Digitalisation as a way to improve voluntary tax compliance

Digitalisation as a way to improve voluntary tax compliance

By Ksenija Cipek

12-11-2018

Authors: Ksenija Cipek and Iva Uljanić Škreblin – Ministry of Finance, Tax Administration on https://www.world.tax/

The digital economy changes our interactions, shopping and business. Digital companies grow much faster than the economy in general, a trend that will continue. Digital technologies bring numerous benefits to society and, from the point of view of taxation, create opportunities for tax administrations and provide solutions for reducing administrative burdens, facilitating co-operation among tax authorities, as well as combating tax evasion.

In the past, the mutual linkage of legislation, as the rule of law in a particular country, and the development of technology, especially in the field of information technology and artificial intelligence, has often escaped needed attention. New time for ever faster and more continuous technology development requires legislators to focus on this particularly important component. While this applies to legislation in general, it is particularly interesting and important in ​​tax legislation. Focus and attention to the development of technology and recent achievements in this area also affects the creation of executive power policies and tax policies.

In adopting and applying fiscal and monetary policy, the state’s fundamental strategic goals certainly include growing GDP, production, investments – particularly green investments – and employment, as well as stable and stimulating tax policies, price stability (inflation), economic liquidity, monetary equilibrium, currency and exchange rate stability, low interest rates, rising money supply, loyal market competition.

Tax policy supports not just fiscal components, but also wider goals: fostering equal regional development, allowed state aid especially in the area of ​​education and research and development projects and de minimis support, social aspect (exemption from tax payment / tax relief for a certain category of taxpayers), reduction of administrative burden and administrative costs of entrepreneurs, efficient, optimally organized and educated tax and customs administration etc.

Tax legislation should be structured, simple, transparent, understandable, and accessible. Such goals are not always easy to achieve, but without the effort to reach taxpayers (partners, stakeholders), the burden of tax administration will be greater than necessary. That effect will be reflected in their business, liquidity and capital. This will, in turn, affect all economic policy, and thus the quality of life of all citizens.

i. Advanced analytics

Over the last 10 years tremendous progress has been made in gathering, organizing, storing and managing global data. As a result, activities that used to require a lot of time now take just a few minutes. These transformations that are a consequence of technological advances allow tax administrations to understand, analyze, and act upon information available to them. Many tax administrations already use the wealth of information they have in order to better understand their taxpayers and occurrences that appear to improve their efficiency and operational efficiency, provide better services to taxpayers, achieve better results with existing or less resources, direct their attention to the most risky taxpayers, etc. In this way, not only does the tax administration realize cost savings, but also taxpayers express greater satisfaction with the work of the tax administration as a whole. This is because, in addition to receiving better service or assistance in meeting their tax obligations, compliant taxpayers feel no more pressure and repression due to frequent oversight. They place greater trust in tax administration because attention is focused on those who really avoid tax payments, thereby allowing healthy competition and achieving fairness in taxation. Additionally, advanced analytics allows tax administrations to more quickly and accurately identify taxpayers who use fraud or evasion schemes, which can also deter other taxpayers from using those schemes. This, in turn increases the number of taxpayers who will voluntarily meet their tax obligations.

The use of advanced analytical technology is detailed in the OECD report entitled “Advance Analytics for Better Tax Administration: Putting Data to Work”1 issued in 2016 (summarized below).

In this report, “advanced analytics” is defined as the practice of using statistical techniques for predicting and making conclusions about the causes and consequences of certain behavior. From its initial use for surveillance purposes, advanced analytics has increasingly been used in other areas, such as optimizing debt management, tax registration and tax payments, improving tax services, and better understanding the impact of tax policy change. Therefore, advanced analytics has increasingly become the cornerstone of operational and strategic decision-making in modern tax administrations.

