The Changing Landscape of Indirect Tax
Guidance on emerging challenges in state and local indirect tax in the wake of COVID-19

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The indirect tax landscape has changed rapidly in response to the COVID-19 pandemic. If the Supreme Court’s decision in South Dakota v. Wayfair in 2018 created a new playing field, complete with new marketplace facilitator guidance, the global pandemic has moved the goalposts. In this demanding environment, what is the best way for tax professionals to move forward?

More than ever, tax departments are expected to provide greater value to the business. Meeting the challenges of indirect tax post-Wayfair and overcoming uncertainty in the COVID-19 era both require a healthy relationship with technology, with companies learning to take proactive approaches instead of reactive ones and transforming information into insight.

The right technology strategy and processes can help companies navigate the intricacies of tax, allowing not only more efficient compliance with tax obligations but also the ability to identify potential opportunities. Such a transformation calls for a change of mindset—from “What do I need to do?” to “What do I need to know?”

The Future of Work Is Here

A shift in the workplace paradigm in recent years—to a more remote model—has brought on new challenges for companies looking to comply with ever-changing tax rules and seeking ways to generate cash savings on their historic purchases as well as additional savings down the road.

What’s more, the ongoing shift of world economies into “the fourth industrial revolution” or “Industry 4.0,” with a combination of physical assets and advanced digital technologies such as the internet of things (IoT), artificial intelligence (AI), robots, drones, autonomous vehicles, 3D printing, cloud computing, nanotechnology, and more,1 has created challenges that were perhaps inconceivable twenty years ago.

According to Deloitte’s 2021 Return to Workplaces Survey, as of April 2021 sixty-seven percent of workers remain fully remote, with sixty-eight percent of respondents indicating that their company will implement some hybrid model in the future.2 As the data suggests, many companies are redesigning what the new normal will look like, and that new normal will likely be redesigned around better flexibility and a focus on workers’ well-being.

Companies today grapple with myriad indirect tax challenges, including sales and use tax, gross receipts tax, excise tax, property tax, the taxation of digital goods, issues emerging around the remote workforce, and the remote seller and marketplace facilitator laws. Modern challenges need modern solutions.

Paving the Road Ahead

Given that rules differ from state to state, companies must evaluate their filing and collection responsibilities on a state-by-state basis. Companies that have a good handle on their nexus footprint and their compliance may benefit from taking a step back, reviewing their current processes, and determining whether technology may help automate their processes through data-wrangling, data analytics, machine learning, and artificial intelligence (AI). Alternatively, depending on the industry or how things are used differently in a remote world, there could be opportunities for refunds of sales and use tax paid on purchases over the past three to four years, or even longer if a taxpayer is under audit.

Workers in the new remote workplace need digital assets to do their jobs, bringing the multiple-point-of-use (MPU) question to the forefront and complicating nexus definitions for multistate enterprises.

For example, a company may buy a software-as-a-service (SaaS) cloud-based subscription in New York, Illinois, Texas, Ohio, or another state that classifies and taxes such a purchase as software for sales and use tax purposes. In a remote environment, if the employees are located outside the company’s home state and therefore use the software outside that state, there may be an opportunity to reassign the cost of the software to where employees are using it, thus allowing the software cost to be allocated to lower-tax jurisdictions or jurisdictions where software is exempt or excluded from tax.

Performing an MPU study, which evaluates where software or SaaS is being used, is critical for calculating sales and use tax liability accurately and potentially generating sales and use tax refunds.

Selecting the Right Strategy

Companies should consider focusing on sales and use tax overall. Sales and use tax refund reviews may uncover opportunities for cash savings, and the findings from those refund reviews can improve ongoing compliance and ensure that overpayments of sales and use tax do not continue. Companies may also find ways to leverage technology to understand their position throughout the entire indirect tax life cycle.

Whether a tax department prepares forty returns per month or 400, indirect tax compliance can consume much of a company’s limited indirect tax resources—time that could be focused on other value-added tasks, such as refund and exposure reviews, audit defense, exemption certificate compliance, taxability research, general ledger account reconciliations, and fixing issues in sales tax calculation software.

Indirect tax compliance is often a time-consuming and tedious process, encompassing consolidating and validating multiple data sources, manually preparing returns, populating reports to aid in general ledger account reconciliation, and handling jurisdictional notices.

