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Intelligent Fraud Detection Framework for PFMS Using HGRO Feature Selection and OC-LSTM Fraud Detection Technique
In public financial management systems (PFMS), one of the highly challenging fields is financial fraud (FF). Governments have formulated stricter...
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Combatting Fraud
While the previous chapter was a must know for all computer users, parts of this chapter are a must know for all employees. Everyone who handles or...
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A semi-supervised Anti-Fraud model based on integrated XGBoost and BiGRU with self-attention network: an application to internet loan fraud detection
Recently, fraud debt has been one of the major issues for Internet financial institutions. Due to fraudulent activities, huge losses are occurring in...
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Attention layer integrated BiLSTM for financial fraud prediction
The world is turning to financial fraud as a base for daily transactions due to the rapid growth of digital technologies, which creates numerous new...
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A Comprehensive Fraud Detection for Credit Card Transactions in Federated Averaging
Credit card fraud costs card issuers billions of dollars each year. Therefore, an effective Fraud Detection System (FDS) is crucial to minimize...
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Fraud detection with natural language processing
Automated fraud detection can assist organisations to safeguard user accounts, a task that is very challenging due to the great sparsity of known...
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Double-weight LDA extracting keywords for financial fraud detection system
The impact of financial fraud is widespread, from everyday life to the financial industry, and it reduces industry confidence and destabilizes the...
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An augmented AI-based hybrid fraud detection framework for invoicing platforms
In this era of e-commerce, many companies are moving towards subscription-based invoicing platforms to maintain their electronic invoices....
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Auto-Encoder and LSTM-Based Credit Card Fraud Detection
The increased fraud risk due to the most recent methods of paying with a credit card, such as real-time payments and cards with near-field...
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Data-Centric AI for Healthcare Fraud Detection
Automated methods for detecting fraudulent healthcare providers have the potential to save billions of dollars in healthcare costs and improve the...
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Explainable machine learning models for Medicare fraud detection
As a means of building explainable machine learning models for Big Data, we apply a novel ensemble supervised feature selection technique. The...
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An intelligent sequential fraud detection model based on deep learning
Fraud detection and prevention has received a lot of attention from the research community due to its high impact on financial institutions’ revenues...
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CFTNet: a robust credit card fraud detection model enhanced by counterfactual data augmentation
Establishing a reliable credit card fraud detection model has become a primary focus for academia and the financial industry. The existing anti-fraud...
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Fraud detection from paper texture using Siamese networks
In this paper, we present a model for the fraud detection of documents, using the texture of the paper on which they are printed. Different from...
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Investigating the effectiveness of one-class and binary classification for fraud detection
Research into machine learning methods for fraud detection is of paramount importance, largely due to the substantial financial implications...
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Improving fraud detection via imbalanced graph structure learning
Graph-based fraud detection methods have recently attracted much attention due to the rich relational information of graph-structured data, which may...
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Synthesizing class labels for highly imbalanced credit card fraud detection data
Acquiring labeled datasets often incurs substantial costs primarily due to the requirement of expert human intervention to produce accurate and...
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Federated learning model for credit card fraud detection with data balancing techniques
In recent years, credit card transaction fraud has resulted in massive losses for both consumers and banks. Subsequently, both cardholders and banks...
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Credit Card Fraud Detection: Addressing Imbalanced Datasets with a Multi-phase Approach
Credit card fraud detection plays a crucial role in safeguarding the financial security of individuals and organizations. However, imbalanced...
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Enhanced autoencoder-based fraud detection: a novel approach with noise factor encoding and SMOTE
Fraud detection is a critical task across various domains, requiring accurate identification of fraudulent activities within vast arrays of...
