Digitalization: Accelerating the Future of Tax
Digitalization: Accelerating the Future of Tax
- June 21, 2021
- Posted by: Dadjadmin
- Category: Blog
At times, it takes less to get more. Digitalization is one such boon to any industry, and tax is neither an exception. Evolving technologies drive a shift in the traditional operating models of taxation, leading to an accelerated digital transformation across the existing processes and approaches. Of all departments, tax has always been the most data-intensive and complex.
As data and complexity increase, the tax leaders are left with fewer resources to handle these enormous amounts of work, which consecutively affects the quality and time limit. Adapting to digital technologies can help tax leaders automate a major chunk of the tax functions in a faster, flexible, and affordable way.
The path towards a digital transformation
Businesses intend to transform digitally when they identify their existing technologies to be outdated. With the increase in demand and technological advancements, we expect the tax departments to do more with the aid of the digital realm. As a result, tax professionals coming from a traditional tax function model have to adopt the new system to live up to these expectations.
Firms that combine technological abilities with tax knowledge successfully will stand a better chance of succeeding in their journey towards an ideal digital transformation. But, of course, this optimized tax professional does not have to be an expert in all of those functions and technologies. A new digital tax department will emerge as a result of this new pool of skills.
Administrations in charge of taxes
Globally, tax administrations have already begun adapting to digitalization-driven processes and demonstrating efficiency.
The Covid-19 pandemic has demonstrated that remote tax audits are the most efficient way of approach. Accordingly, tax authorities are altering existing auditing processes by making them more digital to gain optimum operational control during such crises. Tax professionals are now extensively looking for ways to implement diverse strategies, techniques, and advanced technologies to improve productivity and reduce errors.
Administration in tax companies is investing in technologies to expand their capabilities. To identify, classify, avoid, and implement, the control framework must become more powerful.
Automation is leading to agile tax operating models
Digitally developed organizations are effectively using Robotic Process Automation (RPAs) for smooth and quick operations. However, this is not the case for all businesses. Some businesses aren’t committed to investing time, effort, and strategy in RPA. Moreover, other firms that launched unstructured RPA projects are now ‘stuck’ and suffering from various challenges due to IT gaps or process complexities.
Another problem that many RPA firms face is a shortage of Subject Matter Experts (SMEs) with RPA architecture and development knowledge.
Therefore, to fully realize robotics potential, businesses will need to develop a new skill set for the existing workforce. They will require an augmented workforce who can collaborate with robots.
A move towards cloud-based Enterprise Resource Planning (ERP) solutions
Most major businesses and organizations are today shifting towards cloud-based ERP solutions. ERP provides a shared data source that records the data in a standard language. This available source eliminates the need for complex manual data mining that most tax functions opt for today.
As a result, using ERP technology for tax collection will inevitably save money and reduce complexities. In addition, tax professionals can now ensure data security. So, they can move on to other aspects like analytics and strategy planning for the businesses.
Adopting Artificial Intelligence (AI)
Tax departments also use AI and advanced analytics to draw inferences and predict situations from different data sources. Moreover, with established use cases, such technologies are becoming more accessible. As a result, more and more organizations have begun to adopt them.
Many businesses began their path with simple AI advancements. However, there is still room for automation technologies like RPA to be adopted. RPA may free up tax professionals’ time by enlisting their participation in adopting technology with immediate payoffs. In addition, RPA technology paves the path for implementing more complex and sophisticated technologies in the future.
Some businesses may hesitate to adopt automation due to high-cost factors. However, technological investments do pay great returns in the future. Companies can reduce costs and eliminate errors in several ways by incorporating these technologies into their operations wholly.
One of the excellent cost-saving methods is outsourcing. In this operating model, companies hire the skill set of a third party for an affordable fee and the desired time. This method allows them to eliminate the cost of investing in ‘in-house’ technologies and professionals. They can access the benefits of the same at a much lower price.
Tax industry: What the future beholds?
New initiatives are leading to increased transparency, leveraged automation, and cross-border information exchange, which aims to make the tax landscape an absolute no-brainer for multinational corporations that are radically shifting. However, it is important to note that increased automation and improved data security also require rigid enforcement tactics and compliance rules.
Technology does hold the key to the future of tax like for any other industry. New technology solutions are developing every day, making way for a complete digital transformation of end-to-end tax processes. It includes data collecting, analysis, compliance, and audit activities, to name a few.
New technology innovations and unparalleled global transparency assist multinational corporations in making their tax functions more advanced, smooth, and secure. To avoid tax functions from becoming critically vulnerable to speed, accuracy, and quality, tax leaders must evaluate their operating models and derive optimum solutions that are agile and robust.
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