Company Bankruptcy Prediction

Keywords: company, bankruptcy

Background

it is very important in any financial sector to analyze the data and identify the chances of going bankrupt. Artificial Neural Networks (ANN) are widely used in the financial industry for various purposes and predicting bankruptcy is one of the important aspects to consider which will be very useful in decision-making and establishing new policies for the company. The challenge in this project is studying huge datasets with various financial aspects and understanding the important facts that will help in forecasting bankruptcy accurately. The problem of this project is to develop an accurate bankruptcy prediction model with the help of ANN to enable the management and the stakeholders to assess the financial status of the company and to make decisions. The solution to predict bankruptcy is to train the ANN model with features like ROA, sales margin, cash flow rate, net profit, and others. The model can differentiate between bankrupt and non-bankrupt companies. The developed model can make the management in making decisions that will enable the viability of the companies.

Aim & Objectives

Aim
To Predict the bankruptcy of company using DL Techniques
Objective
Create a deep learning model for predicting company bankruptcy. Train model with financial data to classify bankruptcy risk. Assess model accuracy to provide reliable bankruptcy predictions using DL techniques.

Research Methodology

ANN Technique used

Software & Tools

Jupyter, Google Collab

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