HOW DATA ANALYTICS CAN IMPROVE VAT PROCESSING

Data

Data analytics is not a new concept but in the indirect tax function it is still relatively embryonic. Uptake is now growing as organisations seek to become leaner and reduce risk, with regulatory requirements from HMRC (such as MTD) further driving adoption.

Data analytics can aid tax teams in several ways. Errors in source data, for example, can be flagged more quickly with their origins identified in ‘real-time’. Businesses can then measure improvements in errors, over allocated periods, and calculate how much time and risk they are saving.

Why is data analytics important to Indirect Tax teams?

To start with, we know that VAT is processed differently from most other taxes; an issue that has created many idiosyncratic challenges for indirect tax teams. VAT data requires the analysis of every sales and purchase transaction and this requires additional manual assessment, making for a laborious, monotonous and error-prone process.

In the UK, the indirect tax return process is not always part of an audit. It could be years after a return has been filed that companies discover any errors; after which time it could be too late. At the time of writing, Brexit and COVID are the major geo-economical challenges facing UK businesses but the challenges won’t end there, of course.

In short, there are always times of external uncertainty when businesses will need greater internal certainty in every area possible. VAT is an area that has long been calling out for greater control and accuracy. Those who are slow or reactive to VAT transformation won’t see the same benefits as those who are proactive. For many, MTD has been the catalyst needed to foster these changes and invest in areas such as data analytics. Our survey in Accountancy Age revealed that around a third are using MTD to encourage technological advance across the business.

Improving error prevention and control

Indirect tax teams in large businesses need to process data high volumes of transaction data which must be pulled from multiple disparate data sources/ERPs, all in different formats. Tax teams have historically tried to bridge the gap by relying on spreadsheets, however, over 65% of those we surveyed said they had concerns over the integrity of formulae in spreadsheets which increase the propensity for error.

For example, the tax codes held in ERP systems may need to be changed/corrected and this presents a real problem when dealing with high volumes. On the AP side, this is largely a manual process but for large businesses such changes are often made in shared service centres. The room for error is significant when you consider that many shared service centres are KPI driven.

However, it’s worth noting that there are ERPs such as SAP and Oracle with VAT ‘logic’ built into them that automatically determine the VAT code on the AR side. Tax teams are then able to add-in controls to ensure consistency so that these codes cannot be overridden manually.

Clearly there’s a middle ground here where data analytics can help. For example, there could be a case where up to 5% of purchase invoices from domestic suppliers had no assigned tax code, resulting in VAT that was then not recovered. Applying data analytics here would enable the business to detect where and how VAT had been missed.

Non-tax insights

Data analytics can also help tax teams deliver insights to other areas of the business, elevating their contribution to the business. With the right software tax teams can utilise smart tax dashboards with standard and bespoke VAT analytics that can be of use to the wider finance team. As an example, analytics can “optimise supply chain from a tax perspective in order to eliminate refund claims in jurisdictions where refunds are difficult/ailing”, according to KPMG, because it can be used to flag and identify trends in number of duplicate invoices, number of invoices without a PO, number of early payments to suppliers etc.

Cash flow forecasting

For many businesses, cash flow forecasting is increasingly more important when facing uncertain economic challenges such as COVID-19 and Brexit.

Data analytics can help tax teams test not only transactional data against VAT/legal requirements, but also assess transactional data for risk areas (e.g. focusing on underpayment of output VAT, claiming too much input VAT), opportunity areas (e.g., focusing on overpayment of output VAT, input VAT recovery, input VAT accruals) and VAT working capital benefits.

Below we can see some specific areas, identified by KPMG, where VAT data analytics can have a huge benefit:

 

Source: KPMG

As data analytics becomes more sophisticated, tax teams should harness it to help them realise specific goals and objectives to monitor and control their VAT. Data analytics will likely become a cornerstone of many tax teams’ skill sets and enhance their position within the organisation; those that ignore it risk becoming less competitive. See Top Three Challenges for Tax Team post Covid-19.

As technology and automation helps rid tax teams of the manual burdens they face, the time this releases can now be more profitably applied to help drive business decisions. Data analytics is instrumental in enabling companies to project and plan ie using future liabilities and so this combination of anomaly and error detection combined with future forecasting is liable to see if become an indispensable tool in the indirect tax team armoury.

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