the vehicle sector. Procedia Computer Science, 164, 211–218. https://doi.org/10.1016/j.procs.2019.12.174
Rottenburger, J. R., Carter, C. R., & Kaufmann, L. (2019). It's alright, it's just a bluff: Why do corporate codes reduce lying, but not bluffing? Journal of Purchasing and Supply Management, 25(1), 30-39. https://doi.org/10.1016/j.pursup.2018.02.004
Safari, M., & Safarian, M. (2015). Examining the concept, nature and conditions of concluding double insurance. Research Journal of Insurance (Insurance Industry), 31(4), 117-138. [In Persian]
Schütz, F., Rampold, F., Kalisch, A., & Masuch, K. (2023). Consumer Cyber Insurance as Risk Transfer: A Coverage Analysis. Procedia Computer Science, 219, 521-528. https://doi.org/10.1016/j.procs.2023.01.320
Sheikhan, N. (2012). Supplementary medical insurance in Iran. Social Welfare 13(48), 247-270. [In Persian]
Varahrami, V. (2010). Factors affecting the presentation of fraudulent claims in car body insurance. Insurance Industry Quarterly, 25(3), 1-26. [In Persian]
Viaene, S., Ayuso, M., Guillen, M., Van Gheel, D., & Dedene, G. (2007). Strategies for detecting fraudulent claims in the automobile insurance industry. European Journal of Operational Research, 176(1), 565–583. https://doi.org/10.1016/j.ejor.2005.08.005
Viaene, S., & Dedene, G. (2004). Insurance fraud: Issues and challenges. The Geneva Papers on Risk and Insurance - Issues and Practice, 29(2), 313–333. https://doi.org/10.1111/j.1468-0440.2004.00290.x
Wilson, H. (2003). An analytical approach to detecting insurance fraud using logistic regression. Journal of Finance and Accountancy, 1-15.
