A Predictive System for detection of Bankruptcy using Machine Learning techniques

TL;DR

This paper presents a machine learning-based predictive system designed to assess bankruptcy risk in companies, serving as a decision support tool to prevent financial losses.

Contribution

It introduces a novel bankruptcy prediction system utilizing soft computing techniques to categorize companies by risk level.

Findings

Effective classification of companies based on bankruptcy risk

Potential to reduce financial losses through early detection

Enhances decision-making in financial risk management

Abstract

Bankruptcy is a legal procedure that claims a person or organization as a debtor. It is essential to ascertain the risk of bankruptcy at initial stages to prevent financial losses. In this perspective, different soft computing techniques can be employed to ascertain bankruptcy. This study proposes a bankruptcy prediction system to categorize the companies based on extent of risk. The prediction system acts as a decision support tool for detection of bankruptcy Keywords: Bankruptcy, soft computing, decision support tool