A Tax Control Framework for VAT focuses on managing material risk areas. An objective of the data analysis could include determination of the controls’ effectiveness and efficiency with regard to these risk areas.
In practice, I have noticed the following in reviewing data analysis regarding indirect tax:
- The Tax Control Framework of the organization contains 10 controls that can be assessed by means of data analysis.
- Of these controls, 3 were assessed using data analysis and 7 were not included in the assessment.
- Out of the 12 tests that were executed, 7 contributed too little for drawing conclusions regarding either the effectiveness of Tax Control Framework or the quality of the VAT data.
The root cause lies in the fact that many data analysis applications are offered in standardized form in the market, which means that the data analysis is not fine-tuned for the organization respectively the industry.
In the above-described situation identical tests were executed for Accounts Payable and Accounts Receivable, even though the processes and risks differ significantly. Because identical tests were run for both AP and AR, this resulted in many false-positives. There was no tightening of the tests based on specific conditions of this organization whatsoever.
One of the control measures that was not included in the data analysis was determination of the reconciliation of the VAT return with the General Ledger and the Accounts Payable and Receivable reports.
This is remarkable since lack of reconciliation eliminates any proper ground for drawing conclusions. A commonly heard remark is “the current ERP systems always ensure reconciliation”. In practice, however, making the VAT return depends heavily on data extractions from the system and many operations in Excel – a manual and error-prone process.
In the normative framework of VAT processes and work instructions for composing the VAT reports and returns, it is indicated which data are to be used for the VAT return and whether additional actions are required. Data analysis enables determination as to whether this is actually carried out.
|Process||VAT Risk||Control Activity||Test of Control|
|Compilation of VAT reports: reconciliation||VAT reports are inaccurate or incomplete||The VAT department has work instructions detailing the creation of the VAT reports. A checklist is available detailing all data required for completion of the VAT return. The VAT reports are reconciled to the General Ledger by the (VAT/Finance) department. Any differences are explained and followed-up.||Verify that work instructions for completion of VAT reports have been followed and signed off. Apply data analysis to assess reconciliation between VAT reports and GL|
Execution of an effective data analysis requires objectives that are clearly defined in advance.
Examples of objectives are:
- Contributions to the realization of fiscal objectives
- Managing material risk areas concerning indirect tax
- Realizing savings respectively optimizing the cash flow position
- Compliance with laws and regulations (including financial statements)
- Ascertaining that the organization has control over material VAT risk areas and that the TCF is working effectively.
- Showing the tax authorities that the organization is in control, in order that a tax audit can be prevented.
- Defining actions for improvement based on the observed inconsistencies.
- ‘process’ and ‘root cause’ analysis
- more efficient and effective controls (manual and automated)
When the objectives are defined, the right approach regarding data analysis is as follows:
- starting point is reconciliation of the VAT returns with the GL and AP and AR reports
- gaining insight into specific VAT risk areas of the organization respectively the industry, such as:
- intercompany transactions
- cross-border transactions
- transactions within fiscal unity
- foreign VAT (included in incorrect VAT return)
- clearly defining the applications of the data analysis on the basis of these objectives.
Tel: +31 6 8379 0414