Developing a model for managing the risk assessment of import declarations in customs based on data analysis techniques
Subject Areas : Risk ManagementHassan Ali Khojasteh Aliabadi 1 , Saeed Daei-Karimzadeh 2 , Majid Iranpour Mobarakeh 3 , Farsad Zamani Boroujeni 4
1 - Department of Public-Financial Management, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran.
2 - Department of Economics, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran
3 - Department of Computer Engineering and IT, Payam Noor University, Tehran, Iran.
4 - Faculty of Engineering, Department of Computer, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran.
Keywords: Customs, Data Analysis, Risk, risk management, import declaration,
Abstract :
In customs management, the main problem is balancing the needs of trade facilita-tion as a process of simplifying and accelerating foreign business on the one hand and countering illegal trade, reducing government revenue, capital sleep and the level of controls and interventions on the other. Also, due to the financial crisis in recent years, risk management has been reconsidered, although this attention is related to various financial branches. Since risk analysis and identification is the main component of risk management, developing a suitable model for data analysis is of particular importance. The purpose of this study was to use data data analysis techniques to develop an intelligent model to timely predict the risk of import declarations in customs and thus prevent irreparable losses. In this study, data analysis techniques have been used according to the statistical population which is data-driven. Statistical data were extracted from www.eplonline.ir with 575006 import declarations of all Iranian customs during 2019-2020. having pre-processed and prepared the data using PCA, LDA and FastICA methods, attribute reduction and effective attribute extraction were performed using 14 data analysis algorithms. Using Python software, algorithms were trained and modeled with 80% of the final data. Then, 14 obtained models were tested and validated with 20% of the data. Finally, the results of these models were compared with each other and the model obtained from the random forest algorithm was selected as a comprehensive model for predicting and determining the level of risk of import declarations at customs.
[1] Aguirre, J. G., Villar, A. D., Administrative Costs and Tariff Rates in the Presence of Customs Evasion: Evidence from Ecuador, Journal of Economies, 2021, 21(9), P. 1-16. Doi:10.3390/economies9010021
[2] Asadollahi, S.Y., Taherabadi, A, A., and Khairollahi, F., Modeling Liquidity Risk Management in Banking Using System Dynamics Approach, Advances in Mathematical Finance and Applications, 2020, 6(3), P. 493-514. Doi: 10.22034/AMFA.2020.1899914.1424
[3] Annamalah, S., Raman, M., Marthandan, G., and Logeswaran, A. K., Implementation of Enterprise Risk Management (ERM) Framework in Enhancing Business Performances in Oil and Gas Sector, Journal of Economies, 2018, 4(6), P. 1-12. Doi:10.3390/economies6010004
[4] Afanasieva, V., Ivanov, L., and Yanushkevych, D., Modern Approaches to Risk management and Their Use in Customs, Traektoriâ Nauki, 2017, 3(4), P. 1-14. Doi: 10.22178/pos.21-6
[5] Alipour Shirsavar, H., Shirinpour, M., The effect of electronic customs administration on facilitating the export activities of export companies based in Gilan, Iran, Intellectual Economics, 2016, 10, P. 114–121. Doi: 10.1016/j.intele.2017.03.004
[6] Ali Asghari, S., Ahmadi Abkenar, F., and Shah Bahrami, A., Identification of systemic and business risks and risk management in customs. National Conference on Organizational Risk Management, Tehran, Center for Productivity and Human Resources Studies, 2015, (in Persian).
[7] Alipour, M., Badiee, H., and Heydari, M., Requirements and strategies for exercising control after customs clearance of goods, Journal of Management Accounting and Auditing Knowledge, 2012, 4, P. 56-72, (in Persian).
[8] Arabi, M., Strategic planning of the customs of the Islamic Republic of Iran. Tehran, Nil Publications, 2004, 136 pages (in Persian).
[9] Basir, A., Satyadini, A. E., and Barata, A., Modern Customs Risk Management ramework: Improvement towards Institutional Reform, International Journal of Innovative Science and Research Technology, 2019, 4(7).
[10] Braganza, A., Brooks, L., Nepelski, D., Ali, M., and Moro, R., Resource management in big data initiatives: Processes and dynamic capabilities, Journal of Business Research, 2017, 70, P.328– 337. Doi: 10.1016/j.jbusres.2016.08.006
[11] Biljan, J., Trajkov, A., Customs Risk Management – time of Declaration processing by contorol caneels, Economy and Market Communication Review, 2016, 6(1), P. 93-108. Doi: 10.7251/EMC16093B
[12] Biljan, J., Trajkov, A., Risk management and Customs performance improvements: The case of the Republic of Macedonia, Procedia - Social and Behavioral Sciences, 2012, 44, P. 301– 313. Doi:10.1016/j.sbspro.2012.05.033
[13] Coombs, C., Hislop, D., Taneva, S K., and Barnard, S., The strategic impacts of Intelligent Automation for knowledge and service work: An interdisciplinary review, Journal of Strategic Information Systems, 2020, 29. Doi: 10.1016/j.jsis.2020.101600
[14] Chermiti, B., Establishing risk and targeting profiles using data mining: Decision trees, World Customs Journal, 2019, 13(2), P.46-57.
