diff --git a/ynab-karianne.py b/ynab-karianne.py
new file mode 100644
index 0000000..12a1abe
--- /dev/null
+++ b/ynab-karianne.py
@@ -0,0 +1,235 @@
+#!/usr/bin/env python3
+"""
+Bank Statement to YNAB Converter
+Converts bank statements from various formats to YNAB-compatible CSV files
+"""
+
+import os
+import sys
+import glob
+import pandas as pd
+from pathlib import Path
+
+def parse_norwegian_number(value):
+    """Convert Norwegian number format (comma decimal) to float"""
+    if pd.isna(value) or value == '':
+        return 0.0
+    # Convert to string and replace comma with dot
+    str_value = str(value).replace(',', '.')
+    try:
+        return float(str_value)
+    except ValueError:
+        return 0.0
+
+def parse_norwegian_date(date_str):
+    """Convert DD.MM.YYYY format to YYYY-MM-DD"""
+    if pd.isna(date_str) or date_str == '':
+        return ''
+    try:
+        # Parse DD.MM.YYYY and convert to YYYY-MM-DD
+        date_obj = pd.to_datetime(date_str, format='%d.%m.%Y')
+        return date_obj.strftime('%Y-%m-%d')
+    except (ValueError, TypeError):
+        return str(date_str)  # Return original if parsing fails 
+
+def parse_bank_sparebank1(data):
+    """
+    Parse Sparebank 1 bank data
+    Expected columns: Dato, Beskrivelse, Rentedato, Inn, Ut, Til konto, Fra konto
+    """
+    result = []
+    
+    for _, row in data.iterrows():
+        inflow = parse_norwegian_number(row.get('Inn'))
+        outflow = parse_norwegian_number(row.get('Ut'))
+        
+        # Convert outflow to positive if negative
+        if outflow < 0:
+            outflow = -outflow
+            
+        result.append({
+            'Date': parse_norwegian_date(row.get('Dato', '')),
+            'Payee': row.get('Til konto', ''),
+            'Memo': row.get('Beskrivelse', ''),
+            'Outflow': outflow,
+            'Inflow': inflow
+        })
+    
+    return pd.DataFrame(result)
+
+
+def parse_bank_norwegian(data):
+    """
+    Parse Norwegian bank data
+    Expected columns: TransactionDate, Text, Memo, Amount
+    """
+    result = []
+    
+    for _, row in data.iterrows():
+        amount = row.get('Amount', 0)
+        inflow = amount if amount > 0 else 0
+        outflow = -amount if amount < 0 else 0  # Make outflow positive
+        
+        result.append({
+            'Date': row.get('TransactionDate', ''),
+            'Payee': row.get('Text', ''),
+            'Memo': row.get('Memo', ''),
+            'Outflow': outflow,
+            'Inflow': inflow
+        })
+    
+    return pd.DataFrame(result)
+
+
+# Dictionary of banks, filename patterns, and parsing functions
+BANKS = {
+    "Sparebank1": {
+        "patterns": ["OversiktKonti*.csv"],
+        "parse_function": parse_bank_sparebank1,
+        "delimiter": ";"
+    },
+    "Norwegian": {
+        "patterns": ["BankNorwegian*.xlsx", "Statement*.xlsx"], 
+        "parse_function": parse_bank_norwegian
+    }
+    # Add more banks and patterns as needed
+}
+
+
+def process_bank_statement(file_path, parse_function, delimiter):
+    """
+    Process a single bank statement file
+    
+    Args:
+        file_path (str): Path to the bank statement file
+        parse_function (callable): Function to parse the specific bank format
+        delimiter (Optional<str>): Field delimiter
+    
+    Returns:
+        pd.DataFrame: Processed YNAB-compatible data
+    """
+    file_extension = Path(file_path).suffix.lower()
+    
+    try:
+        # Handle CSV files
+        if file_extension == ".csv":
+            data = pd.read_csv(file_path, delimiter=delimiter)
+        # Handle Excel files
+        elif file_extension in [".xlsx", ".xls"]:
+            data = pd.read_excel(file_path)
+        else:
+            print(f"Skipping unsupported file type: {file_path}")
+            return pd.DataFrame()
+        
+        # Call the appropriate bank-specific parsing function
+        ynab_data = parse_function(data)
+        return ynab_data
+        
+    except Exception as e:
+        print(f"Error processing file {file_path}: {e}")
+        raise e
+        return pd.DataFrame()
+
+
+def find_bank_config(filename):
+    """
+    Find the appropriate bank configuration for a given filename
+    
+    Args:
+        filename (str): Name of the file to match
+    
+    Returns:
+        tuple: (bank_name, bank_config) or (None, None) if no match
+    """
+    import fnmatch
+    
+    for bank_name, bank_config in BANKS.items():
+        for pattern in bank_config["patterns"]:
+            if fnmatch.fnmatch(filename, pattern):
+                return bank_name, bank_config
+    
+    return None, None
+
+
+def convert_bank_statements_to_ynab(input_files=None):
+    """
+    Convert bank statements to YNAB format
+    
+    Args:
+        input_files (list): Optional list of specific files to process
+                           If None, processes all files in current directory
+    """
+    current_directory = Path.cwd()
+    output_directory = current_directory / "YNAB_Outputs"
+    
+    # Create output directory if it doesn't exist
+    output_directory.mkdir(exist_ok=True)
+    
+    # Get list of files to process
+    if input_files:
+        print(f"Processing {len(input_files)} dragged file(s)...")
+        files_to_process = [Path(f) for f in input_files if Path(f).exists()]
+    else:
+        print("Processing all files in current directory...")
+        files_to_process = []
+        # Collect all files matching any bank pattern
+        for bank_config in BANKS.values():
+            for pattern in bank_config["patterns"]:
+                matching_files = glob.glob(str(current_directory / pattern))
+                files_to_process.extend([Path(f) for f in matching_files])
+    
+    files_processed = False
+    
+    # Process each file
+    for file_path in files_to_process:
+        if not file_path.exists():
+            print(f"File not found: {file_path}")
+            continue
+            
+        # Find matching bank configuration
+        bank_name, bank_config = find_bank_config(file_path.name)
+        
+        if not bank_config:
+            print(f"No bank configuration found for file: {file_path.name}")
+            continue
+            
+        print(f"Processing file: {file_path} for {bank_name}")
+        
+        parse_function = bank_config["parse_function"]
+        delimiter = bank_config.get("delimiter", ",")
+        
+        # Process the file
+        ynab_data = process_bank_statement(str(file_path), parse_function, delimiter)
+        
+        if ynab_data.empty:
+            print(f"No data processed for {file_path}")
+            continue
+        
+        # Define output file with "ynab-" prefix
+        output_filename = f"ynab-{file_path.name}"
+        if not output_filename.endswith('.csv'):
+            output_filename = Path(output_filename).stem + '.csv'
+        
+        output_file = output_directory / output_filename
+        
+        # Export to CSV for YNAB import
+        ynab_data.to_csv(output_file, index=False)
+        print(f"Data saved to {output_file}")
+        files_processed = True
+    
+    if not files_processed:
+        print("No files were processed. Make sure your files match the expected patterns.")
+
+
+if __name__ == "__main__":
+    # Check if files were dragged onto the script
+    if len(sys.argv) > 1:
+        # Files were dragged - process them
+        files = sys.argv[1:]
+        convert_bank_statements_to_ynab(files)
+    else:
+        # No files dragged - run normal directory processing
+        convert_bank_statements_to_ynab()
+    
+    # Keep window open on Mac so user can see results
+    input("\nPress Enter to close...")
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