Projects related to advanced analytics can be divided into 2 categories:

  • Predictive analytics – aims to anticipate possible problems, so that tax administrations can take appropriate action; this is usually about recognizing the occurrence, i.e. recognizing the link between the data, but not necessarily the nature of that connection; is based on the principle of trial and error in detecting the occurrence of historical data, and this is then used as the basis for prediction.
  • Prescriptive analytics – helps tax administrations to recognize the impact of their activities on the behavior of taxpayers in order for tax administrations to choose the best activities for a particular group or individual taxpayers; it is actually about recognizing the cause, which aims to determine whether our activities are causal or merely coincidental with the change in the behavior of taxpayers.

Advanced Analytics is a kind of step forward in the use of analytics in the work of tax administration since it allows for data and content analysis with sophisticated approaches such as recognizing a particular behavioral pattern, detecting externalities, experimenting design, network analysis, etc. But it does not try to reveal anything fundamentally new, it tries to carry out these tasks with a greater emphasis on the data itself, and less focus on human estimates. For example, Australia, New Zealand, Ireland, the United States, the United Kingdom, and Singapore use advanced analytics in the area of ​​taxpayers’ choice for monitoring, tax filing and payment taxation, taxpayer service, debt management and tax policy setting.

The OECD report shows that 15 of the 16 surveyed countries use advanced tax auditinganalytics (for example, VAT refunds by analyzing a large set of data, analyzing social networks on the Internet, etc., defining mistakes or fraud with income tax on wages, especially in the use of relief, etc.). The purpose of these models is actually to be found on the basis of past data, that is, cases where a fraud or error of a certain common occurrence was discovered and incorporated into a system of risk recognition in future cases, so that a tax administration could anticipate these frauds or errors. However, this type of model will not recognize new or previously unknown types of risk. It is therefore necessary to apply non-standardized models that focus on the data and certain anomalies, rather than learning about the results of specific cases. Such models apply the Australia “nearest neighbors” model, created to find errors or inaccurate data on income tax deductions, or the Ireland “income-consumption” model that seeks out unreported income. Both are based on the same principle: Comparing the tax returns of similar taxpayers. Both models are very useful, and which model a tax administration chooses will actually depend on the goal to be achieved: if it wants to eliminate interventions that will not result in new obligations, a supervised model will be applied, while if it wants to identify new types of fraud or risk which have not been disclosed so far, it will use a non-standardized model.

When it comes to tax compliance with regard to data logging and tax payments, the OECD survey shows that predictive and prescriptive analytics are used to change the behavior of taxpayers. Thus, predictive analytics is used to identify taxpayers who are unlikely to fulfill their obligations and are prescriptive to determine the best way to communicate with such taxpayers. The research has shown that different countries use different techniques:

  • experimental design (for example, the Norwegian Tax Administration has engaged experts in the field of economic behavior research to test different ways of communication with the aim of improving the fulfillment of tax obligations related to foreign income),
  • combining predictive modeling and experimentation (Australia, Canada, Norway, and the United Kingdom use risk modeling and controlled experimentation to identify cases that are unlikely to lead to the fulfillment of tax obligations, and what interventions are needed to prevent it, thus focusing on the most risky taxpayers to create messages targeted precisely at those taxpayers, thus reducing the cost of communication).

For debt management, many tax administrations use the same advanced analytics as the tax compliance related to data logging and payment of taxes. For example, Ireland, Finland, Singapore, and Sweden have built-in mechanisms that predict the likelihood of illiquidity or other problems with paying taxpayers in order to respond in a timely manner. Similarly, Australia and Norway have real-time debt management systems which, depending on the case, apply different payment arrangements in relation to the taxpayer’s ability to pay. The Australian Tax Administration also uses predictive models to send text messages to taxpayers who have established payment risk. Only certain tax administrations use the technique of “uplift modeling” to determine which interventions will achieve the greatest results. Specifically, it is possible that no intervention will occur on certain groups of taxpayers, and there are others where tax obligations will be met without intervention. In order to improve the tax administration’s impact and reduce intervention costs, “uplift modeling” combines a controlled experiment to detect the expected impact of an intervention and predictive modeling techniques to identify which taxpayers will be most responsive to these interventions. This is mostly used in the private sector, but an OECD report suggests further analysis of the use of this method.

