Bank Export Automation Tool (CSV to Lexware)
STACK USED
- Python | Flask
- HTML/CSS | Javascript
Project Overview
This Flask-based CSV (Bank Export) Processor streamlines the transformation of exported bank transaction files into a structured accounting-ready format. The app applies custom financial classification logic to parse, categorize, and enhance transaction data—automatically generating seven additional columns, including SKR04 codes, counter-accounts, and period metadata. It produces a cleaned, enriched CSV file nearly ready for direct import into Lexware, effectively replacing manual spreadsheet work. Built with Python, Pandas, and Flask, the tool has eliminated hundreds of hours of repetitive accounting labor.
Key Features
Custom Accounting Logic
Automatically classifies transactions based on patterns in IBAN, name, and usage reference fields.
Assigns SKR04 codes, calculates periods, and derives Gegenkonto and Buchungszwecke values per custom logic.
Flask-Powered Web Interface
Allows secure uploading of one or multiple CSV files through a browser interface.
Processes and packages cleaned outputs as downloadable ZIP archives.
Pandas for Data Transformation
Utilizes Pandas for high-speed processing, numeric transformation, and error handling.
Supports delimiter normalization, type casting, and regional number formatting (German-style decimal parsing).
Challenges Solved
Manual Data Entry in Lexware
Replaced tedious, error-prone manual entry of accounting data with a scriptable, repeatable processing engine that aligns directly with Lexware's import format.
Classification by Pattern Recognition
Built flexible logic to categorize transactions based on keywords and IBAN metadata using nested conditionals and fallback heuristics.
Multi-File Upload with Streamed Output
Enabled users to batch-upload CSV exports and receive a zipped archive of processed results—handling large volumes seamlessly via in-memory streams.
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