The collection of outstanding returns and payments is important for maintaining high levels of voluntary compliance and citizen’s confidence in the overall tax system. This chapter comments on tax administration performance in managing the collection of outstanding debt, and describes the features of a modern tax debt collection function. It goes on to provide examples of approaches applied by administrations to prevent debt being incurred.
Tax Administration 2022
Comparative Information on OECD and other Advanced and Emerging Economies
Tax Administration
7. Collection
Abstract
Introduction
The collection function involves engaging with, and potentially taking enforcement action against those who do not file a return on time, and/or do not make a payment when it is due. Even with the growth in pre-filled or no return approaches over past years (see Chapter 4), the filing of a tax return or declaration still remains the principal means by which a taxpayer’s liability is established in the majority of jurisdictions participating in this publication. Although 2020 on-time filing rates averaged between 78% and 88%, around 100 million returns were not filed on time that year (see Chapter 4). It is important therefore that administrations continue to focus efforts on improving the timely collection of late and outstanding returns.
Looking at the collection of late payments, all but one administration participating in the survey report staff resources being devoted to taking action to secure the payment of overdue tax payments (the Chilean tax administration reported not being responsible for debt collection; see Table A.8). Information provided by administrations in ISORA 2021, attributes around 11% of total staff numbers to the collection function (see Table D.4).
The legislative framework provides tax officials with powers that enable them to undertake certain actions in relation to the management of debt, the collection of amounts overdue and the enforcement actions that can be taken against delinquent debtors. The 2019 edition in this series had a section summarising the availability of such management, collection and enforcement powers and their usage by tax administrations (OECD, 2019[1]). Since then the ISORA survey did not take a closer look at this topic. However, it is fair to assume that the availability and usage of such powers has not significantly changed.
This chapter:
Takes a brief look at the features of a modern tax debt collection function and the elements of a successful tax debt management strategy;
Comments on tax administration performance in managing the collection of outstanding debt;
Provides examples of preventive approaches to debt being incurred; and
Examines the immediate impact of the COVID-19 pandemic on debt levels, which is likely to be a trend touching future editions of this series.
Features of a debt collection function
To maintain high levels of voluntary compliance and confidence in the tax system, administrations must ensure that their debt collection approaches are both “fit for purpose” and meet taxpayer’s expectations of how the system will be administered. This means not only taking firm action against taxpayers that knowingly do not comply, but also using more customer service style approaches where taxpayers want to meet their obligations but for understandable reasons, such as short-term cash-flow issues, are not able to do so. Increasingly, tax administrations are taking an end-to-end or systems view of their processes and researching the reasons why returns may not been filed or payments made. They are also using information about the taxpayer’s previous history, to identify patterns and/or anomalies.
The 2014 report Working Smarter in Tax Debt Management (OECD, 2014[2]) provided an overview of the modern tax debt collection function, describing the essential features as:
Advanced analytics – that make it possible to use all the information tax administrations have about taxpayers to accurately target debtors with the right intervention at the right time.
Treatment strategies – the collection function needs a range of interventions, from those designed to minimise the risk of people becoming indebted, to support taxpayers to make payments and to take appropriate enforcement measures where appropriate.
Outbound call centres – which make it possible to efficiently pursue a large number of debts.
Organisation – debt collection is a specialist function and is usually organised as such. The right performance measures and a continuous improvement approach help drive desired outcomes.
Cross border debts – the proper and timely use of international assistance is crucial, particularly the “Assistance in Collection Articles” in agreements between jurisdictions.
The 2019 report Successful Tax Debt Management: Measuring Maturity and Supporting Change (OECD, 2019[3]) provides further insights into the elements of a successful tax debt management strategy, setting out four strategic principles that tax administrations may wish to consider when setting their strategy for tax debt management. These principles focus on the timing of interventions in the tax debt cycle, from consideration of measures to prevent tax debt arising in the first place, via early and continuous engagement with taxpayers before enforcement measures, to effective and proportionate enforcement and realistic write-off strategies. The underlying premise for these principles is that focusing on tackling debt early, and ideally before it has arisen, is the best means to minimise outstanding tax debt. The report also contains an overview of a Tax Debt Management Maturity Model and a compendium of successful tax debt management initiatives.
