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TAXline

Rethinking taxation of work

Author: Steve Wade

Published: 01 Sep 2021

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There are multiple routes to automation for corporate tax compliance. Stephen de Vere White shares his experience

Internal direct tax functions are under ever-increasing pressure to do more with less – from contributing to professional fee budget reductions and enhancing control and governance, to acting as business partners – all in the context of changing legislation and enhanced reporting requirements.

While the use of tax engines for indirect tax might be commonplace, real-time corporate tax reporting and automation is less common. Likewise, similar activities – such as group reporting, statutory accounts notes and tax return finalisation – often only occur on an annual basis. For large groups with a broad legal entity footprint, these obligations frequently consume significant resources and time.

In the UK, Making Tax Digital for corporation tax is on the horizon, among other enhanced reporting requirements. This adds to a governance-driven ecosystem that already requires substantiated processes to meet senior accounting officer (SAO) obligations and to limit the risk of representatives criminally facilitating tax evasion – processes that cannot necessarily be subcontracted to advisers. HMRC, when undertaking business risk reviews, is interested in the business’s approach to technology and how it can drive insight and, in the end, accuracy.

During the course of the past year, the tax department at WeWork has been working on transforming its corporate tax functionality with the aim of strengthening risk and governance processes while finding synergies (particularly time synergies) in the tranches of activity just mentioned.

Transforming the direct tax reporting processes

The compilation, cleansing and manipulation of data is an often thankless task for the in-house tax professional, who historically has been beholden to inherited processes and #N/A-riddled spreadsheets.

While there is an undeniable time and resource investment involved, automation can relatively quickly facilitate a re-pivot of the in-house tax function away from time-intensive manual compliance processes and towards greater value-add and risk-prevention activity.

The path to automation is, in any case, recommended as a phased one, but the improvement on multiple fronts that can come about from small incremental changes is stark.

Vehicle for automation and evaluation

There are multiple routes to automation for corporate tax compliance. In some instances, it might be most appropriate to undertake tax sensitisation directly in the enterprise resource planning (ERP) software. In others, particularly where statutory accounting adjustments are not maintained in ERP, or where multiple data sources are relevant for tax return compilation, or (as in our case) where there is a large legal entity footprint, an external workflow tool might be more appropriate.

The workflow tool here acts as the bridge between raw incoming data and the tax return and/or tax provision software outputs.

The workflow tool option also provides an ability to make change quickly within the group tax function – no ERP configuration changes and no metadata changes that might require more drawn-out change management processes (at least in the first transformation iteration).

We chose to use Alteryx Designer – a data analytics tool that allows for ready data preparation, blending, reporting and predictive analytics to bring together source data for populating statutory accounts notes and corporate tax returns and reporting. However, there are numerous alternatives available from the likes of Microsoft (Power Automate) and others.

Our choice was based on ease of use and a clear and accessible training path, but also the prevalent use of the tool elsewhere in the finance organisation and therefore future synergies between sub-functions.

Insource vs outsource

The question of automation might also sit alongside the question of insourcing or outsourcing of tax compliance and reporting matters, and should be considered in tandem.

In evaluating an appropriate model, the ability to have control over SAO-related governance as well as the ability to develop automation capability to drive wide oversight (for example, in relation to managing risks related to the corporate criminal offence for failing to prevent criminal facilitation of tax evasion) drove the decision to bring a substantive part of our corporate tax compliance in-house. This approach also works for our organisation in the context of having a large legal entity footprint with significant repeatable effort, and where our systems and processes are evolving as we continue with the transformation of our business.

For other businesses, there may be occasions where it might be right to entirely outsource the automation or share the automation effort and reward in a co-source relationship with an adviser, depending on the return on investment.

Manual to integrated data feeds

Application programming interfaces (APIs) are commonplace in various data-driven scenarios. In the context of corporate tax automation at its simplest, APIs can allow for direct feeds of data from ERP (and other systems) to the workflow tool and onwards to the tax return/tax provision software, thereby enabling real-time tax reporting dependent on the sophistication of the tax logic sitting in the workflow tool.

The use of APIs does not necessarily mean a significant investment in development or programming expertise. Increasingly, these APIs sit within the wrapping of a ‘connector’ – an out-of-the-box means of facilitating that flow of data from ERP into the workflow tool and into tax reporting software. It was, in fact, the availability of such connectors that influenced some of our workflow tool and tax compliance and reporting decision making.

However, at the outset it is recommended that pre-existing reports and data sources are used and uploaded into the first phase of the workflow. This inherently aids the testing process in the transition from manual compilation and manual manipulation to automated manipulation and ultimately to integrated compilation and automated manipulation.

In both cases (i.e., with or without API connection), the benefit of using a workflow tool is that the source report is never amended with clear visualisation and audit trail as to precisely how the source data is manipulated and prepared.

Discrete data to machine learning

General ledger (GL) reporting and other inputs often include significant amounts of information that can help drive insight and tax logic (for example, free text memos and dimensions including cost centre vendor/customer, GL account, categorisation entries, etc).

It might be that a combination of GL account and journal category and/or cost centre drive basic level tax sensitivity analysis and the first phase of a corporate tax workflow. But as the workflow continues to be developed, machine learning is readily available in the likes of Alteryx.

Next steps

In our experiences to date, we have focused on tax compliance reporting, but in the next phase of our automation and transformation we will be looking at how our data analytics tool can support our transfer pricing efforts. The ability for the tool to simplify and accelerate cost allocation calculations and models is widely talked about.

Tax forecasting is also set to be a more painless exercise. We expect fewer true-ups through the front loading of calculations at the group provision stage of the compliance cycle, and we will apply tax logic to forecasting and planning data.

Tax doesn’t have to be taxing

The use of a data analytics tool might at first glance seem like a sledgehammer to crack a nut – or, indeed, the thought of upskilling might seem like a daunting task. However, neither of these assertions is true.

There are plenty of sources of training for data analytics tools so that upskilling can be an inexpensive and relatively rapid experience. The feedback from our team has been that the data analytics tools is more user friendly than a spreadsheet tool – not only because large volumes of data can be more efficiently managed, but because step-by-step preparation, transformation and analytics are clearly flowed and explainable.

flow diagram of the path of automation

About the author

Stephen de Vere White, EMEA Tax Director, WeWork