Many tax administrations are increasingly using advanced analytics in the taxpayer service segment, such as taxpayer development, decision-making about information design, identifying opportunities for providing different “self-service” services, etc. Generally advanced analytics is increasingly used to encourage greater use of digital communication channels with taxpayers, as it is expected to create new opportunities for further analysis, as tracking and experimentation is simpler and cheaper in the digital environment. For example, Singapore began using the E-mail Analysis Technique that Taxpayers sent to tax authorities in order to reduce the number of queries, prejudicing inquiries and improving taxpayer services, especially when it was important to emphasize important changes or identify trends that would request tax administration response. In one such project, the Tax Administration managed to push the right campaign at the right time, provide more guidance on its website, and proactively update information for taxpayers, thus reducing the need for additional tax administration contact after introducing changes to the tax system. Similar techniques are used by tax administrations in Canada, Ireland, New Zealand, Norway, and the United Kingdom to improve communication channels with taxpayers.

Advanced analytics is also used in the decision-making process on tax administration strategy and policy, most commonly in measuring tax divisions and estimating and predicting the effects of changes in tax policy. For example, China, Finland, the United Kingdom, and the United States use advanced analytics for estimating tax breaks based on data collected in the tax audit process, while Singapore uses visual analytics and simulation methods to investigate the likelihood of tax policy changes. The use of data visualization has allowed legislators to quickly identify occurrences, trends, and anomalies, thus improving the efficiency of decision-making and tax policy audits. China also uses advanced analytics to assess the impact of major tax reforms based on the simulation model.

In addition to the cases mentioned above, which are mainly related to the relationship between tax administration and taxpayers, advanced analytics can be used within the wider organization, organizational structure and organizational culture of wider tax administration.

Advanced analytics are just a tool that can help tax administrations get faster and more objective, and devote less human resources to achieve desired results – predictions and estimates, or analysis and identification of certain occurrences, trends, anomalies, and the like. However, in order for the results to be good it is necessary to have good inputs on which the analyses will be based, and also good management that will focus great attention on successful project management, prioritization, and evaluation. Furthermore, it is necessary to take care of capacity development with existing officers, or hire new ones that will have the capabilities required for a successful understanding and mastering of all the challenges that advanced analytics carry with them (for example, where advanced analytics could be used efficiently and where, where there are technical constraints, where there are limitations of high-quality data sources, where the project will require too much administrative burden for taxpayers, etc.). It is also very important to keep track of and manage the changes in the workflows that advanced analytics carry with them. This is primarily about employees who will have to use the results of advanced analytics in their daily work in the face of natural resistance to change.

For example, the Netherlands Tax Administration has established a data and analytics team whose main goal is to improve the existing system and working methods in organizing data and advanced analytics. The analytical outputs created by this team have a great impact on the daily work of other tax administration officials. To ensure that these products are used properly, they have created a change management team, consisting mainly of psychologists and other experts in the field of organizational behavior. This team provides a link between analytical and organizational understanding and helps in implementing new practices based on analytical recommendations and products. Many of the proposed changes lead to standardization of the process and the officials who will do this may have a feeling that they can no longer decide freely, causing a natural resistance to adopting the new methods. The approach used in the Netherlands consists of the introduction of a new system by simultaneously changing the context of work and changing the entire work process. It also involves the officials themselves by seeking their opinion of what they want the new work process to look like (which is necessary to improve the efficiency of work and what they need to work more efficiently and effectively). The greatest advantage of this approach is that it facilitated the transition from old business processes to new ones, ensuring that predictive modeling and other analytical initiatives achieve practical impact on employee behavior and the results of taxpayers.

ii. Technological tools for combating tax evasion and tax fraud

The increase in voluntary tax compliance as their antipode has a reduction in tax evasion and tax fraud. Although the European Union has been focused for several years on fighting against aggressive tax planning linked to cross-border business (mainly by large multinationals), many countries – particularly small countries like Croatia – face a special form of tax evasion: failing to accurately report revenue, and overstating costs and expenses through fraudulent invoices. These challenges are more pronounced in economies that are highly dependent on cash transactions, as well as in economies with well-developed digital platforms that allow commerce to occur online through businesses that are not registered in the country where profits are generated, and countries making wide use of barter or the sharing economy.

