Variational quantum algorithm for unconstrained black box binary optimization: Application to feature selection by Christa Zoufal, Ryan V. Mishmash, Nitin Sharma, Niraj Kumar, Aashish Sheshadri, Amol Deshmukh, Noelle Ibrahim, Julien Gacon, Stefan Woerner

“…This refers to the problem of selecting a subset of relevant features to use for constructing a predictive model such as fraud detection. Optimal feature selection---when formulated in terms of a generic loss function---offers little structure on which to build classical heuristics, thus resulting primarily in ‘greedy methods’. …”
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Bitcoin Money Laundering Detection via Subgraph Contrastive Learning by Shiyu Ouyang, Qianlan Bai, Hui Feng, Bo Hu

“…In recent years, leveraging graph neural networks for cryptocurrency fraud detection has yielded promising results. However, many existing methods predominantly focus on node classification, i.e., detecting individual illicit transactions, rather than uncovering behavioral pattern differences among money laundering groups. …”
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Evaluating classifier performance with highly imbalanced Big Data by John T. Hancock, Taghi M. Khoshgoftaar, Justin M. Johnson

“…We evaluate the performance of five ensemble learners in the Machine Learning task of Medicare fraud detection. Random Undersampling (RUS) is applied to induce five class ratios. …”
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An Empirical Assessment of Performance of Data Balancing Techniques in Classification Task by Anil Jadhav, Samih M. Mostafa, Hela Elmannai, Faten Khalid Karim

“…Many real-world classification problems such as fraud detection, intrusion detection, churn prediction, and anomaly detection suffer from the problem of imbalanced datasets. …”
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Exploring the evolution of creative accounting and external auditors: Bibliometric analysis by Ayman Mohammad ALShanti, Hani Abdel Hafez Al-Azab, Mohammad Mahmoud Humeedat, Mohammad Zakaria AlQudah

“…The third trend is Financial Statement Audit Quality Management for Earnings Management and Fraud Detection (blue and purple clusters). The fourth trend is related to Preventing the Next Financial fraud: A Global Creative Accounting (yellow cluster).…”
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A Hybrid Simulated Annealing and Back-propagation Algorithm for Feed-forward Neural Network to Detect Credit Card Fraud by Ardalan Husin Awlla

“…A reasonable seeing on all these methodologies will absolutely lead to an efficient credit card fraud detection framework. This paper suggested an anomaly detection model based on a hybrid simulated annealing (SA) and back-propagation algorithm for feed-forward neural network (FFNN), which joined the significant global searching capability of SA with the precise local searching element of back-propagation FFNNs to improve theinitial weights of a neural network toward getting a better result for detection fraud.…”
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Gaussian Mixture Reduction for Time-Constrained Approximate Inference in Hybrid Bayesian Networks by Cheol Young Park, Kathryn Blackmond Laskey, Paulo C. G. Costa, Shou Matsumoto

“…Hybrid Bayesian Networks (HBNs), which contain both discrete and continuous variables, arise naturally in many application areas (e.g., image understanding, data fusion, medical diagnosis, fraud detection). This paper concerns inference in an important subclass of HBNs, the conditional Gaussian (CG) networks, in which all continuous random variables have Gaussian distributions and all children of continuous random variables must be continuous. …”
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Continuous-variable quantum neural networks by Killoran, Nathan, Bromley, Thomas R., Arrazola, Juan Miguel, Schuld, Maria, Quesada, Nicolás, Lloyd, Seth

“…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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Detecting accounting anomalies using Benford's Law: evidence from the Malaysian public sector / Nooraslinda Abdul Aris ... [et al.] by Abdul Aris, Nooraslinda, Othman, Rohana, Mohd Bukhori, Muhamad Anas, Mohd Arif, Siti Maznah, Abdul Malek, Mohamad Affendi

“…Thus, with respect to fraud, detection, investigation, and preventive measures are extremely important. …”
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Mental Card Gaming Protocols Supportive Of Gameplay Versatility, Robustness And Efficiency by Soo, Wai Han

