Assessing the accuracy and completeness of taxpayer reported information is a core function of tax administrations. This chapter takes a closer look at tax administrations’ work in this area, including what they do to understand and manage compliance risk, and how they prevent and address non-compliance. Finally, this chapter looks at approaches to evaluate taxpayer compliance burdens.
Tax Administration 2024
Comparative Information on OECD and other Advanced and Emerging Economies
Tax Administration
Abstract
The audit, verification and investigation function assesses the accuracy and completeness of taxpayer reported information. This function employs on average 30% of tax administration staff to verify that tax obligations have been met. While this often happens through audits, there is an increasing use of automated electronic checks, validations and matching of taxpayer information. The undertaking and visibility of these and other compliance actions is critical in supporting voluntary compliance, including through their impacts on perceptions of fairness in the tax system, as well as creating a ‘deterrent effect’. This chapter therefore looks at:
How tax administrations manage compliance risks, including the different approaches to prevent and address non-compliance;
The delivery of compliance actions undertaken by tax administrations, looking at audits as well as tax crime investigations; and
The importance of evaluating and reducing taxpayer compliance burden.
The process of compliance risk management, as described in the 2004 OECD guidance note Compliance Risk Management: Managing and Improving Tax Compliance (OECD, 2004[1]), has remained largely unchanged over the years. Its key steps, as illustrated in Figure 6.1., still serve as a blueprint for managing compliance risks. Since then, several OECD reports explored aspects of this framework providing guidance and good practice examples, and the 2017 report The Changing Tax Compliance Environment and the Role of Audit (OECD, 2017[2]) looked at a range of incremental changes occurring across tax administrations which, taken together, were changing the nature of the tax compliance environment, allowing for more targeted and managed compliance.
Source: OECD (2004), Compliance Risk Management: Managing and Improving Tax Compliance, https://www.oecd.org/content/dam/oecd/en/topics/policy-issues/tax-administration/compliance-risk-management-managing-and-improving-tax-compliance.pdf (accessed 12 September 2024).
With ISORA 2023 capturing a significant amount of new data on compliance risk management approaches, this section examines how tax administrations are organising their processes in this area. It does so by looking at tax administrations approaches towards understanding and managing compliance risks, and some of the steps taken by administrations as regards preventing and addressing non-compliance.
Understanding tax compliance risks
Around 85% of administrations report having a formal compliance risk management strategy. Almost all of those having in place dedicated approaches for identifying, assessing and prioritising key compliance risks, with close to 30% making compliance risks public and around one quarter publishing outcomes in addressing the risks (see Table 6.1.). This is on the basis that publication can enhance compliance strategies by increasing taxpayer awareness of possible risks and acting as a deterrent to those considering non-compliance. Combined they can also reassure the public that non-compliance is being dealt with. The example in Box 6.1. describes a new automated risk model developed by Australia to identify international risk in the private wealth market.
Percentage of administrations
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Table B.20 Compliance risk management: Strategy, https://data.rafit.org/regular.aspx?key=74180916 (accessed on 10 September 2024).
The Australian Taxation Office (ATO) has designed an automated international risk model, to identify international tax risks in the private wealth market. The Private Wealth International Risk Model combines bespoke private wealth risk rules with data matching and trend analysis to identify common risks in privately held businesses, including:
Related party financing;
Intangibles migration;
Mischaracterisation of service arrangements;
Business restructures; and
Controlled foreign company risk.
The model allows the ATO to rank taxpayers by international risk, so that resources can be prioritised to focus on the most material cases. It also reduces manual intervention and enables the ATO to identify risks in real time, which mitigates period of review issues (statutory limitations on cases).
Using this new risk model is important to the ATO, because historically tax authorities have focused on identifying the most material international risk in large multi-nationals through Country-by-Country reporting (CbCR) data and publicly available information, which often are not present in privately held groups. As the number and scale of privately held businesses increase globally (largely driven by the scalability of technology-based businesses) this targeted approach allows the ATO to improve the accuracy and efficiency of international risk identification in privately held businesses to complement existing international risk models.
Source: Australia (2024).
Tax gap analysis
The use of tax gap measurements is becoming more common, especially for value added taxes (VAT), as jurisdictions increasingly see the benefits of having high level estimates of non-compliance within the tax system, including identifying compliance risks and understanding drivers of non-compliance.
Tax gap estimation is complex and there are two main approaches:
Top-down methodologies that use aggregated macro-economic data represent a relatively low-cost means of producing such estimates.
Bottom-up methodologies that include information from audits, are more resource intensive but can provide a more accurate picture of lost revenue across segments and tax types.
Two-thirds of the 58 administrations covered in this report indicated that they or another government agency produce periodic tax gap estimates for one or more of the main tax types, with the production of estimates of the VAT tax gap the most prevalent. Around half of jurisdictions that produce assessments make (some of) their estimates publicly available. (See Table 6.2.)
Chapter 11 provides a detailed overview of tax gap estimation by OECD Forum on Tax Administration (FTA) member administrations, including the methodologies used, the different tax gap components and how tax gap analysis is used by tax administrations.
Percentage of administrations
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Table B.24 Compliance risk management: Tax gap, https://data.rafit.org/regular.aspx?key=74180916 (accessed on 10 September 2024).
The National Revenue Agency (NRA) has implemented a project aimed at enhancing the capabilities of the NRA in developing analytical tools and methodologies to determine the extent of tax non-compliance.
The project uses econometric models to understand the key factors that determine taxpayer behaviour and to forecast the evolution of tax non-compliance in Bulgaria. Three models were built focused on the following areas: the shadow economy, Personal Income Tax (PIT) and Value-Added Tax (VAT). The models measured the size of the shadow economy at the country-level and tax gaps for VAT and PIT, as well as assessing their causes.
The models are used by the NRA on regular basis to estimate and forecast the compliance levels, and to choose appropriate measures to increase compliance.
For more information, please see here: https://reform-support.ec.europa.eu/publications-0/strengthening-tax-compliance-assessing-external-context-and-taxpayers-behaviour_en#files (accessed on 10 September 2024).
Source: Bulgaria (2024).
Random audits
Slightly less than two thirds of participating tax administrations report having random audit programmes in place (see Table 6.3.). As well as enhancing any deterrent effect, these programmes also provide a more accurate understanding of compliance risks that can enhance risk-profiling systems. About half of the administrations with established random audit programmes report also using the data to produce tax gap estimates. Those administrations that do not use random audit programmes often cite the significant burden on the taxpayers, particularly low-risk taxpayers who would otherwise not be audited.
Percentage of administrations
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Table B.36 Verification / audit activity: Random audits, https://data.rafit.org/regular.aspx?key=74180918 (accessed on 10 September 2024).
Increasing availability of data
As more and more data is stored electronically, and the transfer, storage and integration of data has become easier through the application of new techniques and processes, there has been a huge increase in the amount of data available to tax administrations for compliance purposes, that can help them to understand risk areas and promote tax compliance. Frequently used data sources include:
Data from devices: Data can be collected from devices that register transactions such as online cash registers and trip computers for taxis and trucks, and also gate registrations from barriers and weigh bridges.
Data from banks, merchants or payment intermediaries and service providers: This allows direct verification of income or assets reported by the taxpayer. Some jurisdictions already receive transaction details or transaction totals for taxpayers on a regular basis.
Data from suppliers: Collecting data from suppliers, either directly or through the taxpayer, allows a more complete picture to be drawn about the activities and income of the taxpayer. This is seen in the increasing use of e-invoicing systems which, as noted in Chapter 4, allows some tax administrations to prefill tax returns.
Data from the customer: This is easiest in cases where the number of customers is limited and known, but increasingly mechanisms to leverage customer data are being used, for example in the verification of cash receipts.