Box 7.1. Examples - Tools to advance debt management
Argentina – Risk profiling
Argentina has created a risk profile system called SIPER, which performs a monthly automatic categorization of the entire Taxpayer Register of the Federal Administration of Public Revenue (AFIP). SIPER identifies non-compliant taxpayers, and risk categories are allocated from low risk to high risk, based upon different types of controls (called deviations) that identify formal, material and judicial breaches registered in AFIP’s systems.
The system notifies taxpayers of the category they were allocated, including the reasons, and gives taxpayers the chance to correct any errors using different data. One of the most important uses of SIPER is identifying the category “Distinctive non-compliance management”, which contains 86% of debt. This allows for focused administrative collection measures on taxpayers with the highest tax risk, and the beginning of judicial proceedings in a shorter time.
The aim of SIPER is to foster the idea in taxpayers that compliance is the best option, which brings more benefits in the long term as non-compliance entails a higher cost.
Canada – Tailoring services
The Canada Revenue Agency (CRA) risk assessment process determines the allocation of accounts at the appropriate level based on a risk score. This initiative ensures that accounts are directed to specific workloads and processed according to associated strategies. The CRA has already developed strategies that segment collection accounts with specific stakeholder interactions, such as insolvency-related files. There are additional opportunities to segment based on debtor and debt characteristics. The CRA will segment portions of their inventories to group accounts and develop expertise among the collectors in how to best resolve these accounts.
Segmenting accounts based on common characteristics will allow for a more targeted approach to the collection of these debts. For instance, by segmenting deceased accounts, which are a specialty workload and of a sensitive nature, they will be handled in a different manner where the CRA will assist the trustees of the estate to resolve the debt and obtain a clearance certificate. The ultimate outcome for segmenting accounts is to have them assigned to the right individual at the right time, avoiding inventory backlogs with accounts that could be resolved at an earlier stage of the collections continuum.
United States - Optimising Collection Delivery and Selection
In 2021, the Internal Revenue Service’s (IRS) Collection organisation revamped its process for determining the best work stream for a particular case by expanding the use of predictive models into routing decisions. The objective was to optimise assignment of Collection inventory to treatment streams (within operational constraints), allocate productive inventory more effectively, and identify unproductive inventory more quickly.
IRS Collection has a suite of predictive models that integrates behavioural insights with the vast amount of available tax administrative data, to better anticipate the complexity and the level of effort that will be required to resolve a case. The models were built using logistic regression. They help predict the likelihood a taxpayer will resolve their liabilities by payment or payment agreements, the risk of future non-compliance, and the expected amount of payments. As the models are utilised, their performance is continually evaluated, and refinements can be made to improve their accuracy and functionality over time.
Case routing uses several predictive models to optimise three different factors: future compliance, dollars collected and case resolution, and having several factors included in the routing decision provides flexibility in weighting factors based on strategic priorities and inventory levels. As the use of predictive models expands, this provides a foundation upon which future analytical capabilities can be built.
Sources: Argentina (2022), Canada (2022) and the United States (2022).
Performance in collecting outstanding debt
The total amount of outstanding arrears at fiscal year-end remains very large, in the region of EUR 2.3 trillion. For survey and comparative analysis purposes, “total arrears at year-end” is defined as the total amount of tax debt and debt on other revenue for which the tax administration is responsible that is overdue for payment at the end of the fiscal year. This includes any interest and penalties. The term also includes arrears whose collection has been deferred (for example, as a result of payment arrangements).
The total amount of “Collectable arrears” at fiscal year-end was around EUR 900 billion. Collectable arrears is defined as the total arrears figure less any disputed amounts, or amounts that are not legally recoverable. It also includes arrears which are unable to be collected, but where write-off action has not yet occurred.
As a result, and despite efforts to make data comparable, care needs to be taken when comparing specific data points as the administration of taxation systems and administrative practices differ between jurisdictions. Care also needs to be taken because of the impact of the COVID-19 pandemic, which is likely impacting on this year’s figures. This is because many governments took action to support individuals and businesses as part of the pandemic by extending payment terms, or suspending collection of outstanding debt. This may well be a major factor in the increase in collectable arrears between 2019 and 2020 may be a result of this. (CIAT/IOTA/OECD, 2020[4]). Future editions of this series will likely continue to reflect the impact of these actions as tax administrations slowly return to pre-pandemic activities.
