Skip to content
Two businesspeople working in an office

Why technology and a solid data foundation are key to tax transparency

EY Americas
EY Americas

Multidisciplinary professional services organization

9 minute read 21 Jan 2025

Breakthrough technologies such as GenAI are already amplifying tax teams’ transparency efforts, and more tech support is on the way.

In brief
  • Tax regulation has dramatically increased transparency obligations for tax teams.
  • Technology such as AI can prove to be transformational for tax teams, but it is also enabling tax authorities to achieve increasing levels of scrutiny.
  • Tax teams should keep pace with technology advances and make their data transformation-ready if they are to help deliver the required levels of transparency.

The global tax transparency imperative, propelled by sustained collective action by the world’s governments on tax policy, has raised the stakes for businesses that find themselves accountable to a wider variety of stakeholders than a decade ago.

Tax disclosures don’t just have to comply with the myriad transparency laws across jurisdictions, they’re increasingly important to meeting stakeholder expectations around corporate citizenship and informing broader objectives around corporate environmental, social and governance (ESG) objectives.

Businesses are increasingly deploying technological tools to both meet their obligations and harness their tax data to gain better insights about their own enterprises, including sharing more details about their affairs publicly. But knowing what tools to invest in can be a challenge, particularly for tax functions who are among those identifying cost pressures as their biggest obstacle to fulfilling their vision and purpose.

Getting it right is critical. Dramatic advances in digitalization, data storage and artificial intelligence (AI) analysis, all enable taxpayers and tax authorities to quickly interrogate huge volumes of data. Such tech advances are also enabling authorities to routinely share and compare taxpayer data with overseas counterparts, increasing the need for businesses to be consistent about what they’re sharing publicly about themselves.

AI-equipped tax administrations
The number of tax authorities saying they either use AI or they are planning to do so, according to OECD figures from 2022.

How EY can help

  • Tax technology and data

    Our tax professionals can help your business manage tax big data in a way that enables efficient compliance and provides strategic insights. Learn more.

    Read more

Advances in technology offer opportunities including efficiency gains and better visibility about how taxes affect other functions for tax teams faced with more reporting regimes. But they also face more compliance risks as tax authorities also become more tech-enabled. The Organisation for Economic Co-operation and Development (OECD) Tax Administration 2022 report shows that as of 2022 more than 40 tax administrations globally are either using AI or planning to do so.1

 

It is critical to keep current with the latest developments in regulatory technology and harness it to increase the granularity, accuracy, cost effectiveness and timeliness of reporting data. This is especially true to meet the demands of increasingly tech-enabled tax authorities.

 

Being more transparent about tax practices is one way to build trust and remain compliant in this dynamic environment. This is often easier said than done, however. Even if individual tax teams comply with specific tax regulation, their positions will still be vulnerable if they do not have a centralized strategy spanning entities and jurisdictions.

 

 Sourcing data for reporting related to digital tax filing, especially e-invoicing, ESG-related demands and initiatives from the OECD’s base erosion and profit shifting (BEPS) project including the global minimum tax under Pillar Two is challenging, leading many companies to turn to outsourcing for help. The 2024 EY Tax and Finance Operations Survey found that businesses say complying with real-time and digital tax filings is the most “significant” emerging reporting requirement they face.

The importance of creating a single source of tax master data

Albert Lee, EY Global Tax Technology and Transformation Leader, says creating a single source of data is the most effective first step towards enabling effective tax analysis and a foundation for AI.

Poor data quality creates a lack of trust, which means a lot of time is spent preparing and checking tax information.

Albert Lee

EY Global Tax Technology and Transformation Leader

He says tax professionals are currently committing too much time and effort validating large volumes of general ledger data – such as supplier and customer names and locations, registration numbers, transaction tax codes, goods and services tax (GST) and value-added tax (VAT) numbers as well as numerous legal entity data points.

 “Poor data quality creates a lack of trust, which means a lot of time is spent preparing and checking tax information,” Lee says.

He adds that tax teams should ask themselves if each line in a general ledger, payment or invoice system has been classified correctly. “If that data is incorrect or incomplete, this impacts all subsequent disclosures, undermining transparency efforts as well as damaging confidence across the wider business,” he says.

1

Chapter 1

Harnessing AI to build a solid foundation of tax data

Human-in-the-loop AI systems are helping tax professionals address critical anomalies in huge data sets.