As discussed in the previous section, advanced analytics can have the effect of predicting and preventing risky behavior only if we have a good source of data and enough information on taxpayers. The first step in this is actually the use of cost-efficient technology tools that have become increasingly sophisticated and increasingly accessible not only to developed countries but also to developing countries. Even storage of large numbers of data is no longer a problem, as data storage costs have become cheaper. With the help of advanced analytics, neither the processing nor the analysis of this data is excessively expensive.

Croatia is one of the countries that began several years ago (in 2013, to be precise) to use the technological tools it was trying to introduce in the retail segment, i.e. cash paid transactions. This is, of course, a project on the fiscalization of cash payments. But Croatia is neither the only nor the first country to use such a way of tracking transactions between taxpayers in real time. For example, in 2006, Brazil introduced a pilot project to monitor B2B e-invoices, which is very similar to the Croatian fiscalization system. It was introduced to reduce cross-border B2B fraud and is still used today. Portugal has introduced Real-Time Transaction tracking for all VAT payers in 2015, and Russia plans to introduce a similar system this year.

One aspect of electronic tracking of invoices is Italy’s announcement that it will mandate the use of e-invoices for all taxpayers (except for those for which a special procedure for small taxpayers is prescribed and in this regard requested the EU Council approval for the derogation from Articles 218 and 232 of the VAT Directive last year, in the period from 1 July 2018 to 31 December 2021). Invoices would be exchanged through the System of Interchange (SoI) system managed by the Italian revenue agency, so that the tax administration would get information in real time on all issued invoices and better monitor the compliance between reported and paid VAT. Italy considers that introducing a general e-bill obligation has the advantage of combating tax evasion and evasion, as well as simplifying the collection of taxes. It also believes that tax compliance will improve and that it will realize real benefits from increased timeliness and effectiveness of control against tax fraud and tax evasion. Specifically, Italy claims that the current tax administration needs about 18 months to become aware of the existence of a “missing trader,” while the immediate availability of an e-bill would reduce that interval to just three months, enabling Italy to disrupt those fraudulent chains much faster. This would also stimulate digitalisation and administrative simplification2.

In 2017, the OECD issued a report titled “Technology tools to tackle tax evasion and tax fraud”3 based on 21 countries’ experiences in using cost-effective technological solutions for the prevention and detection of tax evasion and tax fraud, particularly in the field of cash transaction and sharing economics. The report emphasizes the key successes in using these technologies, identifying not only countries experiencing a significant increase in tax revenues, but also discussing the consequences of the overall increase in taxpayer compliance. Avoiding to report all financial transactions is no longer related to the simple non-registration of an individual cash transaction, but taxpayers are increasingly using sophisticated methods involving technological solutions, such as using cashiers in demo mode or deleting a transaction after the invoice has already been issued. The research has shown that taxpayers mostly use two tools:

  • “phantomware” – includes software installation as part of the sales cash register, which allows one to change the previously recorded data. The program is accessible only through a hidden menu that allows the business owner to secretly manipulate sales documents after the transaction has occurred, and
  • “zappers” – an external device or external program that is available online that can be linked to the cash register and allows manipulation of transaction records, performing a similar function as phantomware.

Both tools allow the user to delete individual sales records thus reducing total reported sales. Because of their hidden nature, it’s hard to get rid of these tools, particularly because the cash registers seem to work normally. These models are specific in the application of so-called “Fiscal pits” or electronic fiscal cash registers, which individual countries use and at the end of the day supply sales tax information. But when data is sent to the tax authorities in real-time, these tools do not work.

