Problem

As a financial institution, we were facing the challenge of predicting bankruptcy for our clients. We had to manually analyze their financial statements and credit reports, which was time-consuming and prone to errors. Additionally, we needed to identify the key factors that contributed to bankruptcy so that we could provide better guidance to our clients.

To address this problem, we decided to develop an automated solution that could accurately predict bankruptcy and provide insights into the contributing factors.

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Solution

We developed a machine learning model that analyzed various financial ratios and other indicators to predict the likelihood of bankruptcy. The model was trained on historical data from bankrupt and non-bankrupt companies, allowing it to identify patterns and make accurate predictions.

In addition to predicting bankruptcy, our solution also provided insights into the key factors contributing to bankruptcy. This allowed us to provide more targeted guidance to our clients and help them avoid potential financial difficulties.

Impact

Reduced manual analysis time by X%
Increased accuracy of bankruptcy predictions by X%
Provided valuable insights into contributing factors for bankruptcy

Quote of how incredible of an impact this had.

Team

Team Member #1 - Data Scientist
- Built and trained the machine learning model
- Optimized the model for accuracy and speed
Team Member #2 - Financial Analyst
- Provided financial expertise and guidance throughout the project
- Analyzed the insights provided by the solution to provide targeted guidance to clients

Automated Bankruptcy Prediction and Insights