Unstructured data concerning the taxpayer: Increasingly electronic traces relevant to business activities and transactions can be found on the internet and in social media.
Data from other government agencies: Data held by other government agencies for example for licencing, regulatory or social security purposes can be relevant in verifying tax returns or in risk assessments.
Data from international partners: International exchanges of data from the International Standards for Automatic Exchange of Information in Tax Matters (OECD, 2023[3]) and Country-by-Country Reporting (OECD, 2015[4]) is massively increasing the quantity of data available on international activity and providing useful information for audit and case selection processes and in some cases for prefilling of tax returns.
Much of this is a result of technological advancements and the digitalisation of the economy, and tax administrations can help to further promote the digitalisation and digital transformation of business operations as can be seen in the example included in Box 6.3.
The National Tax Agency (NTA) has started promoting the digitalisation of general business operations to improve accuracy and processing speeds.
Up until now, the NTA has mainly focused its digitalisation efforts on tax procedures. However, if various day-to-day business processes (for example, billing payments and accounting) were also digitalised, this would improve the overall accuracy of processing and productivity of general business operations.
The NTA has a wide variety of stakeholders, including related private organisations, tax professionals, and local economic organisations. In promoting the digitalisation of businesses, it is essential to work and cooperate with these organisations, related ministries and agencies more than ever.
The NTA will continue to work on the digitalisation of society as a whole through further cooperation and collaboration with related organisations to create momentum for digitalisation among businesses, such as the Joint Declaration on Digitalisation and the Declaration on the Promotion of Cashless Payment, as well as by strengthening cooperation and collaboration with other ministries and agencies to promote awareness of and encourage the use of digital invoices and various subsidies.
Source: Japan (2024).
Table 6.4. shows for which types of income individual payment details are generally reported to the administration. Not surprisingly, almost all administrations receive information on wage and salary payments. This is followed by dividend and interest payments where around 80% of administrations receive information on individual payments. Looking at the jurisdiction level data, a significant number of administrations receive comprehensive information on income payments making pre-filling regimes possible (see Chapter 4) and underreporting by the taxpayer more difficult. (See also Table B.50.)
Percentage of jurisdictions
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Table B.50 Reporting of payment details, https://data.rafit.org/regular.aspx?key=74180917 (accessed on 10 September 2024).
With significant amounts of data being available, tax administrations are investing in systems for importing, storing and managing third-party data. Table 6.5. summarises for which types of third-party data administrations have such systems. Around 80% of administrations are working with customs data, data from social security agencies, and/ or data on property ownership and sales. Close to half of the administrations are also importing, storing and managing data from online vendors.
Percentage of administrations
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Table B.51 Third-party data, https://data.rafit.org/regular.aspx?key=74180918 (accessed on 10 September 2024).
With ongoing digital transformation, there is also more tax related data becoming available from taxpayer’s business systems. This includes, for example, e-invoicing systems and the use of devices that register and transfer data to the administration. As Table 6.6. illustrates, half of the administrations receive data from electronic fiscal devices or cash registers and in two-thirds of those situations, data is transferred automatically. A small number of administrations (around 15%) also receive data from other devices such as taxi meters.
Percentage of administrations
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Tables A.105 Compliance approaches: Electronic invoicing, and A.106 Compliance approaches: Devices that register transactions, https://data.rafit.org/regular.aspx?key=74180897 (accessed on 10 September 2024).
Lithuania – Smart Electronic Cash Register Subsystem
The State Tax Inspectorate (STI) has implemented a project for the creation and implementation of the Smart Electronic Cash Register Subsystem (i.EKA), one of the seven parts of the intelligent Tax Administration System project in Lithuania. The objectives of the i.EKA project are to reduce the administrative burden on businesses, increase the efficiency of the STI, and reduce the size of the shadow economy by modernising and optimising the use of cash registers through creating and implementing new electronic services:
Remote registration of cash registers and other points of sale – this allows businesses to automatically fill in an electronic technical passport, remotely perform registration of a means of payment, notify a change of conditions, adjust registration data, and process the digital certificates necessary for the process of recording and transferring transactions.
Virtual fiscalisation for cash registers and other points of sale – this service enables the automatic transfer of receipt data (for example, receipt amount, VAT rates and amount) from cash registers or other means of payment to the tax authority directly, forming an electronic journal of a cashier’s operations.
This has enabled more efficient control of income accounting and real-time reviews of cash register registration data, as well as the ability to generate cross-cutting reports on i.EKA managed data. The data obtained from the cash registers can be used for comparison with the data provided in declarations submitted by taxpayers to assess if there are any risks. Customers of registered businesses can verify the submission of their receipt data to STI and whether the transmitted data is correct. If there are discrepancies, the buyer can submit a report about potential violations.
Saudi Arabia – Electronic Invoicing (Fatoora Project)
Electronic invoicing (e-invoicing) was introduced as part of Saudi Arabia’s (KSA) ongoing economic renaissance and digital transformation efforts. As part of this, the Saudi Zakat, Tax, and Customs Authority (ZATCA) introduced the National E-invoicing Project (“Fatoora Project”).
The implementation of this Project was divided into two distinct phases:
Phase 1, from 4 December 2021, focuses on the generation of e-invoices. It also includes provisions regarding the processing of electronic invoices, and the essential task of record-keeping.
Phase 2, from 1 January 2023, involves the integration of taxpayers’ e-invoicing systems with ZATCA’s e-invoicing portal (Fatoora). It mandates the transmission of e-invoices and e-notes, along with the requirement to share them with ZATCA.
E-invoicing has had several positive impacts in KSA, being implemented by over 300 000 taxpayers through over 700 listed solution providers to generate, transmit, and store e-invoices.
The key impacts are:
Manually generated paper-based invoices have been completely eliminated since Phase 1.
Over 950 million e-invoices have been generated since the launch, with a success rate of 98%.
Clearance of invoices by Fatoora has been achieved in less than 0.1 seconds through fully automated solutions.
E-invoicing has played a significant role in the government’s digital transformation plans detailed in the Kingdom’s Vision 2030 strategy. This initiative demonstrates ZATCA’s commitment to adopting digital technology, supporting a digital economy, and functioning as a critical facilitator in reaching ZATCA’s goal of becoming a “World Class” digital revenue administration organisation.
Sources: Lithuania (2024) and Saudi Arabia (2024).
With increasing amounts of data being handled by tax administrations, the implementation of mechanisms to protect and manage data is now commonplace, and a critical function. These mechanisms support wider data governance processes, and in turn help maintain taxpayer trust in the system as well as meet legal obligations (See Table 6.7.). Moreover, as data systems become more connected, the importance of cyber security is growing. The 2023 edition of this publication contained a few examples from tax administrations in this space – see Tax Administration 2023, Box 10.5. (OECD, 2023[5]).
Percentage of administrations that have the respective process in place
Note: The table is based on data from 52 jurisdictions that are covered in this report and that are included in the ITTI database.
Source: OECD et al. (2024), Inventory of Tax Technology Initiatives, https://web-archive.oecd.org/temp/2023-03-09/618463-data-management.htmhttps://www.oecd.org/tax/forum-on-tax-administration/tax-technology-tools-and-digital-solutions/, Table DM4 (accessed on 10 September 2024).
Tax compliance and gender
The ISORA 2023 survey also explored whether tax administrations started looking into tax compliance by gender. Identifying whether a gender difference exists in tax compliance, could help administrations to tailor compliance approaches, but also to address underlying causes through tailored taxpayer services and education campaigns.
Only eight administrations reported collecting gender-disaggregated data for individual taxpayers on tax compliance and six of those have undertaken a compliance analysis based on gender. Interestingly, half of those administrations concluded from their analysis that it is not necessary to make changes to the way they administer the tax system.