“…priori distrustful and potentially untrustworthy remote parties and should minimally providewithout the introduction of a trusted third party (TTP)---for card confidentiality, fraud detection and conditional security against collusion. …”
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Early Detection Method for Money Fraudulent Activities on E-commerce Platform via Sentiment Analysis by Misiran, Masnita, Shi Er, Tan, Pheng Hong, Augustus Saw, Mohd Subri, Nur Azuin, Ahmad Darus, Nur Syazana, Md Yusof, Zahayu, Ahmad, Nazihah

“…The data were converted into measurable metrics to enable quantitative fraud detection. The model enabled the early detection of possible money fraudulent activities on Shopee products based on customers’ reviews. …”
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Practices of artificial intelligence to improve the business in Bangladesh by Md. Touhidul Islam, Md. Mahadi Hasan, Md. Redwanuzzaman, Md. Kamal Hossain

“…According to the results, using AI in enterprises may have a significant positive impact on efficiency, decision-making, production, cost, fraud detection, and supply chain optimization. However, obstacles to AI deployment include a lack of qualified personnel, poor data quality, money, infrastructure, and legal frameworks. …”
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COMPARATIVE ANALYSIS OF METHODS FOR IMBALANCE ELIMINATION OF EMOTION CLASSES IN VIDEO DATA OF FACIAL EXPRESSIONS by Elena V. Ryumina, Alexey A. Karpov

“…The imbalance of classes in datasets has a negative impact on machine classification systems used in applications of artificial intelligence, such as: medical diagnostics, fraud detection and risk management. This problem in facial expression datasets also degrades the performance of classification algorithms. …”
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Systemic Acquired Critique of Credit Card Deception Exposure through Machine Learning by Rui Miguel Dantas, Raheela Firdaus, Farrokh Jaleel, Pedro Neves Mata, Mário Nuno Mata, Gang Li

“…This study identifies the crucial gaps which ultimately allow research opportunities in this fraud detection process by utilizing knowledge from the machine learning domain. …”
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Identifying Credit Card Fraud in Illegal Transactions Using Random Forest and Decision Tree Algorithms by Indah Werdiningsih, Endah Purwanti, Gede Rangga Wira Aditya, Auliya Rakhman Hidayat, R. Sulthan Rafi Athallah, Virda Adisty Sahar, Tio Satrio Wibisono, Darren Febriand Nura Somba

“…To overcome this, many financial institutions have developed credit card fraud detection systems that can identify suspicious transactions. …”
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A Review of Local Outlier Factor Algorithms for Outlier Detection in Big Data Streams by Omar Alghushairy, Raed Alsini, Terence Soule, Xiaogang Ma

“…Outlier detection is important in many applications, including fraud detection in credit card transactions and network intrusion detection. …”
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Botanical Origin Assessment of Honey Based on ATR-IR Spectroscopy: A Comparison between the Efficiency of Supervised Statistical Methods and Artificial Intelligence by Maria David, Ariana Raluca Hategan, Dana Alina Magdas, Camelia Berghian-Grosan, Bianca Simionescu

“…Food authenticity control represents a constant concern nowadays, and against this background, new means of food fraud detection are developed by research and control laboratories. …”
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Imperative Node Evaluator With Self Replication Mode for Network Intrusion Detection by Ragini Mokkapati, D. Venkata Lakshmi

“…Monitoring user activity for abnormalities is a useful fraud detection strategy. The ability of a system to efficiently discover new, previously unknown vulnerabilities and respond in a way that minimises damage and, ideally, removes the threat, is one of the most important open research topics in the field of cyber security. …”
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Chinese corporate fraud risk assessment with machine learning by Qingyang Lu, Chuyan Fu, Kailiang Nan, Yichu Fang, Jialue Xu, Jinyao Liu, Anthony Graham Bellotti, Boon Giin Lee

“…We also present an efficient and accurate framework for corporate fraud detection that could be used as a fraud risk early warning system for financial institutions and regulatory authorities. …”
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Heterogeneous Network-Based Chronic Disease Progression Mining by Chenfei Sun, Qingzhong Li, Lizhen Cui, Hui Li, Yuliang Shi

“…They also do not take into account the different medication stages of the same chronic disease, which is of great help when conducting healthcare insurance fraud detection and reducing healthcare costs. In this paper, we propose a heterogeneous network-based chronic disease progression mining method to improve the current understanding on the progression of chronic diseases, including orphan diseases. …”
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