Modelos preditivos de insolvências: uma revisão sistemática da literatura

Translated title of the contribution: Predictive models of insolvency: a systematic literature review

Mariana V.S. Ildefonso, Raul M.S. Laureano, Miklos A. Vasarhelyi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study aims to explore the importance of predicting financial distress, insolvency and bankruptcy for investors, creditors, banks and other stakeholders of companies due to the likelihood of corporate default. Since the 2008 financial crisis, it has been a priority for firms to find the best predictive model for forecasting possible weak conditions. This study presents a systematic review of work already done and increases the degree of knowledge through the use of advanced data analysis techniques and using financial and non-financial indicators.

Translated title of the contributionPredictive models of insolvency: a systematic literature review
Original languagePortuguese
Title of host publication2023 18th Iberian Conference on Information Systems and Technologies, CISTI 2023
PublisherIEEE Computer Society
ISBN (Electronic)9789893347928
DOIs
StatePublished - 2023
Externally publishedYes
Event18th Iberian Conference on Information Systems and Technologies, CISTI 2023 - Aveiro, Portugal
Duration: Jun 20 2023Jun 23 2023

Publication series

NameIberian Conference on Information Systems and Technologies, CISTI
Volume2023-June

Conference

Conference18th Iberian Conference on Information Systems and Technologies, CISTI 2023
Country/TerritoryPortugal
CityAveiro
Period6/20/236/23/23

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

Keywords

  • Data Mining
  • Insolvency
  • Machine Learning
  • Predictive Models

Fingerprint

Dive into the research topics of 'Predictive models of insolvency: a systematic literature review'. Together they form a unique fingerprint.

Cite this