Academic literature on the topic 'Detect economic crimes'
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Journal articles on the topic "Detect economic crimes"
Moskaleva, E. G., and N. N. Podol'naya. "CRIMINOLOGICAL ANALYSIS OF ECONOMIC CRIME." Bulletin of Udmurt University. Series Economics and Law 31, no. 1 (February 12, 2021): 117–23. http://dx.doi.org/10.35634/2412-9593-2021-31-1-117-123.
Full textMoskaleva, E. G. "ECONOMIC CRIME IN RUSSIA: MAIN TRENDS AND FACTORS." Scientific Review: Theory and Practice 10, no. 8 (August 31, 2020): 1726–40. http://dx.doi.org/10.35679/2226-0226-2020-10-8-1726-1740.
Full textOcansey, Evans O. N. D. "Forensic Accounting and the Combating of Economic and Financial Crimes in Ghana." European Scientific Journal, ESJ 13, no. 31 (November 30, 2017): 379. http://dx.doi.org/10.19044/esj.2017.v13n31p379.
Full textSandagiri, Chamith, Banage T. G. S. Kumara, and Banujan Kuhaneswaran. "Deep Neural Network-Based Crime Prediction Using Twitter Data." International Journal of Systems and Service-Oriented Engineering 11, no. 1 (January 2021): 15–30. http://dx.doi.org/10.4018/ijssoe.2021010102.
Full textVorobyova, Svetlana V. "Certain issues of combating customs crimes." Current Issues of the State and Law, no. 18 (2021): 281–95. http://dx.doi.org/10.20310/2587-9340-2021-5-18-281-295.
Full textNguyen, Duc Hanh, and Thi Mai Dinh. "Legal framework for wildlife farming benefits species conservation and preventing wildlife crimes in Vietnam." E3S Web of Conferences 175 (2020): 03025. http://dx.doi.org/10.1051/e3sconf/202017503025.
Full textVera, José Carlos. "Instrumentos de análisis para identificar operaciones de lavado de dinero." Cuadernos de difusión 11, no. 21 (December 30, 2006): 69–95. http://dx.doi.org/10.46631/jefas.2006.v11n21.04.
Full textYakovleva, Margarita, and Elena Marchenko. "Historical prerequisites for legal regulation of prevention crimes committed by the Internal Affairs bodies of the Russian Federation." Vestnik of the St. Petersburg University of the Ministry of Internal Affairs of Russia 2020, no. 2 (July 21, 2020): 72–81. http://dx.doi.org/10.35750/2071-8284-2020-2-72-81.
Full textБулгакова, Марина, and Marina Bulgakova. "Holding certain types of legal expertise in criminal cases related to illegal forestry." Services in Russia and abroad 9, no. 1 (June 25, 2015): 3–13. http://dx.doi.org/10.12737/11703.
Full textNasir, Noorul Azwin Md, Hafiza Aishah Hashim, Noorshella Che Nawi, Mohd Nor Hakimin Yusoff, and Nur Athirah Mohd Aluwi. "Enhancing Financial Reporting Quality through Corporate Ethics Commitment: A Malaysian Review." 12th GLOBAL CONFERENCE ON BUSINESS AND SOCIAL SCIENCES 12, no. 1 (October 8, 2021): 72. http://dx.doi.org/10.35609/gcbssproceeding.2021.12(72).
Full textDissertations / Theses on the topic "Detect economic crimes"
Ahlm, Kristoffer. "IDENTIFIKATION AV RISKINDIKATORER I FINANSIELL INFORMATION MED HJÄLP AV AI/ML : Ökade möjligheter för myndigheter att förebygga ekonomisk brottslighet." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-184818.
Full textEconomic crimes are more lucrative compared to other crimes as drugs, selling of stolen gods, trafficing. Early preventions that make it more difficult for criminals to use companies for criminal purposes can reduce large costs for sociaty. A litterature study showed that there are large weaknesses in the collaboration between Swedish authorities to detect serious economic crimes.Today most crimes among companies that commit fraud are found after a company has declared bancruptcy. In studies, machine learning models have been tested to detect economic crimes and some swedish authorites are now using machine learning methods to detect different crimes and more advanced methods are used by the danish authorites. Bolagsverket has a large register of companies in Sweden and the aim of this study is to investigate if machinelearning can be used to detect on annual reports that have been digitaly submited and information in Bolagsverket’s register to be able to train classificationsmodels and identify companies that are suspicious. To be able to train the model lawsuits have been collected from the Swedish Economic Crime Authority that can be connected to specific companies through their digitally submited annual report. Principal component analysis is used to visually show differences between the groups suspect companies and not suspected companies and the analysis show that there is an overlap between the groups and no clear clustering between the groups. Because the dataset was unbalanced with 38 suspicious companies out of 1009 companies the oversampling tecnique SMOTE was used to create more synthethic data and more suspects in the dataset. The two machinelearnings models Random Forest and support vector machine (SVM) was compared in a 10 fold crossvalidation. Both models showed a recall on around 0.91 but Random Forest had a much higher precision with a higher accuracy. Random Forest was chosen and was trained again and showed a recall on 0.75 when it was tested on unseen data with 8 suspects out of 202 companies. Lowering the treshold resulted in a higher recall but with a larger portion of wrongly classfied companies. The study shows clearly the problem with an unbalanced dataset and the challanges with a small dataset. A larger dataset could have made it possible to make a more selective selection of certain crimes that could have resulted in a more robust model that could be used by Bolagsverket to easier identify suspicous companies in their register.
