Evaluation of a Fintech Sales Synthetic Data Generation Model Using a Generative Adversarial Network

Felipe A. Lopez, Marcia Duran-Riveros, Sebastian Maldonado-Duran, David Ruete, Giannina Costa, Jairo R. Coronado-Hernandez, Gustavo Gatica

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The need for more and better information for decision making is fundamental in modern organizations, especially in the financial industry. One type of this information is time series, which allow prediction and estimation of different scenarios, but are difficult to obtain for small and medium sized enterprises (SMEs). This research presents the design and validation of a generative adversarial network (GAN) capable of generating synthetic data for daily sales of Chilean SME. The problem that needs to be resolved is the lack of this kind of data within a Chilean fintech company called Dank. This data can be useful in developing an automatic risk evaluation model and, therefore, in reducing business process time, since risk evaluation is currently being carried out by people. The solution allows maintaining the anonymity of the data and using GAN to obtain different synthetic time series, increasing the data by 10%. It uses images from a vector of random numbers that are in temporal coherence and equal distribution. This research allows SMEs to obtain a greater amount of data, with a simple solution, to make better decisions.

Original languageEnglish
Title of host publicationComputational Science and Its Applications – ICCSA 2024 Workshops, Proceedings
EditorsOsvaldo Gervasi, Beniamino Murgante, Chiara Garau, David Taniar, Ana Maria A. C. Rocha, Maria Noelia Faginas Lago
PublisherSpringer Science and Business Media Deutschland GmbH
Pages56-70
Number of pages15
ISBN (Print)9783031652844
DOIs
Publication statusPublished - 2024
Event24th International Conference on Computational Science and Its Applications, ICCSA 2024 - Hanoi, Viet Nam
Duration: 1 Jul 20244 Jul 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14820 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference24th International Conference on Computational Science and Its Applications, ICCSA 2024
Country/TerritoryViet Nam
CityHanoi
Period1/07/244/07/24

Keywords

  • Fintech
  • GAN
  • Synthetic Data Generation
  • Times series

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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