The Power of Numerical Indicators in Predicting Bankruptcy: A Systematic Review

Dimitrios Billios, Dimitra Seretidou () and Antonios Stavropoulos
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Dimitrios Billios: Department of Applied Informatics, University of Macedonia, Egnatia 156, 546 36 Thessaloniki, Greece
Dimitra Seretidou: Department of Applied Informatics, University of Macedonia, Egnatia 156, 546 36 Thessaloniki, Greece
Antonios Stavropoulos: Department of Applied Informatics, University of Macedonia, Egnatia 156, 546 36 Thessaloniki, Greece

JRFM, 2024, vol. 17, issue 10, 1-12

Abstract: This paper systematically reviews the behavior of numerical indicators in predicting future bankruptcy of companies through statistical analysis models. Following the PRISMA standard, ten primary studies were included in the review. The obtained results underline (1) the ability of numerical indicators, through simple statistical analysis models, to forecast the bankruptcy of businesses and companies and (2) the reliability of cash flows in predicting financial distress through statistical analysis, and (3) models are built with indicators from a specific economy; it is impossible to consider them stable and unchanging, as changes in a country’s economic conditions can potentially impact their predictive accuracy.

Keywords: bankruptcy; early warning; failure prediction; financial distress; prediction; numerical indicators; statistical analysis; PRISMA (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2024
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