Robots to the Rescue

Data-wrangling workflows and robotic process automation (RPA) can help companies gain efficiencies throughout the indirect tax life cycle by automating the extraction and reconciliation of indirect tax data. Data visualization and dashboards can enable the sharing of key insights. These efficiencies, which can be applied to sourcing, nexus, classification, taxability, compliance, audit defense, and reverse audits, can drive more seamless execution of a company’s indirect tax function. They can also provide useful insights into other indirect tax efficiencies that could be realized.

Given that indirect tax is an increasing focus post-Wayfair, and so data-intensive, companies may consider the whole indirect tax life cycle, including sourcing, nexus, classification, and tax liability determinations, and how to best leverage technology for visualizations and dashboards to better show where sales and use tax and other transaction taxes are being paid. Understanding how much is paid, to whom, at what rate(s), and into what jurisdictions is critical.

AI Transforms Indirect Tax Recovery

Implementing processes with automation, RPA, smart optical character recognition (OCR) engines, and other technologies can help companies better understand their indirect tax footprint. Use tax is relatively visible because it is reported on the company’s sales and use tax return, but sales tax is not as visible, since it is paid directly to vendors.

In the current economy, companies are seeking ways to generate cash. Evolving technologies make it easier for companies to dig through large volumes of data to identify opportunities—including opportunities that have arisen in response to COVID-19 and the remote workforce.

The sheer number of indirect tax transactions combined with the complexity of state-specific variations in tax law makes it challenging for large companies and their tax professionals to ensure they have identified all of their potential US sales and use tax over- and underpayments. Many tax managers have historically performed this task manually, using sampling techniques and relying on their own knowledge of their general ledger accounts and vendors. This process has depended highly on tax professionals’ ability to correctly recall, interpret, and apply thousands of widely varying US sales tax regulations, defining taxability according to the nature of the purchased item or service and its intended use. The result has been often inefficient and time consuming, with failures to address the full population of spend, incorrect classification of transactions as taxable or nontaxable, and inadequate attention paid to potentially material over- or underpayment of sales and use tax.

Generating deeper insights from large volumes of data helps business leaders identify potential issues and seize opportunities. Business leaders often employ advanced AI and analytics tools and engage with indirect tax service providers who leverage technologies such as Deloitte’s CognitiveTax Insight™ (CogTax™) that can aggregate and draw conclusions from multiple data sources to address specific challenges that individual tax departments face. Compared to older sampled approaches, such technologies can help companies to gain a better and more efficient analysis of their indirect tax data set and to analyze all of their accounts payable transactions.

Work Smarter—Not Harder

AI technologies such as CogTax™ use a mix of supervised and unsupervised learning, augmented with natural language processing, to develop a company-specific and company-approved algorithm to analyze a company’s accounts payable transactions automatically, reducing human error and increasing the number of transactions subject to review. Furthermore, as tax rules change, these technologies can learn through a human-supervised learning process, allowing the technologies to reach higher levels of accuracy and scale.

Combining AI technologies with sales and use tax recovery reviews can save tax departments time and resources spent on analyzing indirect tax over- and underpayments. In addition to delivering a purely backward-looking analysis of potential tax over- or underpayments, AI technologies may provide additional insight and information to allow companies to adjust sales tax calculations to mitigate tax over- or underpayments faster.

The First Step Is a Look Back

Moving forward requires taking a step back and looking at all areas of the indirect tax life cycle: master data setup; indirect tax calculation; tax computation and posting; and preparing, populating, and submitting tax returns. From there, companies can determine areas of immediate exposure or potential opportunity.

Analytics can provide hindsight into historical tax positions and insight into current obligations. In advanced forms, analytics can provide foresight into “what-if” changes in tax conditions and liability. It can even identify potential risk areas.

Tax data analytics combines tax technical knowledge and advanced information technologies with large sets of master data and transactional data to identify patterns and anomalies. Leading to deeper insights and greater understanding, tax data analytics can provide an array of benefits, from uncovering errors and improving cash flow to prioritizing indirect tax focus areas.

For a typical large multistate business, transactional data sitting behind the tax determinations being evaluated can easily run into the millions. For example, an analytics dashboard that brings together structured and unstructured data can reveal trends in spending over time by vendor, cost center, general ledger account, and more.

