مشخصات مقاله | |
ترجمه عنوان مقاله | کشف تقلب مالی با استفاده از تکنیک های داده کاوی: بررسی جامع از سال ۲۰۰۹ تا ۲۰۱۹ |
عنوان انگلیسی مقاله | Financial fraud detection applying data mining techniques: A comprehensive review from 2009 to 2019 |
انتشار | مقاله سال ۲۰۲۱ |
تعداد صفحات مقاله انگلیسی | ۲۳ صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
پایگاه داده | نشریه الزویر |
نوع نگارش مقاله |
مقاله مروری (Review Article) |
مقاله بیس | این مقاله بیس میباشد |
نمایه (index) | Scopus – Master Journals List – JCR |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
ایمپکت فاکتور(IF) |
۷٫۸۷۲ در سال ۲۰۲۰ |
شاخص H_index | ۴۴ در سال ۲۰۲۰ |
شاخص SJR | ۱٫۶۴۶ در سال ۲۰۲۰ |
شناسه ISSN | ۱۵۷۴-۰۱۳۷ |
شاخص Quartile (چارک) | Q1 در سال ۲۰۲۰ |
فرضیه | ندارد |
مدل مفهومی | ندارد |
پرسشنامه | ندارد |
متغیر | ندارد |
رفرنس | دارد |
رشته های مرتبط | مدیریت، اقتصاد، حسابداری |
گرایش های مرتبط | مدیریت مالی، اقتصاد مالی، مهندسی مالی و ریسک، حسابداری مالی |
نوع ارائه مقاله |
ژورنال |
مجله | بررسی علوم کامپیوتر – Computer Science Review |
دانشگاه | Advanced Informatics Department, Razak Faculty of Technology and Informatics, Universiti Teknologi Malaysia, Malaysia |
کلمات کلیدی | کلاهبرداری مالی، تکنیک داده کاوی، کلاهبرداری کارت اعتباری، تقلب دربیمه، تقلب بیت کوین، تقلب در صورت های مالی |
کلمات کلیدی انگلیسی | Financial fraud – Data mining technique – Credit card fraud – Insurance fraud – Bitcoin fraud – Financial statement fraud |
شناسه دیجیتال – doi |
https://doi.org/10.1016/j.cosrev.2021.100402 |
کد محصول | E15882 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
Abstract Keywords Introduction Types of financial fraud Methodology Literature review Results Conclusion and future work CRediT authorship contribution statement Declaration of Competing Interest Acknowledgment References |
بخشی از متن مقاله: |
Abstract This paper gives a comprehensive revision of the state-of-the-art research in detecting financial fraud from 2009 to 2019 inclusive and classifying them based on their types of fraud and data mining technology utilized in detecting financial fraud. The review result yielded a sample of 75 relevant articles (58 conference papers with 17 peer-reviewed journal articles) that are categorized into four main groups (bank fraud, insurance fraud, financial statement fraud, and cryptocurrency fraud). The study shows that 34 data mining techniques were used to identify fraud throughout various financial applications. The SVM is found to be one of the most widely used financial fraud detection techniques that carry about 23% of the overall study, followed by both Naïve Bayes and Random Forest, resulting in 15%. The results of our comprehensive review revealed that most data mining techniques are extensively implemented to bank fraud and insurance fraud with a total of 61 research studies out of 75 that constitute the largest portion equal to 81.33% of the overall number of papers. This review provides a good reference source in guiding the detection of financial fraud for both academic and practical industries with useful information on the most significant data mining techniques used and shows the list of countries that are exposed to financial fraud. Our review contributes by expanding the sample of the reviewed articles that were not included by previous research and presents a summary of the prominent works done by various researchers in the field of financial fraud. Introduction Over the past years, a technological revolution has occurred on the Internet that paved to the emergence of modern services especially in e-commerce and money transfer. E-commerce is one of the many economic domains in information and communications technology that contributed to business improvement, paved the way for managing medium and small companies, reducing costs and saving time, and increasing productivity [1]. The growth in ecommerce enabled most companies and organizations to perform their financial transactions electronically through the adoption of payment systems such as Healthcare Insurance systems, Telecommunication systems, and the Financial Sector. Lately, there is a noticeable rise in the number of financial transactions due to the large adoption of Internet bank services and financial institutions as well as e-commerce |