Percentage of administrations
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Table B.21 Compliance risk management: Gender-disaggregated data, https://data.rafit.org/regular.aspx?key=74180916 (accessed on 10 September 2024).
Managing tax compliance risks
Data science
Over recent years, the application of advanced analytics to risk management and risk targeting is becoming increasingly common:
Table 6.9. shows 80% of tax administrations reporting using big data in their work, and of those that use big data nearly all are using it to improve their compliance work.
Of the 58 tax administrations covered by this report, nearly all report using data science / analytical tools with the remaining administrations in the process of preparing the use of such tools going forward (see Table 6.10.).
Similarly, the use of artificial intelligence, including machine learning, for risk assessments and detecting fraud is already undertaken or in the process of being implemented by around half of the administrations covered in this publication (see Table 6.9.).
This increasingly sophisticated use of analytics on expanded data sets is leading to a sharpening of risk management and the development of a range of intervention actions, including through automated processes. Additionally, the OECD report Advanced Analytics for Tax Administration: Putting data to work (OECD, 2016[6]) provides practical guidance on how tax administrations can use analytics to support compliance and service delivery.
Percentage of administrations
Note: The percentages are based on ITTI data from 52 jurisdictions that are covered in this report and that have completed the global survey on digitalisation.
Source: OECD et al. (2024), Inventory of Tax Technology Initiatives, https://web-archive.oecd.org/temp/2023-03-09/618463-data-management.htm, Table DM3 and https://web-archive.oecd.org/temp/2023-03-09/618466-tax-rule-management-and-application.htm, Table TRM3 (accessed on 10 September 2024).
Australia – Enhancing capabilities across business, technology and data & analytics domains
The ATO is one of the largest consumers of third-party data in Australia.
To enable the ATO to follow the OECD’s Tax Administration 3.0 vision, the ATO has embarked upon a modernisation programme. This programme has successfully delivered upon its initial tranches, underpinned by some innovative capabilities, including:
Nexus agile delivery methodology: The implementation of a Nexus delivery method under the scaled agile framework, to facilitate improved collaboration between architecture and delivery team members, resulting in increased delivery speed. This has shifted the culture from monolithic system delivery to rapid, iterative value driven releases.
(Note: The Nexus framework builds on Scrum (an agile team collaboration framework) to enable multiple teams to work together on a single product by minimising cross-team dependencies and integration issues. It focuses on continuous integration and delivery, ensuring that teams contribute to a cohesive and integrated outcome by the end of each sprint.)
Uplifted cross-disciplinary capabilities for the future: The ATO has established multi-disciplinary teams, with cross-skilled team members from data consumers, engineers and producers. This has reduced skill dependencies, enabling continuous and timely design.
Pattern based approach to enhance ATO data capabilities: The ATO has implemented a use-case driven approach to deploy patterns in its new capabilities, made up of two key components:
Solution patterns – Reusable end-to-end solutions for specific data characteristics to achieve a business outcome.
Component patterns – Reusable, configuration-driven patterns within an application to satisfy common and repeatable requirements e.g., reusable patterns for ingesting streaming data across multiple use cases.
The ATO has seen a reduction in development time starting to emerge at the end of its first delivery tranche, and significant use-cases emerging that are lining up to use its new data patterns, including the administration of highly complex tax affairs using fully automated solutions.
Finland – Status centres
The Finnish Tax Administration has in recent years reformed the way it operates, and as part of this has introduced status centres to measure to what extent its operations are achieving the administration’s goals. This is done by comparing and collecting data on activities and targets in one place, allowing for employees to make decisions and set further goals based on the evidence.
Thousands of employees in the tax administration actively use status centres, including for team meetings where successes, lessons and challenges can be identified to inform next steps. Data sharing and communication is key in advancing evidence-based decisions to support the administration’s goals and find solutions to any challenges faced.
The status centres have seen trust and interaction within teams and across the administration increase. Having access to all the relevant data and information directs attention to any issues, focusing discussion on solutions and enabling informed goal setting.
France – Using artificial intelligence to fight real-estate property income taxation fraud
The Directorate General of Public Finances (DGFiP) has started using artificial intelligence (AI) to identify tax fraud, with positive results.
In particular, DGFiP uses AI to calculate the level of rents that need to be declared for income tax purposes in relation to both property that is owned and rented out. A model has been built to estimate the rental value of each property, which is based on a machine-learning algorithm that analyses and links the amount of rent declared, the characteristics of the rented properties and the socio-economic data for the neighbourhoods in which the properties are located (median income, household composition, number of social housing units, etc.).
The model is then applied to all the residential premises rented out, and the total estimated rental amount for each landlord is compared with the rent they declare, enabling DGFiP to detect any under-reporting of rental income and potential fraud.
This was the first model to be put into production for targeting tax fraud by private individuals, and the cases selected for audit by the model resulted in additional tax being paid in almost 50% of cases. Whilst the support of service providers was needed to launch this work, the necessary data-science skills have now been developed within DGFiP to carry out this work.
Japan – Use of artificial intelligence and data analytics in taxation
The NTA is working to improve the efficiency and sophistication of tax collection by using AI. This makes it possible to determine taxpayers with a higher risk of not filing their tax returns correctly and increases revenue by collecting more tax.
The NTA analyses data from a variety of sources, including tax returns and financial statements provided by taxpayers, information provided by third parties, and information from tax audits. This data is then analysed using statistical analysis and machine learning methods to determine which taxpayers are most likely to not file their tax returns. By utilising the results of this analysis, NTA is able to carry out its tax audit and compliance measures more efficiently.
For example, in 2022 AI determined that the average amount of additional tax due per corporate tax and consumption tax audits for small and medium-sized enterprises was 40% higher than the tax actually received. Part of the issue was that regional taxation bureaus struggle to contact taxpayers, even after attempting phone calls or in-person visits. Therefore, AI is used to predict the most preferable method to make contact, ranging from making phone calls to in-person visits and sending letters. This is based off information such as previous contact archives of taxpayers and their tax returns.
Sources: Australia (2024), Finland (2024), France (2024) and Japan (2024).
Percentage of administrations
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Tables A.108 Innovative technologies: Implementation and usage - Blockchain, artificial intelligence, and cloud computing, and A.109 Innovative technologies: Implementation and usage - Data science, robotic process automation, and APIs, https://data.rafit.org/regular.aspx?key=74180897 (accessed on 10 September 2024).
With the use of analytics becoming a common and integrated part of tax administrations across the world, in developed and developing countries alike, the OECD’s Forum on Tax Administration developed the Analytics Maturity Model (OECD, 2022[7]) to help tax administrations self-assess their current level of maturity in their analytics usage and capability. This provides insight into their current status by identifying areas of weaknesses as well as strengths. As Figure 6.2. shows, it has been completed by over 40 tax administrations, and the results of this are guiding and supporting administrations in their analytics strategies.
Source: OECD (2022), Analytics Maturity Model, https://www.oecd.org/en/topics/sub-issues/comparative-analysis-of-tax-administrations/tax-maturity-models.html (accessed on 10 September 2024).
Taxpayer programmes
Another approach for targeted risk management is the creation of units looking into the tax affairs of specific taxpayer segments. Two specific areas where tax administrations have found it advantageous to manage specific groups of taxpayers on a segmented basis are large business taxpayers, and high net wealth individuals (HNWIs). The rationale for focusing administration resources on managing these groups revolves around the:
Significance of tax compliance risks: due to the nature and type of transactions, offshore activities, opportunity and strategies to minimise tax liabilities; and in the case of large business, the differences between financial accounting profits and the profits computed for tax purposes.
