Written by Richard Cornelisse and Robbert Hoogeveen


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Learn from yesterday, live for today, hope for tomorrow. The important thing is not to stop questioning.

Tax Authorities, due to technological innovations, have become increasingly better in executing their tax audit. The probability that the Tax Authorities will issue additional assessments and penalties in the near future because errors in indirect tax are detected, increases by the day. Tax authorities collect and analyze already indirect tax data (e.g. SAF-T for VAT). The focus is not only about timely and accurate VAT reporting but as well whether on high risk areas an effective tax control framework is in place. Tax risk management methods are assessed.


What is needed for best in class data analysis for VAT?


Generate more insights from data VAT decisions are more and more shifting from employees who make entries in the system manually to ultimately the ERP system based on implementation of conditions tables/defaults. Data analysis can be a way of testing whether these VAT decisions are logical.


Replace emotion and second-guessingThe results of the data analysis can provide insight into the existing compliance risks or opportunities with respect to the remittance of too much or too little VAT. 

In making VAT decisions, companies are entirely dependent on the underlying ERP system of the employees who manually process data in the system. 

Data analysis can be used to check whether these decisions are legitimate. Such analyses can comprise all transactions in a specific period – year, quarter or month.


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Data analytics can contribute to improving business performance:

  • Cost reduction: by identifying potential cost savings and limiting expenses (for instance by tracing VAT that was erroneously not deducted)
  • Risk analysis: tracing incorrect VAT determination or reporting incorrect returns
  • Compliance: by identifying possibilities to improve the quality and efficiency of internal control

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Indirect Tax Risk Management definitief Richard4


Business challenge


Data analyses of various market players are generally standard analyses that are generated by a data dump from SAP. Extracting data from a SAP environment is often not possible due to lack of the proper authorization.  Moreover, the extraction of data is limited to a specific number of document numbers per extraction.This requires the same extraction to be executed over 30 times when an extensive amount of data is to be retrieved. 

Retrieving data in multiple steps brings the risk of the format of the data not always being identical. As a result, there are no unequivocal results available and many manual adjustments are necessary. In the case of extensive data, SAP often breaks off the analysis, because run time limits are exceeded. In addition, due to restriction of the size of reports in SAP, created data files cannot always be copied to a pc.

Solely standard analyses are possible, which does not sufficiently take into account the complexity of business models and specific risk domains.


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Best practice data analytics


The risk domains should be salient. Knowledge for enabling fully automated VAT determination and building an integrated Tax Control Framework is crucial in data selection. Besides that it is important that only VAT relevant data is retrieved that is necessary for this analysis.

Better output in less time Providers of data analysis use for example third party software tools, so the data can be extracted from SAP in a uniform manner (data warehouses / centralized data hubs). For example, aggregate transactional data across ERP systems in use and connect automatically with as outcome that the blueprint of the company can be shown real-time.

With this, problems regarding performance, format of reports and interpretation of data could belong to the past and guarantees the quality and integrity of data.


Analyze source data and provide trend analysis


 

Quality and integrity of data

 

Profile analysis of the most important data fields in order to ascertain whether these comply with the applicable business regulations.

 

Identify the root cause of the problem regarding data quality and implement improvements.

 

Develop and implement improved data governance and quality assurance. Add new attributes to existing data so uniform and risk-oriented analysis becomes possible.

 

Combine information from different ERP sources and analyse this in conjunction.


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 'Turn data into information and information into insight'


Quantitative insights and visibility This enables foreseeing future risks long before they manifest themselves. Use data-based insights for decision making. By linking your business strategy to advance analytical possibilities, decision-making capabilities can be improved. A business change can be simulated via 'what if' with realtime data and its impact can be quantified (data-based insights).

Beyond indirect tax this should improve processes for management of e.g. transfer pricing, for logistics and warehouse locations management, cash flow planning, etc.


Enhance your performance to make smarter, faster decisions


  • Many stakeholders can benefit from this functionality; it is accessible real-time and it should improve both internal and external effective communication because you can ‘talk numbers’. It will contribute to buy-in from other departments and ease the writing of problem statements.
  • In addition, it will support business cases with the aim to realize sponsorship for change and better management of the Executives own KPIs as real numbers have actually been used.

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Benchmarking yourself against your peers



Foster continuous control and improvement


Continuous controls monitoring is an emerging governance, risk and compliance technology that monitors controls in ERP and other financial applications to improve financial governance, monitor and verify access and transactional rules, and automate audit processes.

CCM contributes value to risk management and compliance initiatives in three ways:

  • Lowering compliance costs — a CCM solution can reduce the cost of audits by eliminating much manual sampling and minimizing the time it takes to gather documentation.
  • Improving financial governance — CCM can increase the reliability of transactional controls, improve auditor trust and increase the effectiveness of anti-fraud controls.
  • Improving operational performance — CCM controls, such as those that monitor duplicate payments, incorrect discounts or misapplied warranties, go beyond what most people consider compliance. By preventing these violations of business rules, CCM can improve key financial processes and increase the availability of working capital. 

From: Magic Quadrant for Continuous Controls Monitoring by French Caldwell, Paul E. Proctor


Written by Richard Cornelisse and Robbert Hoogeveen


Phenix Consulting - our services - team - network



Fast adoption of technology
Add-on for SAP offers high-quality data for tax managers and
lowers work pressure for the IT department


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All VAT relevant transactional data of legal entities operating on the same SAP platform could immediately be made visible and accessible, as this information is stored separately in one table in SAP. That means real-time insight - without facing run-time issues - into the company’s blue print without the need of performing a manual transaction mapping exercise first.


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