Corporate finance and tax professionals can be forgiven for letting their eyes glaze over when conversation turns to cloud-based technology. Call it cloud fatigue, the result of seeing an endless succession of conference tracks and news articles about how cloud-based technologies will improve efficiency, streamline workflows, and reduce equipment costs.
It’s all true, of course: cloud-based technologies are less-expensive over the long haul and much less cumbersome to maintain than their locally installed counterparts, but it’s still kind of hard to get too excited about being more efficient.
Now, however, as ever-larger numbers of multinational corporations have adopted cloud-based tech for everything from sales-lead management to enterprise-wide tax management, some of the sexier applications of the cloud are starting to emerge from the operational abyss. Chief among them: the power to tap into transaction data to power larger predictive analytics and corporate intelligence initiatives that are making us not only more efficient, but also a lot smarter.
Here’s how it works. Until recently, the vast repository of transaction data in any large corporation was housed deep within the indirect tax function of the company’s enterprise resource planning (ERP) platform. It existed in a silo with the express purpose of accurately capturing sales tax, per-unit tax, and value-added tax (VAT) in each jurisdiction in which the company operates. This information was used by the corporate tax team to ensure that taxes were being applied accurately to all sales made around the world, based on a constantly-evolving rubric of jurisdictional tax laws.
When you consider the scale of today’s multinational businesses, most of which are doing business in hundreds of different tax jurisdictions around the globe, that’s no small feat. In fact, for anyone old enough to remember what it was like to track that kind of information manually and reconcile the books based on columns in a spreadsheet, the idea that we can now automate this process on a global scale is definitely life-altering technological innovation.
Still, the story of tax technology automation has been largely about efficiency, accuracy, and improved workflows. Now, as the evolution of tax tech has bumped up against the world of big data housed in cloud-based servers, the potential to unlock even more intelligence from tax is just beginning to emerge.
With the latest tax technology, global transactional data is updated continually to ensure compliance with tax jurisdictions around the world, and these real-time updates can specifically define geographical information systems. Through address validation and cleansing, tax technology provides significantly increased accuracy when it comes to calculating indirect tax. It also provides complete jurisdictional coverage, so it’s not only data on state, county, and city authority taxes but also related information, such as hyper-local district tax data, including police, transportation, mall, cultural, and scientific taxing authorities.
And through integration with existing ERP systems, this data can be used to make consistent, repeatable, and scalable tax determinations, calculations, and even post-tax collections and accruals automatically to the general ledger.
This kind of information also has the power to make tax departments much smarter. For example, this month, India’s Upper House approved a landmark goods and services tax, which will, if passed by the Lower House, replace all existing sales, VAT, and luxury taxes in the country with a single tax to be levied anytime a consumer buys a good or a service. Designed as a simplification to the current system of taxation in India, the implementation has the power to wreak havoc on the tax systems of any multinational doing business in India.
In preparation for a change like this, a multinational tax department would typically spend months testing and preparing for the change, constructing manual models to try to predict how the change would affect its accounting function and the underlying business operations in India. Today, that data can be modeled instantly, factoring inputs from other regions that have gone through similar transitions and detailed, line-by-line analyses of historical transaction data to clearly illustrate the impact this change will have throughout the tax structure.
This shifts the focus of the tax department from tedious, time-consuming work to strategic analysis and decision support — a radical (and welcome) change for multinational tax professionals.
And it’s just the beginning. Today, we’re seeing some of the most progressive tax professionals tap the cloud to model the impact of tax legislation on their bottom lines. Tomorrow, they will be creating predictive analytics engines that will function more like Siri or Amazon’s Echo than any tax software we’ve ever seen before. Want to know the impact of a presidential candidate’s tax proposal on retail sales in the Northeast during peak back-to-school shopping season? Just ask the natural language processing tax engine.
We are not far from this type of capability being a reality. The key is to not let our eyes glaze over with what we believe to be the status quo in new technology, but to keep looking beyond the plateaus to what’s possible when we exploit the true power of great ideas.
Brian Peccarelli is president of Thomson Reuters Tax & Accounting.