A Predictive System for detection of Bankruptcy using Machine Learning techniques
This work addresses bankruptcy prediction for financial stakeholders, but it appears incremental as it applies existing soft computing techniques without claiming major innovations.
The study developed a bankruptcy prediction system using machine learning to categorize companies by risk level, aiming to serve as a decision support tool for early detection to prevent financial losses.
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