Complexity of business and tax dealings: particularly the breadth of their business interests and in the case of HNWI, the mix of private and tax affairs.
Integrity of the tax system: the importance of being able to assure stakeholders about the work undertaken with these high-profile groups of taxpayers.
Additionally, in the case of large taxpayers, while being a small number of taxpayers, they are typically responsible for a disproportionate share of tax revenue collected. Even though large taxpayer offices/ programmes manage only 1.7% of corporate taxpayers, on average they account for 44% of all net revenue collected, including withholding payments on behalf of employees (Table 6.11.). Looking at the individual country-level, the data indicates that for most jurisdictions between 30% and 60% of their total net revenue was received from taxpayers covered by their large taxpayer programmes (see Figure 6.3.).
Note: The table shows the average percentages across the jurisdictions that were able to provide the information.
Sources: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Tables D.17 Large taxpayer office / program ratios: Full-time equivalents (FTEs), and D.18 Large taxpayer office / program ratios: Corporate taxpayers, additional assessments raised, and net revenue administered, https://data.rafit.org/regular.aspx?key=74180900 (accessed on 10 September 2024).
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Table D.18 Large taxpayer office / program ratios: Corporate taxpayers, additional assessments raised, and net revenue administered, https://data.rafit.org/regular.aspx?key=74180900 (accessed on 10 September 2024).
While the management of these groups of taxpayers is often undertaken as a programme, in a large number of jurisdictions these programmes are also structural involving a Large Taxpayer Office or HNWI unit. As can be seen in Table 6.12. and Table 6.13., the scope of the work of these units varies considerably, ranging from undertaking traditional audit activity, through to “full service” approaches which may also encompass co-operative compliance programmes (see Chapter 8 for more on this). However, on average more than 60% of tax administration staff in large taxpayer offices or programmes are working on audit, investigation and other verification related issues (see Table 6.11.).
As regards the main criteria for including taxpayers in LTO/P and HNWI programmes, these are (by order of importance):
For large corporate taxpayers: Turnover/revenue, economic sector, and amount of taxes (see Table B.16); and
For HNWIs: Assets/wealth, and income (Table B.17).
Percentage of administrations
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Tables A.34 Large taxpayer office / program: Existence and revenue collected, A.35 Large taxpayer office / program: Functions - Registration, return and payment processing, and services, and A.36 Large taxpayer office / program: Functions - Audit, debt collection, dispute resolution, https://data.rafit.org/regular.aspx?key=74180907 (accessed on 10 September 2024).
Percentage of administrations
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Table A.40 High net wealth individuals (HNWIs) office / program: Existence and revenue collected, https://data.rafit.org/regular.aspx?key=74180907 (accessed on 10 September 2024), and Table B.18 High net wealth individuals (HNWIs) office / program: Functions, staff and taxpayers, https://data.rafit.org/regular.aspx?key=74180915 (accessed on 10 September 2024).
Planning for future risks
While it is key for tax administrations to understand current compliance risks and prepare appropriate response strategies, it is equally important to understand and prevent risks which may arise in the future. The increasing availability of data along with the enhanced capacity of tax administrations to handle and analyse that data allows tax administrations to more robustly assess future tax risks.
The ability to identify, understand and manage risks in a rapidly changing environment is a critical element of successful and resilient tax administration. Table 6.9. highlights the large number of tax administrations who engage in forecasting, which is putting them in a position to assess where new compliance risks may arise, and to develop appropriate mitigation strategies. This is leading to the creation of sophisticated risk management programmes, that can embed risk management across the organisation rather than being carried out in silos.
The Finnish Tax Administration conducts foresight activities systematically and as a result, the administration’s top management is provided with information on this four times a year to help assess whether the strategy requires updating.
The groups engaged in foresight activities also share futures information for use in other part of the administration to help give a broad perspective on how the operating environment is changing. There are seven groups: customer relations, customer experience and stakeholders; changes in work; technology; user experience; public administration; PESTLE (Political, Economic, Sociological, Technological, Legal, Environmental); and observations from customer service.
To encourage the widespread use of this insight, information is made available in the management’s status centre. In addition, there are also monthly coffee sessions focused on current foresight activities and a staff training programme.
As a result, the Tax Administration’s foresight activities help foster a collaborative culture and are also widely networked. This collaboration extends to other public authorities and with other countries’ tax authorities so that there is a good snapshot of the present situation and future challenges identified.
Source: Finland (2024).
Planning for future risks also involves tax administrations navigating a number of challenges that might, if not addressed, undermine their overall efforts. Complex and evolving laws and regulations, digital transactions, and cross-border activities can make it difficult to identify and mitigate compliance risks effectively. In this respect, ISORA 2023 invited tax administrations to characterise a number of challenges in addressing compliance risks related to international tax issues.
Table 6.14. summarises tax administration’s views and shows that human resource (HR) related issues cause most concerns. Recruiting people with the right skills, experience and knowledge to deal with international tax issues is perceived as being very challenging by more than half of the administrations. Retaining those people is also considered very challenging by close to 40% of administrations.
Percentage of administrations
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Table B.22 Compliance risk management: Characterization of challenges related to international tax issues, https://data.rafit.org/regular.aspx?key=74180916 (accessed on 10 September 2024).
Preventing non-compliance
Tax administrations rely heavily on the positive compliance attitudes of taxpayers in reporting and paying their taxes. This is often termed “voluntary compliance”. Compliance attitudes are particularly important where tax administrations rely heavily on taxpayers to undertake full and accurate self-reporting of taxable income and taxable events and to make payments.
As highlighted in Chapter 5, tax compliance can be heavily affected by elements outside of the control of the tax administration, but they can use a variety of service-related approaches to support voluntary compliance and prevent non-compliance. Typically, those approaches take place before tax returns are filed and include:
Reminding taxpayers of deadlines (filing and paying);
Facilitating taxpayer access to third-party data already collected, for example, through pre-filing regimes or access to such data through taxpayer portals;
Running targeted campaigns to encourage compliance; and
Providing educational and support initiatives.
Streamlining communication with taxpayers can also be fruitful as can be seen in the example in Box 6.7.
One of the main objectives of the Spanish Tax Agency (AEAT) is to promote voluntary compliance from taxpayers. To achieve this goal, AEAT has undertaken a project to simplify the content and structure of its communications with citizens. Updates include:
The introduction of a header page that outlines in simple language the key information about the purpose of the document, recipient, and actions requested from the taxpayer.
Reduction in the length of documents to streamline information.
Simplification of the response forms attached to make it easier for taxpayers to fill out.
Availability of customer services via telephone (pre-booked appointments only) and webchat.
This project has already produced benefits. There has been a 20.2% increase in responses, reputational benefits for AEAT, and reduced the administrative burden on staff.
Source: Spain (2024).
However, there are also non-service-related approaches that tax administrations have at their disposal to influence compliance. For example, around one-third of administrations indicated that they provide taxpayers with information on predetermined compliance interventions (see Table 6.15.). Knowing that an intervention might come, may encourage taxpayers to pay closer attention to tax compliance issues.
Percentage of administrations that undertake the relevant intervention
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Table B.26 Compliance risk management: Interventions before return filing, https://data.rafit.org/regular.aspx?key=74180916 (accessed on 10 September 2024).
Administrations also reported the use of letters, emails or social media reminding and encouraging taxpayers to fulfil their tax obligations. This might be done through generic mass communication, or in the form of preventive personalised communication to taxpayers with previous non-compliance as regards certain obligations. The use of telephone calls to taxpayers that are considered high-risk has also been indicated.
As regards large businesses, tax administrations also pointed to the use of co-operative compliance programmes and advanced pricing arrangements as a means for preventing non-compliance. Those approaches are described in more detail in Chapter 8.