In 2020, the average ratio for total year-end arrears to net revenue collected was 37% (see Table D.19). As in past years, it remains heavily influenced by the very large ratios of a small number of jurisdictions that show ratios above 90%. If these jurisdictions are removed, the average reduces to around 15% of net revenue (see Figures 7.1 and 7.2 as well as Table D.19).
Table 7.1. Average arrears ratios
Note: The table shows average arrears ratios for those jurisdictions that were able to provide the information for the years 2018, 2019 and 2020. The number of jurisdictions for which data was available is shown in parenthesis. Data for Bulgaria was excluded from the calculation of the average for the ‘total year-end arrears as a percentage of net revenue collected’ as its data for the three years was not comparable (see Table A.31).
Source: Table D.19 Arrears: Closing stock, collectible arrears, and arrears relating to state owned enterprises.
When comparing 2020 with 2019 a significant increase in total year-end arrears to net revenue collected is visible. While there was almost no change between 2019 and 2018, during 2020 – the year of the pandemic – the ratio increased on average by more than 20 percent (see Table 7.1). Further, the jurisdiction level data shows that in 2020 the ‘total arrears to net revenue collected’ ratio increased in around 85% of jurisdictions (see Table D.19).
Looking at collectable tax arrears, the 2020 data for 41 jurisdictions shows that on average 55% of the total arrears are considered collectable. That is an increase of 5% compared to 2019 (see Table 7.1). However, Figure 7.3 illustrates well the differences between jurisdictions: in some jurisdictions almost all arrears are considered collectable, while in others almost all arrears are considered not collectable.
Figure 7.1. Total year-end arrears as a percent of total net revenue, 2020
Source: Table D.19 Arrears: Closing stock, collectable arrears, and arrears relating to state owned enterprises.
Figure 7.2. Total year-end arrears as a percent of total net revenue, 2020
Source: Table D.19 Arrears: Closing stock, collectable arrears, and arrears relating to state owned enterprises.
Figure 7.3. Total year-end collectable arrears as percentage of total year-end arrears, 2020
Source: Table D.19 Arrears: Closing stock, collectable arrears, and arrears relating to state owned enterprises.
Figure 7.4. Movement of total arrears between 2019 and 2020
Note: The figure does not include data for Bulgaria as its data for the years 2019 and 2020 was not comparable (see Table A.31).
Source: Table D.21 Arrears: Year-on-year Change.
Figure 7.4 show the change of total year-end arrears between 2019 and 2020. In absolute numbers, the total year-end arrears increased in 39 out of 51 jurisdictions that were able to provide the information.
In looking at the amount of arrears for the main tax types (see Table 7.2), it seems that individuals are more likely to pay on time than businesses. The average ratio of corporate income tax (CIT) arrears to CIT net revenue collected is around 35% and the ratio for value added taxes (VAT) is around 30%. At the same time, the ratio for personal income tax (PIT) is much lower at around 16%.
At around 7%, the ratio is the lowest for employer withholding taxes (WHT). However, this is expected, as employers are responsible for forwarding those taxes to the administration on behalf of their employees and have no right over the amounts.
Table 7.2. Average ratio of year-end arrears to net revenue collected by tax type
Note: The table shows the average ratios for jurisdictions that were able to provide the information for the years 2018, 2019 and 2020. The number of jurisdictions for which data was available is shown in parentheses. Data for Bulgaria was excluded from the calculation of the average for the total year-end arrears as a percentage of net revenue collected as its data for the three years was not comparable (see Table A.31). Further, because they would distort the averages, data for Greece was excluded in the calculation of the average for CIT and data for Malta was excluded in the calculation of the average for VAT.
Source: Table D.20 Arrears in relation to collection by tax type.
Preventive approaches
The range of actions undertaken by tax administrations to prevent debt from arising and to collect outstanding arrears continues to evolve. Advances in predictive modelling and experimental techniques as reported in the OECD report Advanced Analytics for Better Tax Administration (OECD, 2016[5]) and in the compendium of successful tax debt management practices contained in the OECD report Successful Tax Debt Management: Measuring Maturity and Supporting Change (OECD, 2019[3]) are helping many administrations better match interventions with taxpayer specific risk. The approaches used fall into one of the following categories:
Predictive analytics, which tries to understand the likelihood of certain outcomes and, as regards debt collection, includes modelling the risk that an individual or company will fail to pay as well as models that attempt to assess the likelihood of insolvency or other payment problems.
