The Imbalanced Classification of Fraudulent Bank Transactions Using Machine Learning
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Marina Pavlovna Khrestina & Dmitry Ivanovich Dorofeev & Polina Andreevna Kachurina & Timur Rinatovich Usubaliev & Aleksey Sergeevich Dobrotvorskiy, 2017. "Development of Algorithms for Searching, Analyzing and Detecting Fraudulent Activities in the Financial Sphere," European Research Studies Journal, European Research Studies Journal, vol. 0(4B), pages 484-498.
- Ayed Alwadain & Rao Faizan Ali & Amgad Muneer, 2023. "Estimating Financial Fraud through Transaction-Level Features and Machine Learning," Mathematics, MDPI, vol. 11(5), pages 1-15, February.
- Surjeet Dalal & Bijeta Seth & Magdalena Radulescu & Carmen Secara & Claudia Tolea, 2022. "Predicting Fraud in Financial Payment Services through Optimized Hyper-Parameter-Tuned XGBoost Model," Mathematics, MDPI, vol. 10(24), pages 1-17, December.
- Singh, Kishore & Best, Peter, 2019. "Anti-Money Laundering: Using data visualization to identify suspicious activity," International Journal of Accounting Information Systems, Elsevier, vol. 34(C), pages 1-1.
- Tzu-Hsuan Lin & Jehn-Ruey Jiang, 2021. "Credit Card Fraud Detection with Autoencoder and Probabilistic Random Forest," Mathematics, MDPI, vol. 9(21), pages 1-16, October.
- Emanuel Mineda Carneiro & Carlos Henrique Quartucci Forster & Lineu Fernando Stege Mialaret & Luiz Alberto Vieira Dias & Adilson Marques da Cunha, 2022. "High-Cardinality Categorical Attributes and Credit Card Fraud Detection," Mathematics, MDPI, vol. 10(20), pages 1-23, October.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Zeinab Rouhollahi, 2021. "Towards Artificial Intelligence Enabled Financial Crime Detection," Papers 2105.10866, arXiv.org.
- Ogbeide, Henry & Thomson, Mary Elizabeth & Gonul, Mustafa Sinan & Pollock, Andrew Castairs & Bhowmick, Sanjay & Bello, Abdullahi Usman, 2023. "The anti-money laundering risk assessment: A probabilistic approach," Journal of Business Research, Elsevier, vol. 162(C).
- Martin Leo & Suneel Sharma & K. Maddulety, 2019. "Machine Learning in Banking Risk Management: A Literature Review," Risks, MDPI, vol. 7(1), pages 1-22, March.
- Ludivia Hernandez Aros & Luisa Ximena Bustamante Molano & Fernando Gutierrez-Portela & John Johver Moreno Hernandez & Mario Samuel Rodríguez Barrero, 2024. "Financial fraud detection through the application of machine learning techniques: a literature review," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-22, December.
- Lisa Perkhofer & Conny Walchshofer & Peter Hofer, 2020. "Does design matter when visualizing Big Data? An empirical study to investigate the effect of visualization type and interaction use," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 31(1), pages 55-95, April.
- Sharma, Gagan Deep & Tiwari, Aviral Kumar & Chopra, Ritika & Dev, Dhairya, 2024. "Past, present, and future of block-chain in finance," Journal of Business Research, Elsevier, vol. 177(C).
- Hugo Núñez Delafuente & César A. Astudillo & David Díaz, 2024. "Ensemble Approach Using k-Partitioned Isolation Forests for the Detection of Stock Market Manipulation," Mathematics, MDPI, vol. 12(9), pages 1-18, April.
- Bolin Liao & Zhendai Huang & Xinwei Cao & Jianfeng Li, 2022. "Adopting Nonlinear Activated Beetle Antennae Search Algorithm for Fraud Detection of Public Trading Companies: A Computational Finance Approach," Mathematics, MDPI, vol. 10(13), pages 1-14, June.
- Parsaee Tabar , Azam & Abdolvand , Neda & Rajaee Harandi , Saeedeh, 2021. "Identifying the Suspected Cases of Money Laundering in Banking Using Multiple Attribute Decision Making (MADM)," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 16(1), pages 1-20, March.
- repec:ers:journl:v:volumexxi:y:2018:i:issue4:p:524-532 is not listed on IDEAS
- Seyed Farshid Ghorashi & Maziyar Bahri & Atousa Goodarzi, 2024. "Developing and comparing machine learning approaches for predicting insurance penetration rates based on each country," Letters in Spatial and Resource Sciences, Springer, vol. 17(1), pages 1-29, December.
- Tolendi Ashimbayev & Sarkyt Tashenova, 2018. "Prospects for Using Cryptocurrency in the Economy of Kazakhstan and the Attitude of the National Bank," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 524-532.
- Dawei Cheng & Yao Zou & Sheng Xiang & Changjun Jiang, 2024. "Graph Neural Networks for Financial Fraud Detection: A Review," Papers 2411.05815, arXiv.org, revised Nov 2024.
More about this item
Keywords
bank transactions; imbalanced classification; detection of fraudulent transactions; machine learning;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:11:y:2023:i:13:p:2862-:d:1179718. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.