Behavioural insights and nudges
Another approach for preventing non-compliance is the use of behavioural insights. Behavioural insights is an interdisciplinary field of research using principles from the behavioural sciences such as psychology, neuroscience, and behavioural economics to understand how individuals absorb, process, and react to information. These principles can be used to design practical policies and interventions based on human behaviour. This can be particularly powerful when combined with insights gathered from the analysis of the increasingly large volumes of data available to tax administration, both internally and externally generated. One example of this are nudge messages during the return filing process, providing taxpayers with an indication where there might be potential issues/ errors in the figures being reported.
Around half of the administrations report employing behavioural researchers (see Table 10.4.) and the 2021 report Behavioural Insights for Better Tax Administration: A Brief Guide prepared by the OECD’s Forum on Tax Administration Behavioural Insight Community of Interest contains many examples of this in practice (OECD, 2021[8]).
Australia – Contemporising Goods and Sales Tax risk models
The Contemporising Goods and Sales Tax Risk Models (CGRM) project has developed near to real-time prompts for Goods and Sales Tax (GST) reporting to prevent compliance issues before they arise, by supporting those who want to do the right thing and helping them to reduce mistakes.
The ATO’s data-driven models help reduce the errors and mistakes that taxpayers can make while lodging their Business Activity Statements (BAS) online.
The ATO uses available data to identify where BAS lodged online contain an identifiable or likely reporting error. The ATO then generates nudge messaging recommending that taxpayers check their BAS before they lodge their refund.
This model aligns with a key focus area in the 2023-24 ATO Corporate Plan to improve small business tax performance with a digital-first approach, by providing system-generated tax guidance to minimise errors.
This framework can be expanded in the future to include new tailored nudge messages that assist taxpayers to reduce errors.
This initiative has yielded impressive results in the first two years:
Year 1 (2021-22): 196 000 nudge messages were sent to 102 000 taxpayers. This early engagement helped taxpayers to correct errors before lodging their BAS and resulted in the self-correction and protection of revenue of AUD 51.1 million.
Year 2 (2022-23): 543 000 nudge messages were sent to 217 000 taxpayers. This early engagement helped taxpayers to correct errors before lodging their BAS and resulted in the self-correction and protection of revenue of AUD 43.2 million.
China (People’s Republic of) – Promoting tax compliance with behavioural insights
New behavioural insight methods have been deployed by the People’s Republic of China (hereafter “China”) with regards to filing tax returns. The STA has explored sending different types of prompts and reminders to taxpayers in order to increase the number of filed tax returns.
Taking account of China’s vast size and regional differences in behaviour, different provinces across China were chosen as initial pilots. Overall, it was found that introducing reminder messages and prompts via text message, phone calls and China’s income tax app increased filings by 13%. The STA found that taxpayers in the higher socioeconomic brackets were more likely to be influenced by the prompts and reminders to file their tax returns. It was also found that messages which were more positive in tone (i.e. encouraging people to fill out their tax returns) were more effective than negative in tone messages (i.e. referring to possible consequences and penalties if tax returns were not filed).
Slovak Republic – Online notifications to encourage compliance
The Slovak Republic encourages voluntary compliance from its taxpayers by contacting them using online notifications to remind them of their tax obligations. The notifications vary from reminders to pay taxes and any outstanding payments, to pointing out potential errors in tax returns and giving taxpayers the opportunity to correct these. This applies for both individual taxpayers and businesses.
Notifying taxpayers online of their obligations not only increases voluntary compliance levels with little cost to the tax administration, but also increases the efficiency of the tax administration and enables taxpayers to give any feedback, improving customer service.
Türkiye – Using behavioural insights to increase compliance
Türkiye’s tax administration experiences a large volume of demand for its services. In order to ensure rapid responses to taxpayers and reduce the workload of its staff, Türkiye trialled using behavioural insights to send SMS messages to certain groups to increase compliance:
Personal Income Taxpayers: SMS messages were sent to taxpayers who had not made their income tax payments, reminding them of the declaration period deadline. After the declaration period deadline had passed, taxpayers who had not submitted their declarations were identified and a SMS message was sent to them explaining the subsequent process. Taxpayers who had submitted their declarations but not yet made payments were sent a message explaining how to make payments and reminding them of their outstanding debts.
Motor Vehicle Taxpayers: SMS messages were sent informing taxpayers that the declaration period had started. Taxpayers who did not made their payments were reminded at regular intervals until the end of the declaration period. After the end of the declaration period, thank you messages were sent to taxpayers who had made their payments.
Sources: Australia (2024), China (People’s Republic of) (2024), Slovak Republic (2024) and Türkiye (2024).
Taxpayer rating programmes
There has been an increasing number of administrations reporting the introduction of taxpayer rating programmes to encourage compliance through instilling a sense of responsibility around paying taxes and providing indicators for taxpayers to measure how well they are complying with their obligations. To further incentivise compliance, this is sometimes accompanied with a rewards system for those who comply. Box 6.8. contains the latest developments as regards those programmes.
Georgia – Taxpayer Behaviour Rating Programme
To encourage trust and engagement between the tax authority and taxpayers, Georgia has introduced the Taxpayer Behaviour Programme. This evaluates taxpayers’ overall compliance with their tax obligations and aims to improve compliance levels through instilling a sense of responsibility to pay tax. It is primarily aimed at VAT and mid-size taxpayers.
The Programme uses four indicators to measure how well taxpayers are complying:
1. Tax registration
2. Timely declaration of income
3. Accuracy and completeness of declared information
4. Budget accountability
Taxpayers are evaluated on a 10-point scale with an initial allocation of maximum points. Points are deducted based on how well taxpayers adhere to the indicators, with explanations available online. Assessments are conducted monthly, and taxpayers can view their assigned ratings on the e-portal, along with a historical overview of ratings across reporting periods. Taxpayers are provided with the opportunity to submit feedback on their assigned behaviour rating through a designated feedback form. Plans are being explored to enable taxpayers to make their ratings visible to specific audiences, and potentially even make them public.
Latvia – Taxpayer Rating System
Latvia has introduced taxpayer ratings for companies, to enable them to track their compliance performance and improve it. Each company can access its rating and an explanation of how it is formed in their Electronic Declaration System profile.
The ratings levels are:
A - Good performance – reliable taxpayers that could be good cooperation partners.
B - Needs improvement – taxpayers that generally fulfil their obligations, but there is room for improvement. Taxpayer could be a business partner, but evaluation required in terms of cooperation to determine whether the company has significant tax debts or not.
C - Violations – excluded from the VAT payer register or economic activity suspended.
N - Inactive – no economic activity.
J - Newly-registered – established within the last 6 months.
The indicators which make up the ratings are:
Registration data: whether bankruptcy proceedings have been initiated, if economic activity has been suspended, exclusion from the VAT register, company officials’ tax compliance history.
Timely submission of declarations and reports.
Tax payments paid on time and in full; if a debt arises, pays the debt in instalments.
Penalties: proportion of fines is small compared to total tax payments; does not indicate a serious violation,
Wage assessment: comparison with the average wage in the industry and region. Unusually low wages indicate undeclared wage risks and can lower the rating.
Information indicating violations: risks revealed in risk analyses or information received through international exchange of information.
These indicators help companies to understand where and how they can improve their rating. The State Revenue Service (SRS) provides support to companies with higher ratings, whilst restrictions are in place for companies with a C rating.
Lithuania – Using risk profiles to measure compliance risks
The STI launched the internal taxpayer risk profile (RISKIS) and the external tax profile (Client profile), which offer a convenient, quick and thorough assessment of taxpayer behaviour through using risk criterion and aggregated data visualisation.