Prescriptive analytics, which is about predicting the likely impact of actions on taxpayer behaviour, so that tax administrations can select the right course of action for any chosen taxpayer or group of taxpayers. (OECD, 2016[5])
Many administrations are blending both practices and have trialled a variety of approaches aimed at changing “taxpayer behaviour.” As pointed out in Chapter 5, close to 70% of administrations are using behavioural insight methodologies or techniques. These practices have the potential to transform the approach to tax debt as administrations move away from the ‘one-size-fits-all’ approaches (where it is cost-effective to do so) and instead try to identify:
Which cases should be subject to an intervention;
When to intervene (for example, even before a return or payment might be due); and
Which type of action would achieve the best cost-benefit outcome.
Box 7.2 illustrates the approaches taken by some administrations.
Box 7.2. Examples – targeting interventions
Colombia - Portfolio prioritisation model
Machine learning has been used intensively in the banking sector for some time to estimate the prioritization rating for debt recovery, with models being used to estimate the probability of debt collection. The Colombia Tax and Customs Administration (DIAN) decided to use these models with the aim of increasing the amount of the recovered debt and doing so in the shortest possible time.
The methodology had two stages. In the first stage, a survey answered by experts within DIAN was conducted to determine the importance of eight factors in debt collection. From this survey, it was possible to establish the importance of each of these factors when prioritizing the portfolio. For the second stage, different algorithms were included in the model. The purpose of this model was to estimate the probability that a taxpayer pays the amount due. In terms of debt collection, according to preliminary estimates for the period February to July 2021, the model has helped in the recovery of approximately COP 3 billion.
United States - Notice redesign
The IRS has applied behavioural insights to enhance a number of collection notices to make them easier for taxpayers to comprehend and act upon, thereby improving the taxpayer experience and reducing the instances where the debt must be escalated to higher-cost treatments. Many of the redesigned notices include a quick response code which taxpayers can scan with their cell phone to be taken to pages on the IRS.gov website with additional resources and information.
Before being placed into production, notices are tested to determine their effectiveness in improving compliance outcomes. An efficient and repeatable process was used to develop and test the effectiveness of redesigned notices using randomized control trials. The IRS completed a series of pilot tests to measure the benefit of redesigning collection notices and to identify the most effective version of each notice. It also tested various models of the notices to capture taxpayer reaction to different behavioural nudges.
Results from the completed tests showed that redesigned collection notices improved payment compliance, increased use of self-service tools, and reduced costs to IRS, pointing to the benefits of systemic implementation. The IRS estimate that these redesigned notices may increase annual collections by as much as USD 800 million. The redesign promotes the availability and ease-of-use of IRS online services, increasing awareness of alternatives to lengthy wait times on the phone and facilitating taxpayers’ ability to engage with IRS through their preferred channel.
Sources: Colombia (2022) and the United States (2022).
References
[4] CIAT/IOTA/OECD (2020), “Tax administration responses to COVID-19: Measures taken to support taxpayers”, OECD Policy Responses to Coronavirus (COVID-19), OECD Publishing, Paris, https://doi.org/10.1787/adc84188-en.
[3] OECD (2019), Successful Tax Debt Management: Measuring Maturity and Supporting Change, OECD, Paris, https://www.oecd.org/tax/forum-on-tax-administration/publications-and-products/successful-tax-debt-management-measuring-maturity-and-supporting-change.htm (accessed on 13 May 2022).
[1] OECD (2019), Tax Administration 2019: Comparative Information on OECD and other Advanced and Emerging Economies, OECD Publishing, Paris, https://doi.org/10.1787/74d162b6-en.
[5] OECD (2016), Advanced Analytics for Better Tax Administration: Putting Data to Work, OECD Publishing, Paris, https://doi.org/10.1787/9789264256453-en.
[2] OECD (2014), Working Smarter in Tax Debt Management, OECD Publishing, Paris, https://doi.org/10.1787/9789264223257-en.