296 lines
5.1 KiB
Markdown
296 lines
5.1 KiB
Markdown
# <div align="center">ABANCA – Banking Statement Analysis & Automation Platform</div>
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---
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## <div align="center">Overview</div>
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ABANCA is a Python-based financial automation and banking statement analysis platform developed to process, classify and visualize banking transaction data automatically.
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The project focuses on automating financial workflows through:
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- Excel data processing
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- Banking transaction normalization
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- Financial classification
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- KPI generation
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- Automated reporting
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- Data visualization
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The notebook combines data science techniques with financial process automation to simplify banking reconciliation and financial monitoring operations. :contentReference[oaicite:0]{index=0}
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---
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# <div align="center">Main Features</div>
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## Banking Statement Processing
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- Import banking statement files
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- Automatic data normalization
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- Transaction categorization
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- Financial movement processing
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- Date formatting automation
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---
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## Financial Classification
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The system automatically classifies:
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- Debit transactions
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- Credit transactions
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- Banking movements
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- Financial operations
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- Account balances
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---
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## Data Cleaning & Transformation
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- Null value handling
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- Currency normalization
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- Column standardization
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- Duplicate detection
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- Invalid entry filtering
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---
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## Financial Reporting
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- Summary generation
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- KPI calculations
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- Transaction statistics
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- Balance analysis
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- Aggregated reporting
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---
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# <div align="center">Technologies Used</div>
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| Technology | Purpose |
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| Python | Main programming language |
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| Pandas | Financial data processing |
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| NumPy | Numerical operations |
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| Matplotlib | Data visualization |
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| OpenPyXL | Excel compatibility |
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| Jupyter Notebook | Interactive development environment |
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---
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# <div align="center">Project Structure</div>
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```txt
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.
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├── ABANCA.ipynb
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├── Input_Files/
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├── Output_Reports/
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├── Charts/
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└── README.md
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```
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---
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# <div align="center">Requirements</div>
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## Python Version
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```txt
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Python 3.10+
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```
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---
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# <div align="center">Required Libraries</div>
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Install dependencies:
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```bash
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pip install pandas numpy matplotlib openpyxl
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```
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---
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# <div align="center">Running the Application</div>
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Launch Jupyter Notebook:
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```bash
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jupyter notebook
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```
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Open:
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```txt
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ABANCA.ipynb
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```
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Execute all notebook cells sequentially.
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---
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# <div align="center">Supported Input Formats</div>
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| Format | Description |
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| `.xlsx` | Excel banking statements |
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| `.csv` | Transaction exports |
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| `.xls` | Legacy Excel statements |
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---
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# <div align="center">Main Functionalities</div>
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## Transaction Analysis
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The system processes:
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- Transaction dates
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- Descriptions
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- References
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- Debit values
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- Credit values
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- Running balances
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---
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## Financial Aggregation
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The notebook automatically generates:
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- Daily summaries
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- Monthly summaries
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- Account movement analysis
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- Transaction frequency statistics
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- Financial totals
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---
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## Data Visualization
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The project supports:
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- Financial charts
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- Transaction trend analysis
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- KPI dashboards
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- Summary visualizations
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---
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# <div align="center">Workflow</div>
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```txt
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Bank Statement Import
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↓
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Data Cleaning
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↓
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Normalization
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↓
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Transaction Classification
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↓
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Financial Aggregation
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↓
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KPI Calculation
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↓
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Report Generation
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↓
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Visualization
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```
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---
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# <div align="center">Generated Output</div>
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The system can generate:
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- Cleaned Excel files
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- Financial summaries
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- Transaction reports
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- KPI analysis
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- Graphical dashboards
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---
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# <div align="center">Data Processing Capabilities</div>
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## Cleaning Operations
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- Empty row removal
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- Date parsing
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- Numeric conversion
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- Currency formatting
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- Invalid record filtering
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---
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## Analysis Operations
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- Movement counting
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- Total debit calculation
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- Total credit calculation
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- Net balance computation
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- Financial trend analysis
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---
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# <div align="center">Intended Use Cases</div>
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- Banking reconciliation
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- Treasury analysis
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- Financial auditing
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- Banking statement normalization
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- Financial KPI reporting
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- Accounting support
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- Financial automation workflows
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---
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# <div align="center">Notebook Features</div>
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The notebook environment allows:
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- Interactive analysis
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- Dynamic filtering
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- Incremental execution
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- Rapid financial experimentation
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- Visualization customization
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---
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# <div align="center">Future Improvements</div>
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- PDF report export
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- Power BI integration
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- Database integration
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- Real-time banking synchronization
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- AI-assisted financial anomaly detection
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- Automated reconciliation engine
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- Web dashboard interface
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---
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# <div align="center">Security Notes</div>
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This project may process sensitive financial data.
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Users should:
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- Protect banking files
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- Avoid sharing sensitive exports
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- Secure generated reports
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- Validate all processed outputs before operational usage
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---
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# <div align="center">Disclaimer</div>
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This project was developed for financial automation and analytical purposes.
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Users remain responsible for validating all financial calculations and generated reports before official or accounting usage.
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---
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# <div align="center">Author</div>
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José Garcia
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Data Scientist
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Process Digitalization & Automation
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