All Technologies Used
Motivation
The goal was to automate the analysis of incoming data from various financial indicators and use this information to build tailored recommendations for banking employees to improve their performance. The system needed to handle large datasets and provide accurate insights and actionable recommendations.
Main Challenges
The banking system had hundreds of thousands of users and diverse metrics. The main challenge was ensuring that the system could analyze such vast amounts of data accurately and provide meaningful recommendations while considering varying performance criteria across departments.
With over 1000 financial metrics, it was difficult to ensure the recommendations were precise and aligned with each department's specific needs. Maintaining accuracy in the calculation and analysis of these diverse metrics was a key challenge.
Key Features
- Metric Calculation and Analysis: The system calculates over 1000 metrics related to employee performance and financial indicators to produce actionable insights.
- Recommendation Engine: Tailored recommendations are generated based on the analysis of these metrics, helping employees improve performance in specific areas.
- Airflow-based Workflow Management: Airflow is used to schedule, monitor, and manage the system’s tasks, ensuring the entire workflow is efficient and scalable.
- Personalized Employee Recommendations: Recommendations are personalized for each employee, based on their performance and specific department needs, helping them improve productivity and job satisfaction.
Our Approach
Project Impact
The automated recommendation system now helps bank employees identify areas for improvement by providing them with tailored, data-driven insights.
The system has enhanced operational efficiency, enabling managers to make more informed decisions and optimize performance across departments.