When reviewing tax determinations with the underlying transactional data, combining an AI technology that has visual analytics dashboard capabilities, error rates and the potential drivers behind tax over- or underpayments can be made visible, allowing companies to quickly analyze the data and conduct root cause analyses to determine the underlying reasons for tax over- or underpayments and address them in detail. For example, dashboarding and analytics can help companies identify, through a vendor tax spend trend, when a vendor who is typically exempt has started charging tax due to the recent Wayfair case. When necessary, companies can promptly issue an exemption certificate to correct future overpayments instead of waiting three or four years to identify and pursue tax recovery.

AI Transforms Indirect Tax

AI solutions can potentially predict the future taxability of transactions using machine-learning algorithms. Unsupervised learning methods, which may include sampling transactions most representative of the entire dataset, require even less manual input from the tax specialist yet are more accurate. These lessons learned may be applied backward and forward so that past (and potentially future) tax determinations can be reevaluated. This may allow for more accurate tax determinations involving large volumes of transactions even as a company’s business offerings or purchases are highly differentiated and where standard machine learning may have difficulty accommodating such nuances and reaching correct tax determinations.

For example, companies that use AI may more accurately analyze taxability of spending across different industry segments for a single company (such as information technology, manufacturing equipment, and research and development simultaneously) while improving the solution’s AI with respect to each distinct area and associated data. Such advanced learning is essential to a company’s ability to streamline analysis of its sales and use tax position.

Beyond merely determining whether a transaction is taxable or nontaxable, AI solutions can quantify potential over- and underpayment of tax. Many solutions incorporate a tax table, enabling the application to calculate a company’s potential refund and overpayment exposure before it files a refund claim. This feature also has helps companies identify potential risks before an audit.

Go Beyond

Once tax departments have identified one or two indirect tax top priorities, they should explore ways to leverage technology to navigate the entire indirect tax life cycle. The ability to connect human insights with advanced, cutting-edge technology helps companies realize the potential of infinite possibilities and make them a reality. The right technology strategy and processes will be instrumental for companies to respond, recover, and thrive in this challenging time. These strategies and processes include but are not limited to:

  • globally integrated tax platforms, which may automate manual engagement tasks, integrate and centralize tools, and leverage technology to create an intuitive digital experience;
  • data-wrangling tools, with a dedicated team of specialists;
  • data quality and return quality checks to facilitate processing;
  • technology-enabled return preparation that enhances efficiency and quality;
  • data analytics dashboards, which provide visual representations using heat maps and tax trend analysis to assist with obtaining deeper insights into data;
  • assistance with automated monthly compliance data extraction processes; and
  • tools and solutions that use machine learning, AI, and smart OCR to help companies gain
    a broader understanding of their indirect
    tax footprint.

Identifying how Wayfair, remote work, and evolving sales and use tax sourcing, classification, and taxability guidance—not to mention the related compliance issues—have changed the landscape of indirect tax can be challenging. A strong understanding of these evolving standards is crucial. But beyond that understanding, data-wrangling, robotic process automation, machine learning, artificial intelligence, smart optical character recognition, and other technologies are key to efficiently managing the entire indirect tax life cycle.


Kirsten Gulotta, Brian Little, Deval Reddy, and Dave Yaros are tax partners and principals, and Kim Rausch is a senior manager, all with Deloitte Tax LLP in the United States. All are members of Deloitte’s US indirect tax practice.


Editor’s note: This article contains general information only, and Deloitte is not, by means of this article, rendering accounting, business, financial, investment, legal, tax, or other professional advice or services. This article is not a substitute for such professional advice or services, nor should it be used as a basis for any decision or action that may affect your business. Before making any decision or taking any action that may affect your business, you should consult a qualified professional advisor. Deloitte shall not be responsible for any loss sustained by any person who relies on this article.

Copyright © 2021 Deloitte Development LLC. All rights reserved.

As used in this document, “Deloitte” means Deloitte Tax LLP, a subsidiary of Deloitte LLP. Please see www.deloitte.com/us/about for a detailed description of our legal structure. Certain services may not be available to attest clients under the rules and regulations of public accounting.

Endnotes

  1. Deloitte, “The Fourth Industrial Revolution, at the Intersection of Readiness and Responsibility,” 2020, accessed September 10, 2021, www2.deloitte.com/content/dam/Deloitte/de/Documents/human-capital/Deloitte_Review_26_Fourth_Industrial_Revolution.pdf.
  2. Deloitte, “2021 Return to Workplaces Survey: Executives Weigh In on Their Return-to-Workplace Plans,” accessed September 10, 2021, www2.deloitte.com/us/en/pages/human-capital/articles/2021-return-to-workplace-survey.html.

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