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Alejandro Correa Bahnsen
Researcher at University of Luxembourg
Publications - 22
Citations - 1024
Alejandro Correa Bahnsen is an academic researcher from University of Luxembourg. The author has contributed to research in topics: Credit card fraud & Computer science. The author has an hindex of 12, co-authored 19 publications receiving 754 citations.
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Journal ArticleDOI
Feature engineering strategies for credit card fraud detection
TL;DR: This paper proposes to create a new set of features based on analyzing the periodic behavior of the time of a transaction using the von Mises distribution, and examines how the different sets of features have an impact on the results.
Journal ArticleDOI
Example-dependent cost-sensitive decision trees
TL;DR: The results show that the proposed algorithm is the best performing method for all databases, and when compared against a standard decision tree, the method builds significantly smaller trees in only a fifth of the time, while having a superior performance measured by cost savings.
Proceedings ArticleDOI
Classifying phishing URLs using recurrent neural networks
Alejandro Correa Bahnsen,Eduardo Contreras Bohorquez,Sergio Villegas,Javier Vargas,Fabio A. González +4 more
TL;DR: This work explored the use of URLs as input for machine learning models applied for phishing site prediction and determined that the recurrent neural network approach provides an accuracy rate of 98.7% even without the need of manual feature creation, beating by 5% the random forest method.
Proceedings ArticleDOI
Cost Sensitive Credit Card Fraud Detection Using Bayes Minimum Risk
TL;DR: A new comparison measure that realistically represents the monetary gains and losses due to fraud detection is proposed and using the proposed cost measure a cost sensitive method based on Bayes minimum risk is presented.
Proceedings ArticleDOI
Example-Dependent Cost-Sensitive Logistic Regression for Credit Scoring
TL;DR: A new example-dependent cost matrix for credit scoring is proposed and an algorithm that introduces the example- dependent costs into a logistic regression is proposed that highlights the importance of using real financial costs.