Multi-future Merchant Transaction Prediction
نویسندگان
چکیده
The multivariate time series generated from merchant transaction history can provide critical insights for payment processing companies. capability of predicting merchants’ future is crucial fraud detection and recommendation systems. Conventionally, this problem formulated to predict one under the multi-horizon setting. However, real-world applications often require more than trend prediction considering uncertainties, where needs be predicted. This called multi-future prediction. In work, we combine two research directions propose study new problem: multi-future, as it has broad use cases in financial industry reduce risk while improving user experience by providing alternative futures. also challenging now not only need capture patterns past but train a model that strong inference project multiple possible outcomes. To solve problem, using convolutional neural networks simple yet effective encoder-decoder structure learn pattern perspectives. We experiments on data demonstrate effectiveness our proposed model. extensive discussions different design choices experimental section.
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H. WANG∗,§, E. VAN BOVEN∗,†,¶, A. KRISHNAKUMAR†, M. HOSSEINI∗,†, H. VAN HOOFF‡, T. TAKEMA‡, N. BAKEN∗,† and P. VAN MIEGHEM∗ ∗Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, P. O. Box 5031, 2600 GA Delft, The Netherlands †KPN Royal, P. O. Box 30.000, 2500 GA The Hague, The Netherlands ‡Statistics Netherlands, P. O. Box 24.500, 2490 HA, The Ha...
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ژورنال
عنوان ژورنال: Lecture Notes in Computer Science
سال: 2021
ISSN: ['1611-3349', '0302-9743']
DOI: https://doi.org/10.1007/978-3-030-67670-4_17