Forward-thinking tax teams are already recruiting AI to automate many of the processes needed to achieve transparency. They’re using it to validate foundational tax data accurately and quickly, while escalating anomalies for human review. This approach both builds the solid data foundation needed for transparency and frees tax specialists to concentrate on value-added tasks, while streamlining a myriad of downstream tax-data-reliant activities.

The process of compiling a comprehensive list of legal entity data provides a prime example of what AI can achieve. This process can be particularly difficult because legal entity data is often dispersed across the business, stored piecemeal on secretarial data bases, enterprise resource planning (ERP) systems, or even saved locally on spreadsheets compiled by business functions and individuals; in fact, 63% of businesses rely on a provider to consolidate their data out of multiple ERP systems, the TFO survey found. It is unusual for one individual, team or function to take full responsibility for compiling a complete picture of legal entity status. The result is an often incomplete and inaccurate patchwork of information.

Once this information has been gathered, however, an AI-powered entity management solution can reconcile multiple lists and enable tax teams to generate and maintain a single, centralized source of the truth. AI entity management uses a technique called interpolation, which automatically interrogates lists containing thousands of data points, cross-referencing similar legal entity names and identifying possible errors and duplications. Such solutions flag up anomalies for human tax practitioners to review. This AI-powered approach dramatically reduces tax teams’ workloads by switching their focus to exceptions, while also reducing risk by keeping a constant “human-in-the-loop”.

Using AI interpolation

AI interpolation can be used in much the same way to generate a centralized profit and loss (P&L) ledger. Once data has been collected, an AI agent can use interpolation to cleanse and create a single view of P&L truth. Tax practitioners can then adjust this master data according to the specific needs of each end user. For instance, reporting P&L figures to a stock exchange or financial regulator or filing a tax return – each reporting regime with its own unique rules and requirements.

AI solutions avoid the need to generate a separate P&L data set from scratch for every location and use case. This approach is resource-hungry, duplicates labor and increases the risk of errors. It can also undermine transparency efforts by failing to align tax information consistently across entities, business functions and jurisdictions.

Lee says a solution for storing tax data centrally already exists: Enterprise performance management (EPM) systems originally designed to fulfil financial planning, analysis and consolidation purposes are now increasingly being used as tax data warehouses. 

In particular, EPMs are a highly compelling solution for BEPS 2.0 Pillar Two reporting, as they are often used for consolidation and financial reporting. This means they can be easily expanded to accommodate BEPS requirements. “EPMs are ready-made data warehouses that tax functions could be leveraging more,” Lee says.

2

Chapter 2

GenAI assistants are the next step in helping tax teams achieving transparency

Leading edge GenAI solutions both analyze raw tax data and answer questions.

While conventional deterministic, rules-based AI is being used to great effect validating and cleansing tax master data, 87% of tax and finance directors believe integrating GenAI will drive efficiency and effectiveness within the tax function, according to the TFO survey.

Conventional AI requires human operators to collect the raw data needed to achieve tax transparency, but GenAI can automate this process almost entirely and can then validate and cleanse the collected data before generating rich insights.

Richard Clough, EY Global Tax Chief Data Officer, says this breakthrough technology is already being used in four key ways to automatically generate a single view of tax truth, establish external tax rules and ultimately make a unified tax narrative and transparency easier to achieve. These four broad use cases are:

  • Knowledge engineering: This involves using GenAI to source, retrieve and make sense of tax rules from a variety of data sources, including official reports, memos, emails and online information.
  • Document analysis: Interrogating reports, memos, emails and online information, applying tax queries and generating high-quality answers. Analyzing and summarizing new data, for example, as well as reading and reviewing tax documents.
  • Content generation: Creating new content, such as tax reports and memos, based on knowledge and insights derived from existing information. For example, a GenAI-powered BEPS 2.0 Pillar Two virtual assistant.
  • Data engineering: Creating and managing data flows to move, transform and cleanse information. For example, trial balance/tax reporting, data mapping and cleansing, provision to compliance, and transfer pricing.

Clough says his EY team has been working with a mix of clients to achieve proof of concept in these four key areas. It is now focusing on evolving clients’ tax operating models so they can embed GenAI. 

3

Chapter 3

How GenAI helps tax teams improve their horizon-scanning capabilities

GenAI can identify new regulations and then map them to a company’s existing tax risk data.

