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61
Correspondence Learning for Deep Multi-Modal Recognition and Fraud Detection
Published 2021-03-01“…In addition, we propose a fraud detection method using the learned correspondence among modalities. …”
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62
BUILDING CLASSIFICATION MODELS FROM IMBALANCED FRAUD DETECTION DATA
Published 2014-10-01“…This paper reports our experience in applying data balancing techniques to develop a classifier for an imbalanced real-world fraud detection data set. We evaluated the models generated from seven classification algorithms with two simple data balancing techniques. …”
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63
Application of Neural Network in Fraud Detection Using Business Concepts
Published 2003-06-01Subjects: Get full text
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64
Credit Card Fraud Detection using Deep Learning Techniques
Published 2021-01-01Get full text
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65
The accuracy versus interpretability trade-off in fraud detection model
Published 2021-01-01Subjects: Get full text
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66
Credit Card Fraud Detection with Autoencoder and Probabilistic Random Forest
Published 2021-10-01Subjects: Get full text
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67
Transformative Leadership, Locus Of Control On Fraud Detection And Environmental Performance
Published 2022-09-01“…The results of this study are transformational leadership has a positive effect on fraud detection, locus of control has a positive effect on fraud detection, the environmental performance has a positive effect on fraud detection, and environmental performance can strengthen the influence of transformational leadership on fraud detection, and environmental performance can strengthen the influence of locus of control on fraud detection.…”
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68
Big Data and Specific Analysis Methods for Insurance Fraud Detection
Published 2014-02-01Subjects: Get full text
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69
Sequence Mining and Prediction-Based Healthcare Fraud Detection Methodology
Published 2020-01-01“…This article presents a novel methodology to detect insurance claim related frauds in the healthcare system using concepts of sequence mining and sequence prediction. Fraud detection in healthcare is a non-trivial task due to the heterogeneous nature of healthcare records. …”
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70
Determinants influencing fraud detection: Role of internal auditors’ quality
Published 2024-04-01“…The purpose of this study is to ascertain the impact of internal audit effectiveness and continued professional commitment to fraud detection with internal auditors’ quality as a moderating variable. …”
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71
Methods of Handling Unbalanced Datasets in Credit Card Fraud Detection
Published 2020-03-01Get full text
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72
Click fraud detection for online advertising using machine learning
Published 2023-07-01Get full text
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73
Credit Card Fraud Detection with Automated Machine Learning Systems
Published 2022-12-01“…In this paper, we apply the Just-Add-Data (JAD), a system that automates the selection of Machine Learning algorithms, the tuning of their hyper-parameter values, and the estimation of performance in detecting fraudulent transactions using a highly unbalanced dataset, swiftly providing prediction model for credit card fraud detection. The training of the model does not require the user setting up any of the methods’ (hyper)parameters. …”
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74
Prediction of Insurance Fraud Detection using Machine Learning Algorithms
Published 2022-01-01Get full text
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75
Remote banking fraud detection framework using sequence learners
Published 2019“…The reliability and performance of fraud detection techniques has been a major concern for the financial institutions as traditional fraud detection models couldn’t cope with the emerging new and innovative attacks that deceive banks. …”
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76
In-network machine learning for real-time transaction fraud detection
Published 2024“…In this paper, we introduce MIND, conducting ML-based fraud detection within programmable devices. MIND is prototyped on both software and hardware network devices, including BMv2, Intel Tofino, and NVIDIA BlueField-2 DPU, and is evaluated with three publicly available transaction datasets. …”
Conference item -
77
Fraud detection in telecommunication industry using Gaussian mixed model
Published 2013“…In this article, we propose a new fraud detection algorithm using Gaussian mixed model (GMM), a probabilistic model successfully used in speech recognition problem. …”
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Conference or Workshop Item -
78
Forensic accounting: the use of Benford's law to evaluate indications of fraud
Published 2022-04-01Subjects: “…Fraud Detection…”
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