RISKIS has 36 criteria used to flag taxpayers that may be at risk of not paying their taxes on time. The criteria are divided into five dimensions - registration, filing, behaviour, control, and payment. The results for each criterion are displayed using the traffic light principle: red indicates a high risk, yellow suggests a medium risk, green signifies no risk, and grey means that the taxpayer is not eligible to be evaluated by means of that specific criterion. For each criterion, relevant data is presented, providing factual information on why a particular criterion has been triggered. For example, if a criterion is triggered due to a failure to submit a tax return, the specific return form and time-period will be displayed. Using different graphics and diagrams, users can easily understand where the taxpayer is on the risk profile. RISKIS also provides a graphical web of dependencies.
The Client profile consists of 21 criteria, similar to those used in RISKIS. The key difference is that Client profiles are visible to individual taxpayers, which gives them some idea of the kinds of behaviour that indicate a risk to STI. All companies can access their respective taxpayer profiles and take action to mitigate risks, make necessary changes, and present themselves as less risky entities. Companies can also share their Client profile information with other peers.
Flat numbers of tax debt and tax loans are also displayed on RISKIS and Client profiles. All the data in both RISKIS and Client profiles is updated on a daily basis.
Slovak Republic – Tax Reliability Index
To encourage compliance, the Slovak Republic uses a Tax Reliability Index to assess its taxable entities that have been registered for income tax for at least two years. Taxpayers are assessed on various criteria, including non-payment of tax, late filing of tax returns, and findings from tax inspections. Based on a points system, taxpayers are automatically assigned one of the following grades:
Highly reliable
Reliable
Less reliable
Not evaluated
Once assigned a grade, this is published online and made public. Taxpayers have the opportunity to challenge their grade. To reward good behaviour and encourage compliance, those in the highly reliable grade are given benefits such as a 50% reduction in the fee for issuing a binding opinion. Alternatively, those in the less reliable category have restrictions placed on them, such as a shorter deadline for the submission of documents required during a tax audit or investigation.
Sources: Georgia (2024), Latvia (2024), Lithuania (2024) and the Slovak Republic (2024).
Addressing non-compliance
Tax administrations determine through a combination of methods and tools whether a taxpayer is non-compliant with their obligations. This may include data matching programmes; data analytics and the use of algorithms, for example, as part of compliance risk models; information sharing between government agencies and jurisdictions; and risk reviews where officials might look into public records and social media (See also Table 6.16.). Box 6.10. contains some of the latest developments in this space.
Percentage of administrations that undertake the relevant intervention
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Table B.27 Compliance risk management: Interventions after return filing, and measurement of intervention effectiveness, https://data.rafit.org/regular.aspx?key=74180916 (accessed on 10 September 2024).
Australia – Automated Network and Grouping Identification Engine
The Automated Network and Grouping Identification Engine (ANGIE) is an automated, rules-based graph database drawing information from a range of internal and external data sources to help ATO staff identify and visualise complex group structures, networks, and understand relationships between entities and group members.
ANGIE replaces legacy systems responsible for linking clients together via known relationships into defined groups (referred to as client groupings). It allocates the groups to populations for the responsible ATO business area to review based on risk priorities, and enables staff to:
Provide an accurate, dynamic, and customisable view of populations and client groups;
Identify changes to a client group and/or population including movements in and out of them;
Visualise and analyse group structures over time and automatically identify significant changes across time periods;
Engage with the right taxpayers by accurately identifying client groups and effective control;
Identify potential risks by seeing where income is earned, assets are owned, and structural changes.
The ATO is expanding ANGIE, with a focus on more sophisticated analytics, powerful visualisation tools and a wider range of grouping populations. This will improve performance, reliability, usefulness and visibility across the ATO, ensuring that the ATO can respond to the increasingly complex networks and emerging behaviours.
Belgium – Data Integrated Operational System application
Belgium has introduced the Data Integrated Operational System application to enable employees of the Federal Public Service Finance to execute everyday tasks more efficiently. DIOS is a fully integrated single taxpayer database in which the user can both retrieve all the information they need and perform all the relevant analysis in one place. The functionalities provided include the following:
The search engines allow for taxpayers to be traced on the basis of incomplete and/or incorrect data (without exact ID identification). A taxpayer can also be traced through other files even if they are not the main subject.
The network analysis function allows the user to visualise the taxpayer’s network.
The score card analysis tool automatically detects potential ‘suspicious’ behaviour directly and/or indirectly linked to a taxpayer or licence holder.
Users can export standard reports to communicate the results of their investigations in a simple and easy to understand way.
Various data mining projects have been integrated into the project to improve and optimise the use of business intelligence.
Canada – Foreign Source Matching Programme
The Canada Revenue Agency (CRA) has implemented the use of the Common Reporting Standard (CRS) and Foreign Account Tax Compliance Act (FATCA) data in its Foreign Source Matching (FSM) programme.
FSM focuses on individual Canadian residents with potential unreported income from foreign countries, by comparing the foreign source data with what was reported on their income tax return.
A pilot was conducted in 2023 to expand the FSM workload by using the CRS and FATCA data feeds, and involved the review of potentially unreported income from 27 jurisdictions. The pilot had approximately 2 000 FATCA and CRS forms linked to taxpayers who may not have reported the interest and dividend income indicated on the forms. The pilot yielded positive results and had a good return on investment.
The FSM program will continue to work with the FATCA and CRS data feeds and monitor the success of these files and identify potential for program growth if applicable.
Italy – Using predictive models to aid compliance work
To aid with its compliance work, the Italian Revenue Agency has developed a predictive model which ranks taxpayers according to how well they comply with their obligations. The model uses historical tax audit data on taxpayers, and produces a set of scores that can be used to prioritise cases for additional checks and audits.
The process for selecting taxpayers for audit has different phases:
1. Risk analysis to detect suspicious behaviours and identify high risk cases for further analysis.
2. Investigation into these high-risk cases, including sending questionnaires to customers or contacting them for clarification on any uncertainties.
3. If the investigation finds tax violations, the tax administration will formally request the taxpayer to pay an amount based on the violation.
4. Taxpayers can choose whether to pay the amount or to start a tax litigation.
The methodology is based on modelling each phase of the process through a suitable probability distribution. These different models are then combined to predict a score expressing the overall profitability of the investigation of each selected taxpayer.
Sources: Australia (2024), Belgium (2024), Canada (2024) and Italy (2024).
Based on those methods and tools, a tax administration might request further information (see Table 6.16.) or provide a taxpayer the opportunity of voluntary disclosure. Where deemed necessary, a “compliance action” will be launched to determine whether taxpayers have properly reported their tax liability.
The increasing availability of data and the introduction of sophisticated analytical models and artificial intelligence are allowing administrations to better identify returns and claims or transactions which might require further review or be fraudulent. Furthermore, these models, many of which can operate in real-time, are allowing administrations to conduct automated electronic checks on all returns or on transactions of a particular type.
The use of automated electronic checks or using rules-based approaches to treat some defined risks (for example, automatically denying a claim, issuing a letter or matching a transaction) is providing administrations with more effective and efficient ways to undertake some of this work. As Table 6.17. indicates, around 80% of administrations are using electronic compliance checks as part of the return filing process, with:
Around 60% of those doing this during the process of completing the return or while submitting it, for example, via prompts and real-time nudging indicating that information might be missing or deductions to high; and
Almost 85% using electronic checks post return submission.
Percentage of administrations that undertake the relevant approach
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Table A.86 Verification / audit activity: Electronic compliance checks, https://data.rafit.org/regular.aspx?key=74180894 (accessed on 10 September 2024).
The type of compliance action that will be taken may vary depending on the severity of each case and as shown in Table 6.18., close to 90% of administration have (or are in the process of developing) a formal framework for compliance interventions which incorporates traditional tax audit within a framework based on classes of interventions that provide for a consistent, appropriate response to risk and taxpayer compliance behaviour.
