How is AI & Machine Learning revolutionizing the Tax Landscape?

By Sean Sutton
Read Time: 2 Minutes
TAINA, regulation changes, W9 form, W8 forms, QI list, treaty changes, digital asset regulations

How is AI & Machine Learning revolutionizing the Tax Landscape?

Over the last decade of evolving regulations in the tax landscape, Artificial Intelligence (AI) and Machine Learning technologies have brought about an intellectual revolution. These innovations have become indispensable tools in the competitive global market. They do not pose a threat, but instead offer a chance to improve operations and enhance efficiency, cost effectiveness, and customer experience.

Tax administrations globally have not ignored this transformation. The adoption of AI and machine learning technologies is a seismic shift reshaping how tax authorities and businesses approach tax compliance. Businesses are realizing the power of digitization. TAINA Technologies helps them modernize their tax processes.


The Global Drive Towards Technological Advancements in Taxation

Tax authorities worldwide are dealing with the same challenges as private companies in updating old technology and automating manual processes. It is part of the journey created by FATCA and CRS; a journey towards greater transparency, efficiency, and accountability. Data-driven insights guide tax authorities and businesses towards a future where taxation fuels growth, not burdens it.

In recent years we have seen many countries and tax authorities quietly evaluate and invest in AI and machine learning solutions to achieve their tax administration goals. These solutions include:


1. Customer facing functions:

Improving the taxpayer/customer experience and service quality. To achieve these goals, AI technology is found in online UI journeys, Q/A chatbots, document recognition, language translations of tax laws, and better communications. Tax authorities and large businesses can deliver quicker outcomes to benefit taxpayers/customers by automating routine tasks.

However, there are risks to full automation. Current limitations with AI supported chatbots include data privacy and security concerns, limits on data from the last few years, and that accuracy of responses dependent on customer prompt quality. Most problematic is the legal risk, such as found with AI 'Hallucination', in which responses are fabricated and represented as fact.

But these deficiencies are not stopping tax authorities from investing in technology. In the US, the recently passed Inflation Reduction Act has allowed the IRS to start their Paperless Processing Initiative, a groundbreaking plan aimed at reducing processing times and expediting refunds. Thanks to this initiative, the IRS has nine taxpayer-facing voicebots in operation, in addition to 10 chatbots. To date, taxpayers with balances due have messaged online with Collection chatbots more than 1.6 million times.


2. Operations functions:

The backbone of compliance for tax authorities and businesses in support of the front office. Implementing new technologies such as Robotic Process Automation (RPA) with AI capabilities removes manual procedures and creates straight through processing. Automating tasks not only improves efficiency, but also reduces costs and increases accuracy.

Again, there are risks with full integration of AI or machine learning. Without transparency and oversight, irreparable harm can fall on the people for whom this technology is intended to help. For example, a self-learning algorithm in the Netherlands, run by the Dutch Tax and Customs Administration, was erroneously labeling childcare benefit claims as fraudulent. The civil servants tasked with reviewing the cases relied on the technology and “rubber-stamped” the erroneous flags over eight years, resulting in thousands of families required to pay back their valid childcare tax claims.

But this Dutch example is not a large enough red flag to stop the investments. Lessons learned from past attempts, as well as security and ethical AI use concern have only encouraged more initiatives. The OECD AI Principles was adopted in 2019 to promote use of AI that is innovative and trustworthy. Dozens of other countries have enhanced their processes with a goal to aid customer facing stakeholders; for example:

  • The IRS continues to roll out more online functionality with the goal to assist stakeholders. Most recently they have announced the release of a free tool for withholding agents to validate the information being reported on form 1042S. The tool performs a quality review of data before the withholding agent submits to the IRS, helping ensure accuracy of information and limiting penalty exposure in the event of audit.

  • Previously, the IRS announced that its digitization initiative has scanned a staggering 225 times more forms than in the previous year. This represents a monumental leap in the digital transformation of tax administration, aligning with the IRS's goal of going entirely paperless by Filing Season 2025.

  • In India, the Income Tax Department is using AI tools to assess income tax returns whose ratio of donations to charitable trusts and political parties compared to income is skewed. The department is reviewing prior year data which had previously not been heavily scrutinized.

  • Additionally, the Australian Taxation Office (ATO) has curated machine learning algorithms to consume large amounts of data to provide tax assessments timelier. Their machines are trained to use historical data to make improvements resulting in processes which used to take months now taking only days.

  • Other tax authorities around the world including the Canada Revenue Agency, the General Taxation Department of Vietnam, and the Swedish Tax Agency have also invested in AI technologies to streamline their operational processes.

The technology keeps improving. There are AI tools, such as Cassidy AI, which creates customized AI-assistants for all middle and back-office functions. Feeding these tools with internal procedures, data, and branding improves the reliability of output. This type of augmentation will allow more tax authorities to enforce their laws while enabling firms to remain compliant.


3. Analytical functions:

The greatest transformation may be found in focused data analysis; these technologies excel at detecting patterns, anomalies, and trends within data. The RPA found used for workflow automation is limited to structured data. However, AI analysis enables tax authorities and businesses to identify potential tax evasion, make informed decisions, and formulate data-driven policies based on unstructured data.

The analytical solutions include software examples like Tableau, or Power BI, and using computer-assisted audit tools and techniques (CAATTs) to improve compliance and reduce the likelihood of human oversight errors. Rather than making decisions or conclusions based upon a limited sample of a population, CAATTs allow for a complete review of all transactions to find anomalies. They can also "learn" from patterns, predict which transactions are likely to be erroneous based on past audits, and even suggest areas of focus for human auditors. For example:

  • The IRS is tackling complex partnership tax returns in their Large Partnership Compliance program. With the help of AI, the selection of these returns is the result of groundbreaking collaboration among experts in data science and tax enforcement, who have been working side-by-side to apply cutting-edge machine learning technology to identify potential compliance risk in the areas of partnership tax, general income tax and accounting, and international tax in a taxpayer segment that historically has been subject to limited examination coverage.

  • The National Revenue Administration of Poland is using AI driven system, called STIR, to analyze data provided daily by banks and credit unions. This transaction analysis is being used to detect fraud in real time rather than during annual reporting cycle.

Businesses have the ability to keep up, leveraging their own AI and machine learning strategy. In addition to the data analysis, there are also tools that assess risk and compliance. Risk management can be aided by AI through models which can predict potential risks in strategies by analyzing historical audit outcomes and regulator feedback. Regulatory compliance monitoring leverages trained systems to monitor real-time changes in tax regulations across multiple jurisdictions ensuring strategies remain compliant.

Ultimately, new technology unlocks the potential of data as a strategic asset.


TAINA Platform: A Global Solution for Tax Compliance

As tax authorities around the world start to embrace AI and machine learning to modernize their operations, TAINA's mission to revolutionize the tax landscape through digitization finds relevance on a global scale. In an increasingly interconnected world, collaborations with innovative companies like TAINA Technologies are instrumental in shaping the future of tax compliance.​


We would love to discuss your compliance process and how our award-winning FATCA and CRS Validation platform can help you leverage AI and machine learning to revolutionize your tax operations. For more information get in touch or request a demo to see it in action. 

Whitepapers & Case Studies
Read More +
Webcasts & Videos
Read More +
News & Podcasts
Read More +