AI, increasingly the weapon of choice against tax crime, offers rich opportunities for companies to manage their tax liabilities and demands transformation in how companies manage their tax data.
Artificial Intelligence (AI) is beginning to transform how businesses deal with taxation. National tax authorities are already using robotics and AI to analyse the income taxes of individuals. They are determined to bring similar rigour to company taxation.
In the first nine months of 2019, the French tax authorities collected an extra €640 million in personal tax thanks to AI. Web-crawlers scanned personal accounts and social media for signs of fraudulent under-reporting. The project, still in its infancy, detected €335 million in business tax fraud in 2018. France's scale of ambition for AI is huge and is shared by tax authorities around the world, as they work together to counter evasion. In Britain, HMRC has been rolling out its 'Making Tax Digital' programme for VAT. Despite early growing pains, HMRC aims to extend it to the collection of most forms of tax.
AI will allow tax authorities to monitor compliance in real time. They are already analysing online trading, asset leasing, payments to subcontractors and VAT invoices. The implications for detecting potential fraud are clear. AI will find clues hidden in the data that humans might miss. Banks, under pressures of huge fines, have had to become early adopters of AI to manage sanctions and compliance risk.
Turning threat into opportunity
If enforcement is driving the pace of AI in company taxation, it is equally true that AI brings companies themselves a world of opportunity. As they understand their taxation issues more clearly, they will see strategic opportunities they might otherwise miss. Preparing for this new world demands transformation in how companies manage their tax data.
Company tax departments are in the eye of the storm. They are constantly challenged to get compliance right, minimise the risks, and stay ahead of the ever-changing (and not always aligned) demands of state regulators. Not to speak of how they can reduce tax liabilities. They must live in the present, focusing on reducing tax liabilities while getting ready for how AI will change their professional roles. It's a big ask, and a dramatic culture change which will bring data management into sharp focus.
Emine Constantin, TMF Group's Global Head of Accounting & Tax, observes:
"The finance professionals of the near future will have developed IT skills and be able to relate them to a company's technology capacity and its adequacy for meeting evolving tax requirements. Increasingly, they must be capable of operating at board level to influence operational and trading policies and decisions over tax."
AI's rapid evolution
The perception of Artificial Intelligence has shifted over time. John McCarthy, one of AI's pioneers, has ruefully remarked: "As soon as it works, no one calls it AI anymore." While advanced refuse collection was once seen as the cutting edge of AI, the term's practical meaning is ever changing. In the past, AI was understood as robotic applications carrying out highly automated tasks. Now, it is increasingly understood as Machine Learning, the science of teaching computers to progressively improve their performance of particular tasks.
This means solving complex problems using large quantities of data. AI mimics human intelligence in certain ways but can crunch through massive quantities of data in ways well beyond human capacity. On its own, it builds algorithms that lead it to the right way to perform a task. By repetition, it learns to minimise its mistakes.
Unprecedented power of analysis
Much of the routine work of tax professionals can already be done by technical tools – and to better effect. Its sheer analytic scale means that AI can detect underlying patterns that a human might miss. AI tools learn on the job; initial errors are corrected, and results become ever more refined and reliable. AI eradicates bookkeeping errors. As AI capacity builds, companies will develop instantly accessible archives of their tax practices. The potential for powerful predictive analysis is clear.
Understand your data to manage it better
To make best use of AI, businesses will need to bear down on their data strategies; to make certain that they collect the data they will need to report; to collect (or 'curate') data with more precision; and to understand what they need it for. Much of the data will exist already. The question is more one of data clarity.
This means compatible standards in the way it is gathered – eliminating the possibilities for mismatched data – so that raw numbers can be easily reconciled. As Emine Constantin warns:
"A disjointed landscape – international and multi-jurisdictional – where data sits on different systems, containing a growing volume of data, is a liability."
If data is well managed, it will give companies powerful insights into how they managed their taxes in the past and how they can do better in future. For organisations that operate internationally, it will be much easier to identify similar tax practices. Painfully slow manual searches of databases will be a thing of the past.
For tax professionals this will bring a new awareness of the processes behind tax and coding and interpreting data. If they embrace the emerging technologies, they can transform their importance, moving beyond a close focus on numbers to a more strategic role in company strategy.
The key thing is this: the better the data is understood, the more powerful will be its impact.
The first steps are necessarily slow. Training machines to a high level of accuracy is difficult. Specialists with the skills and the time to do it are thin on the ground. Understandably, tax professionals and their clients are still wary of the results. Clients tend to feel more assured if a real human being has sorted out their problem. Tax professionals fear they might be out of a job or see their professional status decline. They shouldn't worry. Tax professionals will still add value – perhaps even more value – and AI will not lessen the need for the human touch.
South America leading the way
However, taxation is still in the early stages of its AI revolution. There is a striking lack of 'digital maturity', an essential threshold for AI between jurisdictions. As TMF Group's Accounting and Tax Report for 2019 observes, it is compulsory to submit tax invoices electronically in only 28% of jurisdictions in the EMEA countries. In the APAC countries, it is compulsory in 46% of jurisdictions. Strikingly, it is the Americas that have made most progress with 67%. Argentina and Brazil have led the way. Brazil's tax authorities audit tax transactions, both personal and corporate, remotely and issue fines remotely.
A major driver of change is reducing tax evasion. South Africa is a recent case in point. However, the United States is a laggard in deploying AI in tax collection, perhaps because of a lack of political will.
Blockchain is another feature of the changing landscape. It records transactions in real time, providing a fraud-proof record on a public digital ledger which can neither be changed nor deleted. Advocates see it as the new frontier in countering tax evasion. Unsurprisingly, HMRC and other tax authorities are fastening on to blockchain.
The present gap between the time when companies close their accounts and when they report to the tax authorities will disappear. Emine Constantin notes:
"once you input a transaction in the system, you will pretty much need to report it to the tax authorities immediately."
Setting a strategy
Strategy and execution are key. TMF Group can help clients get a grip on their sources of information. Emine Constantin underscores the need for high quality data to respond to the demands of the tax authorities. "
"We can assess the quality, assess the gaps, and identify what needs to be done to have the right input into the tax process."
And TMF Group, with its global reach, can help with local compliance, particularly where companies are not already up to speed with their accounting software.
In the near term, AI tax solutions will become dramatically more effective, taking account of tax laws across jurisdictions and the policies of the organisations using it. Deeper layers of guidance will enable companies to cope with tax problems of greater complexity. And this potential will feed through to the bottom line.
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