In this respect, more than 85% of administrations reported providing a proportionate response to non-compliance, for example, applying graduated fines and penalties that reflect the degree of taxpayer co-operation and/ or compliance history. In addition, around 80% of administrations indicated that taxpayers can benefit if they make early disclosure of errors or omissions and if they fully co-operate. (See Table 6.18.)
Percentage of administrations that have the relevant approach
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Table B.25 Compliance risk management: Compliance intervention framework, https://data.rafit.org/regular.aspx?key=74180916 (accessed on 10 September 2024).
France – The optical extraction of estate declarations project
The Optical Extraction of Estate Declarations project, initiated by DGFiP, represents significant progress in enhancing the administrative processing of succession forms for tax purposes. This initiative combines advanced Optical Character Recognition (OCR) with the latest generative artificial intelligence technologies to extract and analyse financial data from these documents.
Succession forms, which detail the assets and liabilities of a deceased individual, are complex because they contain diverse information that ranges from personal details of the deceased to specific financial products that may have tax implications. The ability to accurately decipher and categorise this information is crucial for the correct assessment and collection of estate taxes.
The project’s OCR technology is tailored to navigate through the dense and often handwritten text found in succession forms. It extracts the information needed for tax calculation, addressing one of the major bottlenecks in the field of taxation: the classification and analysis of financial assets.
Generative AI further enhances this process by interpreting various writing styles and legal terminologies. It recognises and understands the specific terms that define familial relationships and the legal context of succession, facilitating the accurate mapping of inheritance chains and the determination of each heir’s tax responsibilities.
This initiative has significantly improved DGFiP’s capability to enforce tax laws and regulations more effectively. By digitising and structuring the wealth of data contained in succession forms, the risk of evasion and error has reduced, thereby promoting a more compliant and efficient tax system.
Singapore – Missing Trader Fraud buffer model
Missing Trader Fraud (MTF) poses a significant risk to public revenue. MTF is a form of VAT/Goods and Sales (GST) Tax fraud where a fraudulent supplier collects VAT/GST from customers for the sales made, but does not remit this VAT/GST to the tax authority. Meanwhile, GST-registered customers down the supply chain continue to claim refunds from the tax authority for the VAT/GST paid on their purchases.
Using artificial intelligence to tackle GST fraud, the Inland Revenue Authority of Singapore (IRAS) has developed an auto-machine learning solution, the MTF Buffer Model, to pre-emptively detect intermediary (buffer) entities engaging in MTF activity. This enables IRAS to intervene early and disrupt the supply chain before they can perpetrate MTF further. This approach challenges the notion that MTF can only be detected at the “end” of the MTF chain when exporters attempt to make the fraudulent GST refund claim.
As the Model targets intermediary or buffer entities set up to obscure the MTF supply chain, IRAS is able to identify the complicit entities and uncover the entire MTF chain in a much shorter time. IRAS has experimented with an auto-machine learning tool, DataRobot, to test and evaluate the performance of various models using different algorithms to identify one with optimal results. To date, the model has yielded encouraging results and is assessed to be three times more effective in detecting buffer entities compared to traditional approaches.
Sources: France (2024) and Singapore (2024).
Following the identification of inconsistencies or anomalies and when further engagement with the taxpayer did not address the potential issue of non-compliance or error, tax administrations may launch an audit action. The scope and depth of the audit can depend on the potential issue and the findings during the pre-audit engagement with the taxpayer. Table 6.19. shows that the vast majority of administrations have different audit actions at their disposal.
Percentage of administrations that undertake the relevant action
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Table B.28 Compliance risk management: Post-filing enforcement actions, https://data.rafit.org/regular.aspx?key=74180916 (accessed on 10 September 2024).
India – Mitigation of risk in High-Risk Refund claim
In order to reduce the number of incorrect refund claims, the data mining and intelligence information system of the Indian Department of Revenue analyses the data using High-Risk Refund (HRR) rules and shares the outcome with the Central Processing Centre (CPC), which processes the Income Tax returns. After this, the CPC puts the processing of a refund on hold until the taxpayer confirms their claim of a refund as being correct or the taxpayer revises their return. As a result, a large number of taxpayers reduced the amount of their refund claims.
However, over time various issues have arisen with this approach such as delays in the processing of returns, increased interest payments by the Government as a result of delayed refunds and interest outgo from the Government on delayed payments etc. In addition, new legislation that allowed for more deduction meant that a new approach needed to be adopted.
Under the new approach the HRR rules are applied but when a taxpayer does not respond to a request for more information, after a defined time-period, the claim is shared with Jurisdictional Assessing Officers (JAO). The JAO then assesses if a refund is released, or the case is considered for further scrutiny.
Latvia – Simplified instructions
From 2023, Latvia has simplified how it conducts its tax inspections by reducing the different types of inspections to just one – tax control. This makes it easier to work with taxpayers and increase compliance levels.
This type of inspection first checks specific discrepancies, then gives taxpayers an opportunity to explain the discrepancy and correct it. If the tax control detects uncorrected inconsistencies, the taxpayer will be informed about paying back the amount of the inconsistency and the appropriate late fee. This is known as a tax control bill.
A penalty is applied for illegal manipulations of cash registers and fines are also applied if significant compliance violations are discovered.
There is also the option to sign a voluntary tax payment agreement in the early stages of inspection, which can reduce fines by up to 85% or in some cases eliminate them altogether.
Sources: India (2024) and Latvia (2024).
Administrative sanctions for taxpayer non-disclosure
In cases of non-disclosure of information or misreporting, tax administrations typically have a range of sanctions at their disposal. Those sanctions are intended to act as a deterrent to non-compliant behaviour; to enforce compliance with a specific provision of the law (for example, the filing of a tax return); and to punish those who offend.
As shown in Table 6.20., almost all administrations apply administrative sanctions for taxpayer non-disclosure. Those that do, typically apply a common administration penalty framework that exists across the major tax types. Around 80% of administrations take into consideration the taxpayer’s culpability and a similar percentage of administration is empowered to remit or reduce penalties under certain circumstances. Furthermore, one-quarter of administrations are empowered to make public details of taxpayers subject to administrative penalties imposed for non-disclosure.
Percentage of administrations
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Table B.38 Administrative sanctions for taxpayer non-disclosure: Application and selected features, https://data.rafit.org/regular.aspx?key=74180918 (accessed on 10 September 2024).
Using the ISORA 2023 data, this first part of Chapter 6 provided a comprehensive overview of tax administrations’ approaches to compliance risk management. It examined their work on understanding and managing tax compliance risks, and how data and data science support those processes, before looking at measures taken to prevent and address non-compliance.
In relation to preventing and addressing non-compliance, it is important to note that many of the other Chapters also include information on the work tax administrations are doing to positively influence tax compliance, for example, pre-filling regimes (Chapter 4), taxpayer services (Chapter 5), or mechanisms to prevent disputes (Chapter 7). Despite the extensive data from the periodic ISORA 2023 survey, it is essential to be aware that this is only a glimpse of the work tax administrations are doing to ensure compliance.
The next part of this Chapter will provide some insights into the compliance actions that tax administrations take and how this has evolved over the past few years.
Measuring the effectiveness of tax compliance interventions is important for several reasons, including optimising resource allocation, improving cost effectiveness, and designing more effective and targeted interventions.
As can be seen in Table 6.21., around 70% of administrations measure the effectiveness of interventions that are undertaken before an audit. Approaches include the use of statistical models to monitor the effect of interventions, such as adjustment rates, additional return filings; the use of behavioural science, for example, nudging letters with control groups; and measuring the number of cases that have been moved to audit.
