Preparing data for VAT4U import

In many cases, it's fast end efficient to export data from your existing Travel Expense Management software (TEM) or Account Payable system (e.g. ERPs like SAP, Oracle, Exact) and import this data to VAT4U

Depending on your data availability, weather you can extract data only, data and scans or only scans, VAT4U supports few data import scenarios:

👉 Data only

This type of import is suitable when you have only data that can be exported from your system (without the invoice scans). Invoice scans can be manually added one by one to the VAT4U platform later on from our Data Entry module.

👉 Data + Scans

This type of import is suitable when you have the possibility to export data and invoice scans from your system. VAT4U needs to understand how to match a invoice scan with the data you are importing. We offer two possibilities:

• URL approach (recommended): your data will have one field including the public URL of the invoice scan for each line. VAT4U will automatically access this URL and download the scan and attach it to the corresponding expense line. 
• Filename approach: your data must have one field including the name of each scan. Example: if the scan is named 123456.pdf, your data must have one field containing "123456". VAT4U will attach this scan to the corresponding expense line.
  It is possible to have only a partial match. Example: if the scan is named 123456_otherID.pdf and if your data must has one field containing "123456", VAT4U will attach this scan to the corresponding expense line.

👉 Scans only

When you have only Scans, and no structured data available, you can still use the benefit of mass data import. Uploading hundreds of documents at once, with predefined values will help you speed up the process of Data entry and data cleaning, providing you some benefits of OCR data recognition system.

Formatting your Data for VAT4U import

1. Your CSV should be semi-colon separated (;)
2. For higher efficiency provide some relevant information about expenses, categories, and vendors. The desired list of fields is attached at the end of this article.
3. Keep your date formats in well-know, standard formats, e.g. (22.08.2019, 2019/08/22, 22/08/19, etc). Full list attached at the end of this help article.
4. Country fields should contain either ISO country 2 letter code (e.g. DE, ES, NL, etc) or Country international name (Germany, Spain, Netherlands, etc)
5. Format your amount values (gross, net or vat) with simple decimal formating, without thousands separator (✅1234,55 or 1234.55  ❌1.234,55 or 1,234.55)
6. There are no requirements about minimal data, although we always suggest having at least these columns available:
   
   1. Expense date
   2. Expense category (spend category)
   3. Expense country of refund (Country where expense occurred)
   4. At least one expense value, either GROSS, NET, or VAT. Having one specified, VAT4U will calculate the other two values based on internal VAT rates.
7. When you prepare data from CSV + Scans import, the URL to scan/document should point directly to the document on your server. This will allow VAT4U system to fetch expense document during the import.
8. When uploading only scans/documents, VAT4U will accept ZIP archive with flat hierarchy, meaning you should grab all your files inside a single directory and directly zip them, without zipping multiple directories together.

List of default CSV fields

Expense date
Expense number
Expense description
Expense country of refund
Expense currency (3 letter currency code format)
Expense category
Vendor name
Vendor street name
Vendor street number
Vendor ZIP code
Vendor city
Vendor country
Vendor other (house number, etc)
Vendor VAT number
Gross expense amount
NET expesne amount
VAT expense amount

List of supported Date formats (d = day in 2 digits format, m = month in 2 digits format, y = year in 2 digits and Y = Year in 2 digits format). VAT4U will try to parse date from the list above, taking first format which fits the date value correctly.

d-m-y = 22-08-19
d-m-Y = 22-08-2019
d.m.y = 22.08.19
d.m.Y = 22.08.2019
d/m/y = 22/08/19
d/m/Y = 22/08/2019
Y-m-d = 2019-08-22
Y/m/d = 2019/08/22
Y.m.d = 2019.08.22