These scams, described in more detail in the OECD report, work by issuing false invoices. The way to counter this type of fraud is through an e-invoice, especially if this invoice has to be registered or otherwise submitted to the tax authorities. Italy has proposed adopting an e-invoice, which is already being implemented in Argentina, Bolivia, Brazil, Colombia, Costa Rica, Ecuador, Guatemala, China, Peru, Uruguay, and Mexico. Implementation in those countries has effectively brought 4.2 million micro-enterprises out of the gray economy and into the formal economy. The use of an e-invoice also has advantages for the company using it (e.g. for bookkeeping), as well as in improving the accuracy of its tax reports, and reducing the administrative costs and burdens on taxpayers.

The same technological solutions that have been mentioned above can be applied to address the challenges related to cash transactions and tax evasion. Some countries also use legislative solutions, analytical tools and incentives for non-cash payments. Argentina, for example, uses an incentive where buyers who buy real estate or services through a credit card or bank account may qualify for a partial VAT refund. In Austria, cash payments for construction services (including labor) exceeding €500 are no longer tax deductible. To be qualify for deduction, those expenses (including wages) must be paid by bank account. In Finland, tax authorities can access and monitor cash withdrawals from ATMs an on-line connection, which can be used as a risk indicator or in combination with other information during the investigation. France and Greece limit cash payments over €1,000 and €1,500, respectively. In Sweden, it has been agreed that the company refuses to receive cash payments and is already using it in some restaurants, public transport and hotels, and the use of cash is declining and it is estimated that about 80% of transactions are paid electronically.

The report concludes that tax administrations should continue to cooperate with taxpayers, the private sector, and other tax administrations to keep up with new risks and share gains from introducing new solutions. Technology is a rapidly changing area and taxpayers who are prone to commit fraud will constantly find new ways to commit fraud, thus requiring new tax administration responses. Tax administrations should therefore continue to share their experience and knowledge in the use of new technologies to curb tax evasion and tax fraud, as well as provide feedback on tax reforms that have led to improvements in meeting tax obligations.

iii. New tools for new business models

One of the major changes in the economy of digitalisation is the rapid growth of multi-faceted online platforms, which often facilitate transactions between individual sellers of goods and services and peer-to-peer transactions (P2P), which take place outside traditional business structures. In particular, online platforms facilitate growth and development of the “sharing economy” (sometimes referred to as the “collaborative economy” or “gig” economics). Although the terms “sharing economy” and “collaborative economy” are often used interchageably, when it comes to business models that reflect the existence or absence of taxable receipts, these two concepts may differ as follows:

  • “sharing economy” involves common spending, i.e. sharing of costs or the joint use of an individual’s property or services, without any additional income or revenue being generated for those who offer it. This is for example the portal “BlaBlaCar” that connects individuals traveling to the same general area and sharing the cost of the route, but the maximum cost that one can offer for transportation with his or her personal car is limited so that no surplus revenue is generated. An example of this kind of collaboration is the portal “homeexchange” that connects individuals to different locations around the world and allows them to exchange vacation homes for free. This kind of economy does not actually create any added value in terms of increasing material benefits for users, and for now, there may be no incentive for tax administrations to introduce taxation;
  • “collaborative economy” or co-operation economics involves online business through social online channels, such as privately renting property via platforms such as Airbnb or Booking, online transportation services such as Uber, and professional sales via online platforms such as eBay. In this business model, which merges supply and demand, the users of this portal that provide their services receive a material benefit, thus creating a hightened interest of the tax authorities to tax user receipts;

The “Gig” economy refers to a labor market characterized by the prevalence of short-term and often non-standard contracts or self-employment, unlike permanent jobs and standard labor contracts. This is an environment in which temporary jobs are common, and organizations engage independent, self-employed workers for short-term assignments. Examples include occasional household cleaning services, etc. In this digital age, the workforce is becoming more mobile, and work can be done more and more from anywhere, reducing the connection between the job and location where it is performed. This means freelancers can choose between temporary jobs and projects across the globe, while employers can choose the best individuals for specific projects from a larger “worker pool” than available in just one area.

