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Embracing AI May Be Your Best Global Tax Strategy


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If we had to pick one word to describe the current global tax landscape, it would be “uncertain.” If we had the luxury of two words, we’d say, “extremely uncertain.” Why? Country-specific tax regulations make corporate tax compliance an exercise in jumping through a string of complex hoops with the goals of conforming to the rules of tax administrations and avoiding double-taxation.

Now couple that behemoth compliance challenge with the fact that the OECD is on the verge of rewriting our current global tax system, a doctrine that has been embedded in cross-border tax practices since the 1920s. The OECD’s Pillar One proposal stands to revolutionize tax allocation rules; if it passes, a portion of a multinational company’s residual profits would be taxed in the jurisdiction where customers are located, as opposed to where companies are headquartered as it stands now. Then there’s the organization’s Pillar Two proposal, a global minimum tax, that hopes to curtail the world’s “race to the bottom,” by dismantling countries’ abilities to entice corporate investment with low- or no-tax rates. Following the June meeting of the G7 finance ministers, under the framework of Pillar Two, negotiations are moving towards —the possibility that companies will pay a minimum global tax of 15% no matter where they do business, pending implementation of the deal into local domestic tax laws.

While there are still a lot of questions surrounding these proposals, including a clear definition of the companies subject to them, if they pass, one thing’s for sure: Everything will change. And if they don’t? Everything will change. Countries have already begun instilling unilateral digital services taxes—another country-specific move that complicates an already intricate landscape. France, Hungary, and the UK, for example, have already launched digital services taxes on revenue streams, not profits, and many countries are gearing up to follow suit.

Compounding these issues are the financial impacts of the COVID-19 pandemic, which has taken tax scrutiny to new heights, as tax administrations have had to offer economic support to help multinational companies recover from losses due to shutdowns, supply-chain breaks, and decreased demand in products and services. Tax authorities will need to recoup from relief payments and recover lost revenue themselves. No doubt, they’ll be looking at corporate tax dollars to help. Like we said: Uncertain.

Fortunately, we live in the Information Age, where technology is always at our fingertips. While many tax departments have been reluctant to embrace any streamlining that threatens the life of an Excel spreadsheet, the truth is technology may be the gateway to tax certainty—or as close as you can get to it. Artificial intelligence (AI) is part of our everyday lives—and anyone who has taken a recommendation from Netflix or set a timer on Alexa is probably already dependent on it. Some tax departments, however, are hesitant, still tackling mountains of data manually, which in today’s world, is analogous to continuing to plot your trip on a roadmap instead of relying on GPS.

Technology such as AI, machine learning, and robotic processing automation can help with filing accurate returns, finding specific information, tracking and updating country-specific requirements, and even predicting tax liabilities—or strategizing for specific outcomes. All of which put taxpayers in a better risk position and less prone to risk and adjustments during audits. Here’s just a few ways technology can help you do it.