In addition, a significant number of administrations has put in place indicators that allow them to understand the effectiveness of audit work, mostly looking at audits that yield in a positive result (93%) followed by additional assessments raised (88%) and audit coverage (74%). Other indicators that have been reported include the number of disputes lost following an audit, positive changes in taxpayer behaviour following an audit or other intervention, and the impact on voluntary compliance of other taxpayers operating in the same sector.
The following sections look at some performance indicators regarding audits and tax crime investigations.
Percentage of administrations
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Tables B.27 Compliance risk management: Interventions after return filing, and measurement of intervention effectiveness, and B.29 Compliance risk management: Enforcement effectiveness indicators, https://data.rafit.org/regular.aspx?key=74180916 (accessed on 10 September 2024).
Audits
On average, audit adjustment rates have remained stable over the period 2018 to 2022 (see Table 6.22.). However, as shown in Figure 6.4., the rates vary significantly across the administrations covered by this report.
The importance of audits can also be seen when looking at the additional assessments raised. On average, the additional assessments raised from audits are between 3.4% and 4.4% of total revenue collections. This has been relatively flat over the years 2018 to 2020 but declined in 2021 and 2022 (see Table 6.22.). Looking at the jurisdiction level data, it can be seen that there are significant differences across the 54 administrations that were able to provide data (see Figure 6.5.).
Note: The table shows the average audit adjustment rates and additional assessments raised through audits (excluding electronic compliance checks) for those jurisdictions that were able to provide the information for the years 2018 to 2022. The number of jurisdictions for which data was available is shown in parentheses.
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Table D.46 Audit ratios: Hit rate and additional assessments raised, https://data.rafit.org/regular.aspx?key=74180903 (accessed on 10 September 2024).
Breaking this down by tax type, it shows that the ratio of additional assessments raised to tax collected is the greatest for corporate income tax (CIT). On average, CIT additional assessment raised as a percentage of CIT collected around is around 6%, and the percentage for value added tax is around 3.5%. Both percentages for those business taxes are well above the percentages for personal income tax (1.6%) and employer withholding taxes (1.0%). (See Figure 6.6.)
In many jurisdictions, the additional assessments raised through large taxpayer offices or programmes (LTO/P) make-up a significant share of the total additional assessments raised from audits (see Figure 6.7.). On average, LTO/Ps contribute around 30% of the total additional assessments raised from audits (see Table 6.11.).
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Table D.46 Audit ratios: Hit rate and additional assessments raised, https://data.rafit.org/regular.aspx?key=74180903 (accessed on 10 September 2024).
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Table D.46 Audit ratios: Hit rate and additional assessments raised, https://data.rafit.org/regular.aspx?key=74180903 (accessed on 10 September 2024).
Note: CIT data for India and Kenya has been excluded from the calculations as it would distort the average ratios.
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Tables D.47 Audit ratios: Additional assessments raised by tax type - CIT and PIT, and D.48 Audit ratios: Additional assessments raised by tax type - PAYE and VAT, https://data.rafit.org/regular.aspx?key=74180903 (accessed on 10 September 2024).
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Table D.18 Large taxpayer office / program ratios: Corporate taxpayers, additional assessments raised, and net revenue administered, https://data.rafit.org/regular.aspx?key=74180900 (accessed on 10 September 2024).
Japan – Digitalisation of inquiries to financial institutions
The NTA issues approximately six million inquiries a year to financial institutions for information on deposits and savings during the tax audit and tax collection processes.
The NTA used to make these inquiries through letters or on-site visits, but switched to using online inquiries in October 2021. This has shortened the average time to receive a response from a financial institution for a written inquiry from several weeks to 2.3 days. In addition, the elimination of the need for written or on-site correspondence has considerably reduced the administrative burden on both NTA and financial institutions. The NTA will continue its efforts to increase the number of financial institutions that can support this service and further expand the use of online inquiries.
Portugal – Digital Audit Procedure
The audit procedure in Portugal has undergone significant digital transformation aimed at transitioning to a paperless environment. These changes entail the complete digitisation of documentation associated with the tax audit procedure. By embracing digital methodologies, the efficiency of the tax and customs audit procedure has been improved, facilitating enhanced traceability and control across its entire lifecycle.
Furthermore, this has also improved the sustainability of the Portuguese Tax and Customs Authority. By reducing reliance on paper and therefore reducing the physical archive storage, this initiative has yielded substantial cost reductions while advancing environmental conservation efforts.
This project has also brought benefits for the taxpayer, as it enables:
Enhanced transparency: The audit procedure is meticulously documented and made available step-by-step within the dedicated taxpayer’s area on the Tax and Customs Authority website. This heightened transparency fosters increased trust and accountability throughout the process.
Streamlined communication: Communication channels between the Tax and Customs Authority and taxpayers have been refined to operate exclusively in the digital realm. This streamlined approach accelerates the speed in audit procedures, promoting efficiency and quickening the resolution of tax matters.
Sources: Japan (2024) and Portugal (2024).
Tax crime investigations
As mentioned in Chapter 2, slightly more than half of the tax administrations covered in this publication are involved in conducting tax crime investigations, and the ISORA survey asked them to provide information regarding the number of cases referred for prosecution.
Table 6.23. shows the total number of cases referred for prosecution during the fiscal year for the 30 administrations that have responsibility for conducting tax crime investigations and that were able to provide the data for the years 2018 to 2022. While the number of cases referred for prosecution was similar in 2018 and 2019, a significant reduction in the total number of cases referred for prosecution is visible since 2020.
This is also reflected in the jurisdiction level data, which shows that around 75% of administrations that have responsibility for conducting tax crime investigations referred a declining number of cases for prosecution over the past years (see Table A.88).
Note: Only includes data for administrations that have responsibility for tax crime investigation and were able to provide the information for the years 2018 to 2022.
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Table A.88 Tax crime investigations: Number of cases, https://data.rafit.org/regular.aspx?key=74180895 (accessed on 10 September 2024).
The core task of a tax administration is to raise revenue to fund government services and to do so in a way which does not impose unnecessary burdens on taxpayers. Minimising burdens is central to achieving the core task as they can impact the willingness or, in some cases, the ability of taxpayers to comply with their obligations. Excessive burdens can also incur significant opportunity costs for taxpayers, potentially reducing economic growth.
That tax administrations are aware of the importance of minimising compliance burdens is evident from the improvements being made to taxpayer-facing processes, such as electronic filing and payment, pre-filling regimes, new and enhanced communication channels, and an increase in self-service options. The numerous examples included in this and previous editions of the Tax Administration Series represent a small part of the many things tax administrations do in this respect.
To support ongoing improvements and better understand where burdens occur more than one-third of administrations have started evaluating taxpayer compliance burdens and most of those do it on an annual basis. In addition, Table 6.24. shows that:
Administrations measure perceptions of compliance burdens: While time and money spent to comply with tax obligations are generally considered essential indicators for measuring compliance burdens, taxpayers are also looking at the cognitive load and emotional burden. It is against this that approximately 85% of administrations that evaluate burdens are also assessing perceptions of compliance burdens.
Compliance burdens are monitored for different segments: Recognising that burdens are distinct for different taxpayer segments, more than 80% of administrations are taking a segmented approach to measuring compliance burdens.
Formal strategies are put in place: With the evaluation of compliance burdens being the first step, more than 70% of administrations that conduct those evaluations have put in place a formal strategy to reduce compliance burdens.
Percentage of administrations
Source: CIAT, IOTA, IMF, OECD, International Survey on Revenue Administration, Table B.52 Taxpayer compliance burden, https://data.rafit.org/regular.aspx?key=74180919 (accessed on 10 September 2024).
References
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