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Estimating Financial Fraud through Transaction-Level Features and Machine Learning

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Credit Card Fraud Detection using Machine Learning Algorithms
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Artificial intelligence and machine learning in finance: A bibliometric review
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Financial fraud, scandals, and regulation: A conceptual framework and literature review
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Credit Card Fraud Detection Using Lightgbm Model
inferredcites →https://doi.org/10.1109/eeei.2010.5662159openalex-snapshot
Using the confusion matrix for improving ensemble classifiers
inferredcites →https://doi.org/10.1109/esmarta59349.2023.10293697openalex-snapshot
Fraudulent Financial Transactions Detection Using Machine Learning
inferredcites →https://doi.org/10.1109/icbaie49996.2020.00045openalex-snapshot
A Deep Neural Network Algorithm for Detecting Credit Card Fraud
inferredcites →https://doi.org/10.1111/eufm.12326openalex-snapshot
Machine learning in finance: A topic modeling approach
inferredcites →https://doi.org/10.1155/2014/252797openalex-snapshot
FraudMiner: A Novel Credit Card Fraud Detection Model Based on Frequent Itemset Mining
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An Evaluation of the Effect of Fraud and Related Financial Crimes on the Nigerian Economy
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Deep Learning in Finance: From Implementation to Regulation
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Machine Learning for Credit Card Fraud Detection System
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A Hybrid Approach for Credit Card Fraud Detection using Rough Set and Decision Tree Technique
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What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Identifying and Preventing Fraudulent Activities in Financial Transactions Using Artificial Intelligence
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An explainable ensemble learning approach for financial fraud detection: Integrating SHAP and LIME on the PaySim dataset
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Financial fraud detection through the application of machine learning techniques: a literature review
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Financial Fraud Detection Using Value-at-Risk With Machine Learning in Skewed Data
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Artificial Immune System and Machine Learning: A Synergistic Approach for Banking Fraud Detection
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AutoML-Driven Architecture Optimization for Efficient and Scalable Neural Network Design
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Unveiling Financial Fraud: A Comprehensive Review of Machine Learning and Data Mining Techniques
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Behavioral--Transactional Data Analytics using Hierarchical Feature Fusion with Attention Deep Learning Model for E-Commerce Fraud Detection
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Analysing Machine Learning Algorithms for Identifying Fraudulent Financial Transactions
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An Introduction to Machine Learning Methods for Fraud Detection
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The Imbalanced Classification of Fraudulent Bank Transactions Using Machine Learning
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Machine Learning in Financial Transaction Fraud Detection and Prevention
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