  1. It keeps track of country-specific requirements. Whether it’s corporate income tax returns, transfer pricing documentation, qualifications for R&D tax incentives, or calculating an income tax provision, nearly every country has its own unique requirements. If you’re a multinational company doing business around the globe, it’s difficult to keep up with and meet country-by-country regulations. AI solves the problem entirely. Not only does software keep track of regulations around the world, but it has the ability to update them automatically—and alert you when there’s been a change or when you’ve omitted information that’s required. As more and more countries pass unilateral digital services taxes, a feature like this will be indispensable. Even better: When regulations change—or if new profit allocation rules come into play–some programs can even offer strategies to manage the specific tax implications for your company.
  2. It manages data in less time. Why spend hours and hours sifting through invoices and receipts by hand when document intelligence, powered by machine-learning algorithms and pattern recognition, can find needle-in-a-haystack tax information in seconds? Machine learning has the ability to identify useful information and then classify it into line items like VAT, sales, expense, taxable, or exempt. It also has the capability of pinpointing items that have been incorrectly booked by finance based on the tax team’s past classifications, so your records are accurate and consistent throughout documents—a key in reducing the burden of audits and avoiding adjustments.
  3. It reads your notices. Tax regulators and auditors send taxpayers notices all the time. Some are informational, while others are requests for additional information. Machine learning technology can review notices and flag only the ones that need your attention. Not only does that save you time, but it facilitates efforts to cooperate with tax authorities and auditors by turning around information in a timely way.
  4. Technology eliminates tax minutia. The field of corporate tax is riddled with numbers—account numbers, ID numbers, income, expenses, you name it. Robotic process automation (RPA) can automate the process of inputting and exporting these numbers, as well as other data, so you don’t have to enter and re-enter repeatedly. Software can take account numbers, industry information, company data and export it on to corresponding tax documents. It can also comb through trial balance accounts to identify new accounts, tax sensitive accounts, and data anomalies. RPA technology also reviews documents to ensure accuracy with prior years, reconcile book accounts to tax, calculate book- to-tax differences, calculate income tax provisions, and even help with audits by gathering the right information and responding to audit queries promptly, which is always smiled upon by tax authorities. RPA is used more and more for invoice payments, account reconciliation, and financial closeouts and reporting. It saves time, resources, and perhaps most importantly, it can maintain consistent information between finance and tax for the entire MNE group.
  5. It identifies deductions and credits. Can you deduct a percentage of your expenses? Do your R&D activities qualify for tax incentives? What about other tax credits—do you qualify? Can you take a credit and a deduction? AI can pore through the rules and identify where you qualify for what, maximize your savings, and produce accurate applications. It even stores applications and supporting documentation in a central cloud-based place, so that you have a good jumping-off point next year.
  6. It paves the way to better benchmarking. Transfer pricing is one of the most commonly scrutinized areas of tax today. Intercompany pricing on goods or services must align with the arm’s length principle, meaning at fair market value. How do you prove you’re operating at arm’s length? By benchmarking your transactions with third parties. Of course, anyone who’s ever done this knows it’s a laborious process that involves days and days of sifting through databases that weren’t built with transfer pricing in mind. The solution? AI-driven software evaluates comparable companies through a transfer pricing lens and comes up with a reliable set of comparable companies in seconds. That cuts off days of work—and if you’re paying a consultant by the hour, it saves considerable money, too. With a manual process, transfer pricing benchmarks are often subjective–part of the reason they’re often questioned (or rejected) by tax authorities, weakening a multinational company’s tax position. AI cuts out all the subjectivity and benchmarks companies by function, so you always have apples-to-apples comparisons. And since technology is up on country-specific rules, it also finds comparable companies in local or regional jurisdictions as mandated by individual tax authorities. Indisputable comparables in the right jurisdictions strengthens your arm’s length position and therefore, your tax position, too.
  7. Technology strategizes your tax planning: Want to free up more cash? Buy equipment to increase depreciation and drive tax deductions? Accelerate expenses to offset income? AI can help. Tax software can analyze regulations, performance data, and your particular corporate strategy and generate tax recommendations for your business, all the while keeping you in compliance.
  8. It predicts future tax liabilities: In such an uncertain tax environment, wouldn’t it be great to have a crystal ball? Well, soon you’ll have the next-best thing: Technology that can predict the outcomes of tax disputes. That’s right, AI will have the capability to review court cases and analyze outcomes, so you can weigh how your company would fair in a likely legal scenario. Software will be able to add or eliminate different variables, so you can mimic your own situation and assess your risk position—and your comfort with it—based on likely results.

While AI-powered software programs learn and eventually think like humans, they won’t replace them. Tax professionals will always be needed to assess the data and make strategic decisions—and they’ll be freed up from being bogged down by tax minutia to do it. It’s never too late to streamline the tax function and make it a value-add part of your company by embracing AI and implementing advanced technology.

Donald Scherer is the Founder and Chief Executive Officer of CrossBorder Solutions.





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