Books on the topic "Detect economic crimes"
Padgett, Simon. Profiling the Fraudster: Removing the Mask to Prevent and Detect Fraud. Wiley & Sons, Incorporated, John, 2014.
Find full textPadgett, Simon. Profiling the Fraudster: Removing the Mask to Prevent and Detect Fraud. Wiley & Sons, Incorporated, John, 2014.
Find full textProfiling The Fraudster: Removing the Mask to Prevent and Detect Fraud. Wiley, 2014.
Find full textMorlino, Leonardo. Equality, Freedom, and Democracy. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198813873.001.0001.
Full textBook chapters on the topic "Detect economic crimes"
Zuev, Sergey V. "Artificial Intelligence Internet Monitoring to Detect and Solve Crimes." In Digital Future Economic Growth, Social Adaptation, and Technological Perspectives, 637–43. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39797-5_61.
Full textGupta, Rohan Prasad, and Bappaditya Biswas. "Banking Scams in India." In Money Laundering and Terrorism Financing in Global Financial Systems, 304–24. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-8758-4.ch013.
Full textShiffman, Gary M. "17. Economic Security." In Contemporary Security Studies, 253–67. Oxford University Press, 2018. http://dx.doi.org/10.1093/hepl/9780198804109.003.0017.
Full textShiffman, Gary M. "17. Economic Security." In Contemporary Security Studies. Oxford University Press, 2015. http://dx.doi.org/10.1093/hepl/9780198708315.003.0017.
Full textKarakuş, Rıfat, Şeyma Yılmaz Küçük, and İbrahim Bozkurt. "Volatility Spillover Between Developed and Developing Markets During Crisis Period." In Advances in Finance, Accounting, and Economics, 230–48. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3767-0.ch012.
Full textVesan, Patrik, and Emmanuele Pavolini. "The Italian labour market policy reforms and the economic crisis: coming towards the end of Italian exceptionalism?" In Labour Market Policies in the Era of Pervasive Austerity. Policy Press, 2018. http://dx.doi.org/10.1332/policypress/9781447335863.003.0004.
Full textBen Sassi, Salim, and Azza Bejaoui. "On the Impact of Long Memory on Market Risk." In Advances in Finance, Accounting, and Economics, 42–62. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3767-0.ch003.
Full textWilliams, Nick. "Returnee Entrepreneurship and Institutions." In The Diaspora and Returnee Entrepreneurship, 37–59. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780190911874.003.0003.
Full textSmith, Matthew R. "A comparative analysis of the criminal and civil justice systems in England and Wales." In Law in Popular Belief. Manchester University Press, 2017. http://dx.doi.org/10.7228/manchester/9780719097836.003.0006.
Full textvan Santen, Rutger, Djan Khoe, and Bram Vermeer. "Smarter Electronics." In 2030. Oxford University Press, 2010. http://dx.doi.org/10.1093/oso/9780195377170.003.0019.
Full textConference papers on the topic "Detect economic crimes"
Yılmaz, Durmuş. "Global Economy and Turkey: 2016 and Beyond." In International Conference on Eurasian Economies. Eurasian Economists Association, 2016. http://dx.doi.org/10.36880/c07.01815.
Full textAksu, Muharrem, Ali Rıza Aktaş, Onur Oku, and Faruk Kerem Şentürk. "Analysis of Security Perceptions of Foreign Tourists: The Case of Alanya." In International Conference on Eurasian Economies. Eurasian Economists Association, 2013. http://dx.doi.org/10.36880/c04.00759.
Full textNagy, Péter Artúr. "Effects of the Global Financial Crisis on the V4." In The European Union’s Contention in the Reshaping Global Economy. Szeged: Szegedi Tudományegyetem Gazdaságtudományi Kar, 2020. http://dx.doi.org/10.14232/eucrge.2020.proc.7.
Full textSawa, Takao, Takafumi Kasaya, Tadahiro Hyakudome, and Hiroshi Yoshida. "Natural Resource Exploration With Sonar on Underwater Vehicle." In ASME 2012 31st International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/omae2012-83819.
Full textLukić Radović, Maja, and Marija Vlajković. "HOW FIRM ARE THE BONDS THAT TIE THE EU TOGETHER? EU RULE OF LAW CONDITIONALITY MECHANISM AND THE NEXT GENERATION EU RECOVERY FUND." In EU 2021 – The future of the EU in and after the pandemic. Faculty of Law, Josip Juraj Strossmayer University of Osijek, 2021. http://dx.doi.org/10.25234/eclic/18299.
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