The economy of cooperation is a relatively new term. While it does not present the same risks associated with cash transactions, some tax administrations have already begun to analyze the risks of tax evasion and tax fraud associated with this type of economy. PwC estimated that the divisional economy now generates $15 billion of revenue worldwide, and could increase to $335 billion by 2025.

Some tax administrations have started activities in this area to reduce tax evasion through technological antitrust and regulatory and legislative frameworks. International co-operation may be of help in this area, especially because online platforms are located outside the country where its users live. For example, Argentina has introduced a special VAT registration system, which it applies to online portals for the sale of new personal property and online portals where the contracting of services is agreed or performed electronically. The online portal operator is required to act as a VAT agent for transactions conducted through its portal. Australia uses significant third party data obtained through access to information collected for the purpose of combating money laundering and terrorist financing. They followed the movement of funds for drivers and landlords paid from overcrowded to a local bank and asked for information from these banks to identify unannounced business activities such as those carried out by Uber drivers. They also collaborate with platforms – particularly, particular Uber and Airbnb – to gain customer information. Austria uses Internet monitoring by means of various tools (e.g. “web harvesting” and “web day extraction”), and uses it for measures that it seeks to increase tax compliance, for example by sending summonsed calls and information campaigns. Belgium uses “Internet scraping,” requiring all digital data to be subject to “data mining,” and applies other analytical tools such as a “Forensic Toolkit” to collect data. Japan collects a large amount of data from the Internet, saves it all in a database and compares it to the data in its tax system for each taxpayer, making it easier to visualize the risks for each taxpayer. The United Kingdom uses a program called “COSAIN,” which automates the process of comparing and filtering data from social networks and sites, making it easier to perceive trends in a particular geographic area or specific business sector.

The advantage of digitalisation, especially in the P2P transaction area, is that even before digitalisation of any kind of transaction, these were not new jobs created by digitalisation or these new business models, but before the bid and demand were mostly merged through oral recommendation, familiarity, physical market or social advertising or networking. In most cases, in fact, it took place in the form of a gray economy, which made it difficult for tax authorities to discover, monitor and monitor. Digitalisation has created an advantage for tax administrations, namely making customer and server data are available online, creating a new potential source of information for tax administrations to monitor, monitor and estimate taxable bases that were previously unregistered.

Encouraging economic activity and ensuring appropriate tax treatment, however, require tax administrations to take into account the impact of administrative burdens on online platform users. This has already been recognized in many countries and simplified tax regimes or special tax incentives for micro, small and medium-sized enterprises and for individuals who are not primarily engaged in the main business are being implemented in order to move them out of the gray economy and encourage voluntary tax compliance.

For example, Denmark has recently announced a growth strategy based on a collaboration economy, which contains 22 initiatives. Among other things, that initiative provides a a higher personal allowance for renters of cars, car and ships if a third party such as an online platform reports their total income on that basis to tax authorities. The strategy also includes the development of digital solutions for income-based income based on activities in the field of cooperation economics.

Italy has introduced an optional tax regime for short-term lease payments, allowing the taxpayer to opt for a substitute tax (instead of income tax) of 21% on gross rental income. The new law applies to lease agreements that do not exceed 30 days, on contracts concluded online, as well as on contracts traditionally concluded.

The United Kingdom has introduced two separate annual tax breaks for individuals, each of £1,000.00, for income from trade or property, to simplify the tax system and support the development of the digital economy and the sharing economy. If these facilities cover all relevant individual incomes (before costs), then the taxpayer will no longer have to apply for or pay a tax on that income. Those with higher incomes will have an opportunity to calculate taxable income to make a receipt for that relief rather than for the actual tax-deductible costs.

It is necessary to assure, however, that applying the same rules for all does not reduce the competitiveness of those who still conduct business in traditional ways, compared to those who do business digitally (such as between taxi drivers and Uber drivers). Therefore, it may be helpful to adopt provisional measures to attract taxpayers who are just starting their business in the economy of sharing or the gig economy, considering that it may be new taxpayers who are not familiar with the tax regime but may not, in the long term, become competitive with traditional business that provide the same or similar services.

