Finance
Recommendation System for the Banking Industry
⚡ Pain Points We Tackled
Bank managers struggled to analyze vast amounts of performance metrics across multiple departments (sales growth, transfers, ratios, etc.) and provide actionable recommendations to employees. Data variability and the sheer number of indicators made manual analysis inefficient and error-prone.
Our Approach
We developed a server-side API from scratch to calculate metrics and generate personalized recommendations for bank employees. The system uses Airflow to manage workflows via DAGs, ensuring accurate, scheduled processing of over 1,000 metrics and generation of 500+ recommendations.
Applied Methods and Practices
- Data Collection & Cleaning: Aggregating and preparing large volumes of employee and financial data for accurate analysis.
- Metrics Calculation & Scoring: Evaluating over 1000 metrics per department to measure performance against KPIs.
- Recommendation Ranking: Prioritizing suggestions using calculated performance indicators to ensure relevance.
- Workflow Orchestration with Airflow: Scheduling, monitoring, and managing tasks efficiently across departments.
- Visualization & Insights: Creating intuitive dashboards to highlight key performance areas and actionable insights.
Solution Features
- Automated Performance Analysis: System calculates and analyzes employee metrics across multiple departments.
- Personalized Recommendations: Tailored suggestions help employees improve specific areas of their performance.
- Scalable Workflow Management: Handles complex, cross-departmental processes without performance bottlenecks.
- Insightful Dashboards: Clear visualizations highlight problem areas and actionable insights for managers and employees.
