Corporate income taxpayers are being hit by two waves of change. One is a growing demand from tax authorities, as well as the general public, for transparency in tax liabilities. The other is a group of digital technologies that are improving so exponentially that they have people scrambling to figure out where they fit in.  

The interesting thing about these disruptive waves is that one of them may offer solutions to the other. Exponential technologies allow us to do more work than ever before. As such, they can help tax functions address the increasing compliance burden and mitigate the risk of being seen as a bad corporate citizen. IT professionals can play a pivotal role in helping their tax and financial colleagues understand and use these exponential technologies.

How exponentials work

To get an idea of the direction this is taking tax, let’s look at three exponential technologies: big data platforms, robotic process automation, and cognitive computing.

Big data involves the use of highly scalable, automated platforms to access, combine, process, and analyze large volumes of disparate data. The data can be structured or unstructured. What this means for tax professionals is that they can use more data from multiple sources to make better informed tax judgments. That greatly expands and speeds access to data that can help inform tax-related decisions, improve tax compliance, and increase transparency into tax-related financial reporting. 

Robotic process automation (RPA) refers to software routines or agents that do the work of humans. RPA is conceptually similar to a macro, except it can work across applications rather than within just one. For tax, RPA could automate recurring, highly manual processes, share data across applications, and notify tax professionals of completed tasks, substantially speeding those processes and, in the process, freeing up tax professionals to perform other value-added activities such as providing a tax perspective on decision-making in other areas of the organization.

Cognitive computing technologies can communicate, learn, and reason like a human. The term cognitive computing also encompasses systems that understand natural language learned by example and exercise judgment based on experience. So for tax, it may “remember” previous tax treatments and use that experience to logically predict conclusions based upon a body of past decisions. As with RPA, these technologies can automate and accelerate tasks previously performed by humans while enabling tax professionals to focus on other work that technology cannot perform.

Collectively, these technologies promise to relieve tax professionals of some fairly humdrum labor. For instance, exponentials might analyze vast quantities of legislation, case law, and other tax authorities for relevant changes. Or, they could automatically call out misclassifications of tax-relevant costs and extract tax-sensitive data from contracts so they can be correctly classified for tax purposes.

Also, exponentials might tackle any repetitive task that has a tax component, such as invoice scanning and processing. They could single out disallowable expenditures for corporate income tax purposes. Another use would be to offer additional hints to users who search tax technical databases.

What makes exponentials different from traditional productivity tools is that the efficiency gains can be ongoing and cumulative, as machine intelligence turns up new instances where its own application might further augment and amplify human effort. Hence, “exponential” improvements in productivity and, potentially, cost savings over time are enabled. Exponential technologies also can enhance human problem-solving capabilities. That is because machine intelligence progressively refines the scope and accuracy of search results, resulting in data that lends itself to sophisticated data analytics.

Ways to prepare

Applications can be particularly complicated when it comes to tax. Whatever systems are implemented must work with a slew of existing applications. For example, tax departments typically deal with workflow technologies, local country tax engines, and tax-specific software for provision and compliance. Tax is also affected by consolidation and planning systems, not to mention ERP migrations to the cloud.

Under these circumstances, the pragmatic approach is to pick the right components and put them together in a tax technology architecture. A well-planned architecture should include source business systems, reporting and return processing software, and tax data management solutions. Workflow, status alerts, document storage, data analysis, and reporting can come together via a tax dashboard. Rigorous data management should underpin all.

Along with the architecture, IT leaders should consider a roadmap for delivery. The roadmap will include a plan to put the solution in place, with agreed budgets, timelines, and specific responsibilities for implementation. It is also a good idea to lay out specific objectives for the most promising new technologies.

These new technologies are worth the upfront planning. Innovation entails taking risks, but not embracing innovation in today’s climate can be the bigger risk. Companies that wait too long could be sidelined by competitors that use technology to become more viable and relevant to the marketplace. In the case of tax, exponentials can reduce manual effort, improve visibility, and bring more control. They can also boost tax analysis and help tax professionals answer oft-encountered questions. Ultimately, the goal is to help tax professionals focus on what they do best: give knowledgeable, fact-driven advice in the context of the speed of business.

Beth Mueller is a tax partner Deloitte Tax LLP focusing on federal and international tax issues for fast-growth companies. She leads Deloitte’s US Tax Analytics practice, helping clients combine tax technical knowledge with transformative technology tools. Beth has significant experience with global acquisitions and dispositions, tax-efficient restructurings, and management of tax function activities. Previously, she led Deloitte’s US Inbound tax practice.