Furthermore, for a “gig” economy, for example, in contrast to standard labor contracts, income reporting will depend on the taxpayer itself (especially the platform does not have a head office in the country where the services are provided). This presents another challenge for tax administration because it will be harder to get information on who earns income and in what amount. In its Interim Report on Digitalisation Issues, released on March 16, 2018, the OECD proposes that tax administrations emphasize providing better education for those taxpayers by issuing timely instructions on appropriate tax treatment and reporting obligations in relation to those new business models. Improving the education of taxpayers who provide goods and services through a P2P platform can have an important impact on the effective taxation of activities that enable online platforms. France, for example, requires P2P platforms to provide information on the obligation to pay taxes and contributions to users of those platforms. That obligation is deemed to be met if the message sent by the platform to its customers provides accurate, unambiguous, and transparent information of those obligations for each transaction, and incorporates in a clear way hypertext links to the tax administration website. In addition, platforms must send their customers an annual certificate (before January 31) that includes the gross amount of receipts earned on transactions executed through that platform.

What could also be helpful in this area is for tax administration receives data from the platform itself. This could, on the one hand, increase the voluntary reporting of receipts (since taxpayers would know that the tax administration would receive that data later) and, on the other hand,t enable tax administrations to carry out the taxation procedure themselves and automatically fill in the tax returns, sending the taxpayers just a bill for the tax due. Also, in the platform where the payment is made or where the payment platform is in the billing service, the obligation to calculate and pay a deduction tax for the platform itself can also be applied. However, such measures would not be so effective when the platforms are located in another jurisdiction, where the tax administration must rely on the exchange of information with the competent tax authority in that jurisdiction (often a time-consuming process).

Examples of good practice can be found in Estonia, where two well-known platforms for transport services provide data directly to the tax authority after approval from the user platform itself before the tax filing period. Based on these data, the Tax Administration calculates the tax, and submits the data to taxpayers who must verify and confirm them. The entire process is conducted electronically. In Mexico, an obligation to issue an e-invoice to all clients in the area of ​​transportation is introduced, and each driver must sign up for online service for that service, request a digital certificate for digital signing of the invoice, and then they can use their own platform for creating and sending the invoices to clients and at the same time to tax administration. Ecuador uses a similar system.

Through the OECD Tax Administration Forum, 50 countries recently agreed to cooperate on a project that should be implemented in 2018 and includes 4 components:

  • develop a common understanding of different platform types, level of challenge and opportunity, location and availability of data from the platform itself,
  • understand the approaches already implemented by some tax administrations to increase tax compliance among platform users, including through education, legal change and platform collaboration,
  • consider the scope of information that tax administrations would need to properly determine the amount of income that the platform users would make and taxed,
  • consult with some of the larger cross-border platform agreements regarding a common set of information that these platforms could provide, with appropriate legal solutions, to all tax administrations in the jurisdiction of their users.

If this global agreement is reached, as has been achieved around global financial reporting standards, this would greatly contribute to increasing tax compliance and reducing tax evasion in the digital economy.


  1. https://read.oecd-ilibrary.org/taxation/advanced-analytics-for-better-tax-administration_9789264256453-en#page13
  2. Reference: “Proposal for a Council Implementing Decision authorising the Italian Republic to introduce a special measure derogating from Articles 218 and 232 of Directive 2006/112/EC on the common system of value added tax”, https://ec.europa.eu/transparency/regdoc/rep/1/2018/EN/COM-2018-55-F1-EN-MAIN-PART-1.PDF
  3. OECD (2017), Technology Tools to Tackle Tax Evasion and Tax Fraud, OECD Publishing, Paris, http://www.oecd.org/tax/crime/technology-tools-to-tackle-tax-evasion-and-tax-fraud.pdf

Source picture : Pixabay Manuchi

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