Article2020

MACHINE LEARNING IN BANKRUPTCY PREDICTION – A REVIEW

15 citations0/0 files storedDOAJ (DOAJ: Directory of Open Access Journals)

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Financial Distress and Bankruptcy Prediction Corporate Insolvency and Governance Forecasting Techniques and Applications

Abstract

There is an increasing interest in machine learning for bankruptcy prediction with more and more researchers contributing to the literature. Although there is a considerable amount of research, the domain does not seem to be aligned and there is still a lot of indecisiveness in terms of what is the best method to be used and on which data. Using Web of Science, Scopus and ScienceDirect databases, a systematic review of 32 texts published between 2016 and 2020 was conducted. This review shows a summary of those papers based on 9 criteria. The criteria identified include source of data, number and type of variables, models used, industry type, and timeline of dataset, sample size, aim and result as well as accuracy of the best performing model used. Overall, it has found that no model performs best on any type of data and that the domain is still away from having a conclusion about what works best and where. This paper contributes towards updating academics and practitioners with the current state of the domain, tools used for bankruptcy prediction lately and their performance.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 15 citations exist upstream.

References

1997A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting 2001Forecasting Bankruptcy More Accurately: A Simple Hazard Model 1873Lombard Street: A Description of the Money Market 2006Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review 1970A Theory of Economic History 200535 years of studies on business failure: an overview of the classic statistical methodologies and their related problems 2010A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems 2019Machine Learning in Banking Risk Management: A Literature Review

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.