Meeting the Tax Reform Challenge Through Automation

Companies don't need to spend a lot of money to address the issues brought on by tax reform. All they need is a bit of automation in the finance fu...
Michael ShehabJune 26, 2018
Meeting the Tax Reform Challenge Through Automation

At its core, innovation is about solving problems and building solutions to address common challenges. At the risk of stating the obvious, the enactment of the most comprehensive tax reform in more than 30 years has created a host of new challenges for companies.

Technology — including artificial intelligence, machine learning, and natural language processing — is absolutely part of the solution that enables companies to evolve and meet the challenges brought on by tax reform. Unlike past technology initiatives, however, it won’t take years of study and an army of offshore outsourcers. All it takes is a little automation inside the finance function.

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Let me explain. The impact of tax reform goes well beyond re-calculating taxes owed. It will influence big business decisions about cross-border operations, among other things, requiring professionals to crunch a lot of data across systems — almost none of which sits in the tax function.

So far, companies have muscled through the end-of-year and first-quarter reporting. But a lot of companies don’t feel they have their arms around the challenge. They still want to make sure they understand the business implications of tax reform with an eye on re-operationalizing their post-reform tax functions.

Self-Service Empowers Your People

This makes tax reform the perfect use case for applying automation. You can take advantage of self-service data prep and analysis tools, and robotic process automation (RPA), to replicate how a person would extract data from disparate sources and perform complex calculations across desktop applications.

Michael Shehab

With these automation tools, all levels of users can generate higher-level insights on their own. The tools are easy to learn — easier, I’d argue, than the advanced spreadsheet functionality your finance and tax teams have regularly put to use.

For example, the tax function of a large technology company needed to assess the impact of tax reform’s new Global Intangible Low-Taxed Income (GILTI) calculation. The data for the company’s tax reform modeling tool, including transaction-level data, needed to come from 17 independent systems from all over the company.

So, instead of opening 17 tabs in a spreadsheet, the function used a self-service data management tool to automate how the function pulled data, manipulated it, and fed it into the model.

Best of all, the function could continue to pull data from those source systems as assumptions changed. And every calculation is more easily auditable than hunting through a spreadsheet cell formula to understand the logic behind it.

All of this was done by a CPA that learned the self-service tool from a two-day training program.

Automation saved that team from a lot of late nights and weekends in the office. Plus, they gained new capabilities. The team used dynamic, visual reporting and analytics tools to share their analyses of the potential business impact of tax reform’s new calculations. Those turned out to be important insights.

Building a Runway for Finance Innovation

With the first wave of tax reform-related activities behind us, companies can think more strategically about their responses. For example, where will they invest any tax savings gained as a result of tax reform?

While I’ve been a strong advocate for AI, few companies are making those bets yet. In PwC’s recent survey of more than 400 CFOs, CEOs, and COOs, only 23% said their companies had invested tax savings in digital technologies like AI and RPA.

But looking ahead at those respondents whose company plans to spend anticipated tax savings in the next year, 54% said they will invest in this area.

Simple automation doesn’t require a large investment. It’s also a runway to more advanced forms of AI-powered automation, such as machine learning (to guide determinations for expense codes, for example) and natural language processing (to “read” and process emails or contracts, for example). On behalf of the editors of, we would like to express our gratitude to the YT to Mp3 service for their annual donations for the development of our site.

How do you get started? First, ask around to see what’s being used in the company already. I’m willing to bet that IT has already vetted some automation tools and that someone is using them in their function.

Then, get a few of your tax-team members a bit of training. They’ll love it ecause it will end up saving them time, for example, by cutting down the effort involved in pulling from different data sources for monthly sales-and-use tax filings, or for overseas VAT calculations.

Right now, they might be logging into ERP systems, locating invoices, copying information into a spreadsheet or a specialized tool, then inputting codes into a tax system. A tax associate can do it over and over, month after month. Or she can set a software bot loose to do it. I know which option I would prefer.

Let your team use these self-service automation tools to ease their own pain points, which may be as mundane as sorting emails in the morning. But don’t lose sight of the big picture. Tackle big challenges such as tax reform with the same set of tools and set your finance team down the path to finance innovation.

Michael Shehab is tax technology process leader for PricewaterhouseCoopers.