[15] Chapman, P., Clinton, J., Kerber, R., Khabaza, T., Reinartz, T., Shearer, C., and Wirth, R., CRISP-DM Step-Data Mining Guide, SPSS Inc.CRISPMWP, 2000.
[16] Duan, J-H., & Pan, Y-L., A Study of Customs Tax Risk Management. Advances in Economics, Business and Management Research (AEBMR), International Conference on Management Science and Management Innovation, 2018, 54.
[17] De Wispelaere, F., Pacolet, J., Data Mining for More Efficient Enforcement, Learning Resource Paper, 2017, P.1-20.
[18] Fayyad, G., Piatestsky-Shapiro, p., and Symth, P., From data mining to Knowledge discovery in databases, Al Magazin, 1996, 17, P. 37-54.
[19] Garcia, G., Caballero, M., A Multi-Objective Bayesian Approach with Dynamic Optimization (MOBADO). A Hybrid of Decision Theory and Machine Learning Applied to Customs Fraud Control in Spain, Mathematics, 2021, 9. Doi: 10.3390/math9131529
[20] Goli, R., Explanation and analysis of the Customs Affairs Law and its executive regulations, Tehran University route, 2018, 383 pages, (in Persian).
[21] Grover, V., Chiang, RH.L., Liang, T-P., and Zhang, D., Creating Strategic Business Value from Big Data Analytics: A Research Framework, Journal of Management Information Systems, 2018, 35(2), P. 388- 423. Doi: 10.1080/07421222.2018.1451951
[22] Gunther, W. A., Rezazade Mehrizi, M. H., Huysman, M., and Feldberg, F., Debating big data: A literature review on realizing value from big data, Journal of Strategic Information Systems, 2017, 26, P. 191– 209. Doi: 10.1016/j.jsis.2017.07.003
[23] Ghazanfari, M., Alizadeh, S., and Timourpour, B., Data mining and knowledge discovery, Tehran University of Science and Technology, 2016, (in Persian).
[24] Gleissner,W., Berger, T., Risk Management in Simple Language. Translated by Shahram Amin Torabi, Tehran: World Economy Publication, 2015, 136 pages, (in Persian).
[25] Geourjon, A-M., Laporte, B., Coundoul, O., and Gadiaga, M., Inspecting less to inspect better: The use of data mining for risk management by customs administrations, Working Paper Development Police, 2012, 46, P. 1- 19.
[26] Geourjon, A-M., Laporte, B., and Graziosi, R., How to modernise risk analysis and the selectivity of customs controls in developing countries? WCONEWS, 2010, 62, P. 29- 31.
[27] Herusantoso, Kh., Dwi Saputra, A., Factors affecting the customs clearance time at prime customs office type an of tanjung priok, Customs Research and Application Journal, 2020, 2 (2).
[28]Hoffman, A., Grater, S., C Venter, W., Maree, J., and Liebenberg, D., Designing a new methodology for customs risk models, World Customs Journal, 2019, 1(13), P. 31-55.
[29] Hayati, M., Atai, M., Khalokakaei, R., and Sayadi, A., Risk assessment and ranking in the supply chain using taxonomic analysis method (Case study: Isfahan Steel Complex), Journal of Operations Research in its Applications, 2013, 1(40), P. 85-103, (in Persian).
[30] Hanafizadeh, P., Comparison of two data mining methods in segmenting car body insurance customers based on risk (Case study: Mellat Insurance Company), Industrial Management Studies, 2013, 30, P. 77- 97, (in Persian).
[31] Haji Heidari, N., Samarand, K., and Farahi, A., Risk Classification of Car Body Insurance Insurers Using Data Mining Algorithms (Case Study: An Insurance Company), Insurance Research Journal (formerly Insurance Industry), 2010, 4, P. 107- 129, (in Persian).
[32] Jellis, V., David, M., and Bruno, P., Customs fraud detection : assessing the value of behavioural and high-cardinality data under the imbalanced learning issue, Pattern analysis and applications, 2020, 23, P. 1457-1477. Doi: 10.1007/S10044-019-00852-W
[33] Jiawei, H., Camber, M., Pi, J., data mining: Concepts and techniques. Translated by Mehdi Ismaili, Tehran, Niaz Danesh Publications, 2017, 600 pages, (in Persian).
[34] Jamaat, A., Asgari, F., Credit risk management in the banking system with a data mining approach, Quarterly Journal of Quantitative Studies in Management, 2010, 11, P.115- 126, (in Persian).
