📅 2024-12-31 — Session: Developed Debt Tracking and Forecasting Systems
🕒 00:55–23:55
🏷️ Labels: Debt Tracking, Financial Management, OCR, Predictive Modeling, Data Analysis
📂 Project: Business
⭐ Priority: MEDIUM
Session Goal
The session aimed to develop a comprehensive debt tracking and forecasting system, leveraging various data processing and analysis techniques.
Key Activities
- Debt Tracking System Design: Outlined principles for a debt tracking system using Google Sheets and Pandas, focusing on data manipulation and live ledger setup.
- Debugging Techniques: Discussed debugging shortcuts in scripting for efficient development.
- Reverse Engineering Financial Models: Implemented methods to reverse engineer penalty rules from observed data, using Python for rate estimation and modeling.
- OCR Data Processing: Executed OCR processes to extract financial data from municipal debt statements, summarizing key details for Tigre Municipality and TASA reports.
- Debt Management Models: Developed a plan for a debt master calculator, including predictive modeling and anomaly detection.
Achievements
- Successfully outlined and initiated the design of a debt tracking system.
- Implemented OCR processing workflows to extract and summarize municipal financial data.
- Developed a structured plan for a debt master calculator, integrating predictive modeling and optimization strategies.
Pending Tasks
- Further refinement of the debt tracking system using Pandas and Google Sheets.
- Continued development of the debt master calculator, focusing on parameter optimization and anomaly detection.
- Additional data cleaning and model refinement sessions to enhance debt prediction accuracy.