It is useful to consider how GenAI can be used to scan regulations to fully appreciate the potential impact of GenAI on tax transparency efforts. Horizon scanning is a critical task that allows tax teams understand the direction of regulatory change and can align their strategy across entities and jurisdictions in a joined-up and timely manner. It can be an intensely resource-hungry task. GenAI, however, can dramatically reduce the time and effort needed to understand and action the seemingly endless torrent of information tax teams need to digest.

For example, with the right tax-specific large language models, GenAI can automatically extract historic data on tax positions from internal tax and finance data bases, memos and emails. The technology can then cleanse, codify and classify this information to create a searchable database which can be interrogated using standard tax terminology by tax practitioners.

GenAI can then be used to identify and make sense of the often fragmented and confusing rules published externally by tax authorities. This is achieved by linking a GenAI agent to external information sources such as online EY tax alerts, online OECD releases and other documents from privately-owned legal databases. According to Clough, such solutions help shorten the time needed to generate a curated rules set from around four weeks to less than one minute.

Horizon scanning can then be achieved by overlaying these internal and external insights and instructing a GenAI-powered risk agent assistant to look for new tax rules which affect the company’s tax positions. It can then flag risk areas in real time for urgent human review. 

4

Chapter 4

The future of tax transparency is a human/AI partnership

Human tax professionals empowered by AI and other tech solutions are changing tax transparency.

One of the biggest benefits of GenAI is that tax practitioners need little or no experience of working with the technology to generate real value. Natural language processing enables them to “chat” with the solution using everyday conversational sentences to identify and explore areas of tax risk, and the solution can then generate a report on demand.

Both Lee and Clough say AI, and especially GenAI, are already proving to be a powerful tool in generating detailed, accurate and timely tax insights that were previously unobtainable through conventional manual processes. They maintain that effective transparency in areas such as BEPS 2.0 Pillar Two, country-by-country reports, the Common Reporting Standard and, for the businesses that choose to participate in it, the Global Reporting Initiative, will rapidly become reliant on humans with the right tax knowledge who are empowered by AI and other tech solutions. Here are three key steps to ensure tax team data is ready for this journey:

  1. Centralize data standards across a federated data as much as possible. Define tax team requirements and ensure there is a method of storing a single source of the truth, such as an EPM.
  2. Identify and examine current data pain points and areas of inefficiency. This will enable tax teams to identify use cases for automation and AI.
  3. Determine the best tech solution for data ingestion, processing and reporting and how this technology can best dovetail with existing systems and processes.

Summary

Data-focused technologies such as GenAI are set to help tax teams overcome the growing challenge of achieving granular and timely tax transparency. However, tax teams will first need to ensure centralized data standards are adopted across a federated data landscape if they are to develop a unified narrative across companies and jurisdictions. 

Related articles

To optimize your tax and finance functions, dig into your data

Data from a recent global tax and finance survey: 500 US-based multinationals offer insights around modernized data strategy and management. Learn more.

13 Dec 2024 Anya Parkhurst

How a decade of transparency forever changed the tax world

A decade of increased tax transparency has changed businesses, who will need more data management to keep up with new developments. Learn more.

22 Nov 2024 Aruna Kalyanam

The future of AI in Tax: insights and practical considerations for the tax function

In this webcast, panelists discuss AI’s current impact in the tax industry and uncover how AI can potentially deliver tangible value in tax operations.

29 Oct 2024 | your local time

How will GenAI shape tax and finance transformation?

GenAI may help tax and finance functions struggling with cost, talent and regulatory pressures. Transforming operating models can help integrate it.

09 Oct 2024 EY Americas

Why public disclosure will require renewed focus on CbC reporting

Public disclosure of country-by-country tax data is set to create new risks for affected multinationals. Learn more.

05 Jun 2024 EY Americas

    About this article

    EY Americas
    EY Americas
    Multidisciplinary professional services organization
    Related topics
    Tax
    Tax controversy
    Tax compliance
    Global tax reform
    Law

    EY refers to the global organization, and may refer to one or more, of the member firms of Ernst & Young Global Limited, each of which is a separate legal entity. Ernst & Young Global Limited, a UK company limited by guarantee, does not provide services to clients.
    You are visiting EY us (en)
    us en