Application of Imbalanced Data Classification Quality Metrics as Weighting Methods of the Ensemble Data Stream Classification Algorithms by Weronika Wegier, Pawel Ksieniewicz

“…This task is hindered by changing the distribution of data over time, called the concept drift, and the emergence of a problem of disproportion between classes—such as in the detection of network attacks or fraud detection problems. In the following work, we propose methods to modify existing stream processing solutions—Accuracy Weighted Ensemble (AWE) and Accuracy Updated Ensemble (AUE), which have demonstrated their effectiveness in adapting to time-varying class distribution. …”
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The practicality of forensic auditing techniques to detect non-government orgnaisations’ financial statement fraud in South Africa using a proactive approach by Jean Damascene Mvunabandi, Bomi Cyril Nomlala, Harold Patrick

“… This article empirically investigated proactive financial statement fraud detection techniques 30 among nongovernment organisations in the eThekwini region, South Africa. …”
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A Novel Clustering-Based Three Level Under-Sampling Algorithm for Class Imbalance Problem by Vibha Pratap, Amit Prakash Singh

“…The experimental results of this research can be used in the classification of various domains, such as medical diagnosis, banking fraud detection, anomaly detection, etc, which are generally imbalanced.…”
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Principal component analysis for authorship attribution by Amir Jamak, Alen Savatic, Mehmet Can

“…Methodology could be used for other purposes, like fraud detection in auditing.…”
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Continuous-variable quantum neural networks by Nathan Killoran, Thomas R. Bromley, Juan Miguel Arrazola, Maria Schuld, Nicolás Quesada, Seth Lloyd

“…These experiments, including a classifier for fraud detection, a network which generates tetris images, and a hybrid classical-quantum autoencoder, demonstrate the capability and adaptability of CV quantum neural networks.…”
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Corporate Governance in Detecting Lack of Financial Report by Syamsudin Syamsudin, Imronudin Imronudin, Sasongko Tri Utomo, Aflit Nuryulia Praswati

“…This study aims to investigate the phenomenon of corporate governance in detecting fraud or irregularities in the preparation of financial statements. Fraud detection is measured by the Beneish model.. The sample used in this research is 694 with manufacturing company period 2011-2015. …”
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How business value can be increased with analytics in the financial services industry by Buana Lintang Singarimbum

“…The elements including great data management, consumer segmentation, risk management, fraud detection, in addition to business value of banking industries are studied. …”
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Artificial intelligence ethics by design. Evaluating public perception on the importance of ethical design principles of artificial intelligence by Kimon Kieslich, Birte Keller, Christopher Starke

“…In this paper, we give first answers on the relative importance of ethical principles given a specific use case—the use of artificial intelligence in tax fraud detection. The results of a large conjoint survey ( n = 1099 ) suggest that, by and large, German respondents evaluate the ethical principles as equally important. …”
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A New Anomaly Detection System for School Electricity Consumption Data by Wenqiang Cui, Hao Wang

“…Anomaly detection has been widely used in a variety of research and application domains, such as network intrusion detection, insurance/credit card fraud detection, health-care informatics, industrial damage detection, image processing and novel topic detection in text mining. …”
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Deep learning enhancing banking services: a hybrid transaction classification and cash flow prediction approach by Dimitrios Kotios, Georgios Makridis, Georgios Fatouros, Dimosthenis Kyriazis

“…Our approach shows promising results on a real-world banking use case and acts as the foundation for the development of further BFM banking microservices, such as transaction fraud detection and budget monitoring.…”
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Resource Scheduling for Real-Time Analytical Workflow Services in the Cloud by Yan Yao, Jian Cao, Shiyou Qian, Xiaogang Wang

“…Some of data analytical applications, the data requests arrived continuously, such as fraud detection application and order application. In general, such workflow applications have a rigid requirement in relation to response time. …”
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Fast Bayesian optimization of Needle-in-a-Haystack problems using zooming memory-based initialization (ZoMBI) by Alexander E. Siemenn, Zekun Ren, Qianxiao Li, Tonio Buonassisi

“…Abstract Needle-in-a-Haystack problems exist across a wide range of applications including rare disease prediction, ecological resource management, fraud detection, and material property optimization. A Needle-in-a-Haystack problem arises when there is an extreme imbalance of optimum conditions relative to the size of the dataset. …”
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Management and reduction of fraud by analysis of the insurer’s internal and external vulnerabilities and contributions by Mihai Ovidiu Vădean

“…Then, given the wave of interest in the insurance industry, emphasis was placed on the use of approaches such as: a) cognitive interviewing and vocal stress analysis that were used in forensic investigation, as well; b) data extraction techniques, specially developed for fraud detection. Are just these effective? The material will try to analyze the vulnerabilities and contributions, both internal and external, that are introduced by the policies, procedures and controls implemented by the insurer within the organization.…”
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Innovation in banking: fusion of artificial intelligence and blockchain by Vedapradha R., Hariharan Ravi

“…Originality/value – A combination of artificial intelligence and blockchain ensures increasing automation to improve efficiency and reduce the operating cost creating a seamless integration in fraud detection, customer support, risk management, security, digitization and automation process, algorithmic trading, wealth management, etc.…”
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A New Method for Olive Oil Screening Using Multivariate Analysis of Proton NMR Spectra by Colleen L. Ray, James A. Gawenis, C. Michael Greenlief

“…The combination of simple sample preparation, rapid sample analysis, novel processing parameters, and easily interpreted results, makes this method an easily accessible tool for olive oil fraud detection by substitution or dilution compared to other methods already published.…”
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The Strategy to Optimize the Role of Government Internal Supervisory Apparatus (APIP) in Procurement Fraud Risk Management in Industry 4.0 by Mustofa Kamal, John Elim

“…Internal auditors must undertake fraud prevention by improving their ability in data analytics, encouraging probity plans, and procurement assistance. Fraud detection is carried out through performance audits using computer-assisted audit techniques, probity audits, information technology governance audits, continuous audits, data analytics, and internal auditor integrity assessments through surveys to the auditee. …”
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Detection of Credit Card Fraud with Machine Learning Methods and Resampling Techniques by Moh. Badris Sholeh Rahmatullah, Aulia Ligar Salma Hanani, Akmal Muhammad Naim, Zamah Sari, Yufis Azhar

“…The dataset used in this study is entitled "Credit Card Fraud Detection" with a total of 284807 data which is divided into two classes: Not Fraud and Fraud. …”
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Bibliometric Analysis of Artificial Intelligence in the Scope of E-Commerce: Trends and Progress over the Last Decade by Samira FRIOUI, Amel GRAA

“…Finally, the keyword co-occurrence network indicates that the most important keywords are machine learning, e-commerce, recommender systems, fraud detection, decision-making systems, data mining, and online retailing.…”
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Framework for Assessing Ethical Aspects of Algorithms and Their Encompassing Socio-Technical System by Xadya van Bruxvoort, Maurice van Keulen

“…The framework has been validated by applying it to real-world fraud detection cases: Systeem Risico Indicatie (SyRI) of the Dutch government and the algorithm of the municipality of Amersfoort. …”
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TVN: Detect Deepfakes Images using Texture Variation Network by Haseena S, Saroja S, Shri Dharshini D, Nivetha A.

“…We propose a new model, TVN, for robust face fraud detection, based on Convolution and pyramid pooling (PP), as a result of the aforesaid discovery. …”
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