[35] Kavoya, J., Machine learning for intelligence driven Customs management, African Tax and Customs Review, 2020, 1(3), P. 50–58.
[36] Kitchens, B., dobolyi, D., LI, J., abbasi, A., Advanced customer analytics: strategic value through integration of relationship-oriented big data, Journal of Management Information Systems, 2018, 35(2), P.540–574. Doi: 10.1080/07421222.2018.1451957
[37] Larus T. Daniel., Data Acquisition an Introduction to Data Mining. Translated by Ali Zeinal Hamedani, Farhad Ebrahimian, Hadith Yaghoubzadeh, Isfahan: Isfahan University of Technology Publishing, 2013, 295 pages, (in Persian).
[38] Laporte, B., Risk management systems: using data mining in developing countries customs administrations, World Customs Journal, 2011, 5(1), P. 17- 29.
[39] Moslemi, A., Pourzamani, Z., and Jahanshad, A., Ranking of Banks’ Risk Reporting Using Data Envelopment Analysis, Advances in Mathematical Finance and Applications, 2021, 6(4), P. 695-715. Doi: 10.22034/AMFA.2021.1899631.1436
[40] Mohammadi, M., Yazdani, Sh., and Khanmohammadi, M., Presenting a Model for Financial Reporting Fraud Detection using Genetic Algorithm, Advances in Mathematical Finance and Applications, 2021, 6(2), P. 377-392. Doi: 10.22034/amfa.2019.1872783.1252
[41] Marzuki, M. M., Abdul majid, W. Z. N., Azis, N.K., Rosman, R., and Abdulatiff, N. K. H., Fraud Risk Management Model: A Content Analysis Approach, Journal of Asian Finance, Economics and Business, 2020, 10(7), P. 717– 728. Doi: 10.13106/jafeb.2020.vol7.no10.717
[42] Mikalef, P., Boura, M., Lekakos, G., and Krogstiea, J., Big data analytics and firm performance: Findings from a mixed-method approach, Journal of Business Research, 2019, 98, P.261– 276. Doi: 10.1016/j.jbusres.2019.01.044
[43] Martincus, C. V., Carballo, J., and Graziano, A., Customs, Journal of International Economics, 2015, 96, P. 119– 137. Doi: 10.1016/j.jinteco.2015.01.011
[44] Meshkani, A., Nazemi, A., An introduction to data mining. Mashhad: Ferdowsi University Publishing Institute, 2009, 450 pages, (in Persian).
[45] Nemirova, G. I., Savelyeva, T. I., Significance assessment of the risk management system to improve the quality customs service provision, Economic consultant, 2020, 31(3), P. 42- 52.
[46] Nelson, C., Machine learning for detection of trade in strategic goods: an approach to support future customs enforcement and outreach, World Customs Journal, 2020, 2(14), P. 124-133.
[47] Okazaki, Y., Implications of Big Data for Customs -How It Can Support Risk Management Customs, Journal WCO Research Paper, 2017, 39, P. 1- 24.
[48] Rukanova, B., Tan, Y-H., Slegt, M., Molenhuis, M., Rijnsoever, B. V., Migeotte, J., Labare, M. L.M., Plecko, K., Caglayan, B., Shorten, G., Meij, O. V. D., and Post,S., Identifying the value of data analytics in the context of government supervision: Insights from the customs domain, Government Information Quarterly, 2021, 38, 101496. Doi: 10.1016/j.giq.2020.101496
[49] Ravisankar P, Ravi V, Rao GR, Bose I., Detection of financial statement fraud and feature selection using data mining techniques, Decision Support Systems, 2011, 50, P. 491- 500.
[50] Shishechiha, M., Risk management in customs affairs, Tehran, Basic Science Development Publications, 2015, 144 pages, (in Persian).
[51] Salarzaei, A., Jamshidi, S., New Risk and Customs Management in Khorramshahr, Master Thesis, Sistan and Baluchestan University, 2012, (in Persian).
[52] Yousefi, M., Comparative study of customs risk management, Tehran, Dara Publications, 2016, 179 pages, (in Persian).
[53] Yousefi, M., Modern customs programs in the 21st century, Tehran, Dara Publications, 2016, 235 pages, (in Persian).
[54] Zhou, X., Data mining in customs risk detection with cost‑sensitive classification, World Customs Journal, 2019, 2(13), P. 115-128.
[55] Zehero, B-B., Soro, E., Gondo, Y., Brou, P., and Asseu, O., Elicitation of Association Rules from Information on Customs Offences on the Basis of Frequent Motives, Engineering, 2018, 10, P. 588- 605. Doi: 10.4236/eng.2018.109043
[56] Zarepour, Z., Chamani, G., Risk management and its executive requirements in customs, paper Second National Conference on Modern Management sciences, Gorgan, 2013, (in Persian).