RFP Grid Classifier
Business Opportunity
The business opportunity for the RFP Grid Classifier lies in automating decision-making processes to identify credentialing status for different types of organizations. Currently, manual efforts are required to determine which entities need to be credentialed, leading to longer review times and potential errors due to varying rules and exceptions across different lines of business and geographical locations.
Link to Canvas Dashboard: RFP Grid Classifier
Solution / Approach
The solution involves the development of a CatBoost model to predict whether credentialing should be "yes" or "no" for different organization types. The model has demonstrated a high performance level of around 98% accuracy in identifying the credentialing status. Decision tree rules have also been incorporated to enhance the decision-making process.
The model is integrated into a Flask application, where it takes input data from Excel files, predicts the credentialing status based on the CatBoost model and decision tree rules, and sends the results as JSON responses.
Architecture
Key Metrics
- Model Accuracy: Monitor the accuracy of the CatBoost model in predicting the credentialing status for different organization types, ensuring the solution's effectiveness in automating decision-making processes.
- Decision Tree Rules Performance: Evaluate the effectiveness of decision tree rules in enhancing the decision-making process alongside the CatBoost model, contributing to the overall success of the solution.
- Data Processing Efficiency: Measure the efficiency of processing Excel data within the Flask application to predict credentialing status, reflecting the system's ability to handle input data quickly and accurately.
- Response Time: Track the response time of the system in predicting and sending credentialing status as JSON responses, providing insights into the solution's speed and user experience.
- Scalability: Assess the scalability of the solution to handle increasing volumes of data and maintain high performance levels, ensuring that the system can accommodate future growth and evolving requirements.
Tech Stack
- Python
- Cat Boost Model
- Flask
Resources Links
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