Recent conceptual and methodological developments on measuring illicit financial flows for policy action

SDG indicators

SDG target 16.4: By 2030, significantly reduce illicit financial and arms flows, strengthen the recovery and return of stolen assets and combat all forms of organized crime
SDG indicator 16.4.1: Total value of inward and outward illicit financial flows (in current United States dollars) (Tier II)

Every year, billions of dollars of IFFs stemming from organized crime, trade in illegal goods, corruption and illegal and illicit tax and commercial practices move across borders, often in the direction of financial havens. These flows divert resources that are needed for sustainable development. By eroding the tax base and discouraging public and private investment, they hamper structural transformation and sustainable economic growth. They also weaken state institutions by fuelling corruption and violence and undermine the rule of law and the functioning of the criminal justice systems.

The ability to achieve the SDGs remains fragile when undermined by IFFs. Indeed, the 2030 Agenda for Sustainable Development (United Nations, 2015b) underscores the need for an increased mobilization of financial resources dedicated to sustainable development, including through the improved capacity for revenue collection, and more resources dedicated to investment. IFFs undermine this effort. The 2030 Agenda identifies the reduction of IFFs as a priority area to build peaceful and just societies around the world, as reflected in target 16.4, which reads: “by 2030, significantly reduce illicit financial flows and arms flows, strengthen the recovery and return of stolen assets and combat all forms of organised crime”. The Addis Ababa Action Agenda (United Nations, 2015a) on financing for development also calls for a redoubling of efforts to substantially reduce IFFs, with a view to eventually eliminating them.

In July 2017, the United Nations General Assembly adopted the indicator framework for the monitoring of progress towards SDGs (United Nations, 2017). Indicator 16.4.1, “total value of inward and outward illicit financial flows (in current United States dollars)”, was selected as one of the indicators to measure progress towards target 16.4. At the time, there was no universal agreement on the definition of IFFs, what should be included within their scope or how the component parts could be measured. Absence of consistent statistics on IFFs causes uncertainty about how large these flows are, how and where they originate and their impact on development, and it hampers policy action to combat these flows. UNCTAD and UNODC, the two co-custodians of indicator 16.4.1, started methodological work and broad consultations to develop statistical definitions and methods to measure IFFs.1

Statistical challenges in measuring IFFs

A review of the literature reveals that there are different understandings of what IFFs constitute and how they can be measured. Understanding what is illicit or even illegal can differ by jurisdiction, or depend on many determinants and contextual elements. Consequently, it is not straightforward to decide on an internationally applicable criteria as to which flows are illicit.

IFFs are deliberately hidden and, as they take many forms and use varying channels, their measurement is challenging both conceptually and in practice. The challenges differ across countries, depending on their institutions, types of activities generating IFFs, statistical practices and national priorities. This calls for space for country-specific solutions and the flexible application of methods in line with a common framework.

Comparable statistics need to be based on definitions that can be applied in a similar fashion across countries. For instance, crime statistics are based on an ICCS (UNODC, 2015) consisting of actions and behaviours to be measured regardless of what is considered a crime by the national legislation. From a practical perspective, statistics cannot be based directly and exclusively on legal considerations since legal frameworks are not consistent across jurisdictions and are often reactive (e.g., with significant time lags before new activities are declared illegal) leading to differential treatment across countries and time.

Transactions of an illicit nature can take place in several guises and at various stages of economic activity.2 The activities that generate IFFs need to be analysed carefully and placed in a framework that can identify the various components that give rise to illicit activity. IFFs need to be classified using a discrete, exhaustive and mutually exclusive statistical classification aligned with existing statistical frameworks and principles (OECD, 2020a).

Many illicit activities are intertwined. To avoid duplication, separate accounting for income generation and income management is needed consistent with the SNA and other statistical frameworks.

Conceptual development and reclassification of SDG indicator 16.4.1 as a Tier II indicator

UNCTAD and UNODC are undertaking a series of coordinated actions and consultations to develop the statistical measurement of IFFs. The initial steps involved analytical studies and background research and a review of the measurement methods applied by various researchers and organisations across countries and internationally.

From 2017 to 2019, UNODC and UNCTAD held a series of expert consultations to take stock of current research, knowledge and experience regarding different types of IFFs (UNODC, 2017; UNCTAD, 2018). The expert consultations included contributions from national statistical offices, financial intelligence units, tax authorities, academia, non-governmental organisations, international organisations and other IFF experts. In addition, UNCTAD and UNODC collected expert advice and insights at various fora. The meetings highlighted an urgent need to agree on concepts and definitions and recommended further engagement with national statistical authorities.

To this end, UNCTAD and UNODC established a joint statistical Task Force on the measurement of IFFs in January 2019 to define concepts, assess data availability, develop statistical methods, and review country-level activities in this area.3 The Task Force’s work is based on analytical studies that provided a thorough overview of the aspects to be addressed in developing a method for SDG indicator 16.4.1. The statistical definitions and methods build on previous work on IFFs and related statistical activities.4

Following the review of current methods, the Task Force held several conference calls and a meeting in Geneva on 16-17 July 2019, leading to a common understanding and a way forward on the statistical scope and definitions for measuring SDG 16.4.1. Based on this work, the custodian agencies presented in October 2019 a reclassification request at the 10th session of the IAEG-SDG. The IAEG-SDG endorsed the direction taken, and reclassified indicator 16.4.1 from Tier III to Tier II, meaning that the indicator is conceptually clear and based on internationally established standards, while data are not yet available from countries.

Statistical definition and scope of IFFs for SDG indicator 16.4.1

For the purpose of the SDG indicator, IFFs are defined as financial flows that are illicit in origin, transfer or use that reflect an exchange of value and cross country borders. This definition implies that IFFs have the following features:

  • Illicit in origin, transfer or use. A flow of value is considered illicit if it is illicitly generated (e.g. originates from criminal activities or tax evasion), illicitly transferred (e.g. violating currency controls) or illicitly used (e.g. for financing terrorism). The flow can be legally generated, transferred or used, but it must be illicit in at least one of these aspects. Some flows that are not strictly illegal may fall within the definition of IFFs, e.g. cross-border tax avoidance which erodes the tax base of a country where that income was generated.
  • Exchange of value, rather than money or purely financial transfers. Exchanges of value include not only currency exchanges, but also exchanges of goods and services, and financial and non-financial assets.
  • IFF measure a flow of value over a given time, as opposed to a stock measure, which would be the accumulation of value.
  • Flows that cross a border. This includes assets where the ownership changes from a resident of a country to a non-resident, even if the assets remain in the same jurisdiction.5

SDG indicator 16.4.1 calls for the measurement of the “total value” of IFFs. While useful as an indication of the overall size of the IFF problem and for advocacy, it has limited applicability as policy guidance. A more granular measurement and a finer typology would help to identify and separate, as necessary, the main sources and channels of IFFs and also provide guidance for national and international interventions targeting them. Such a typology would also enable disaggregation of those IFFs that are legal from those that are not.

IFFs originating from illegal economic activities can be laundered so that subsequent transactions appear as legal. It should be emphasised that flows of capital of illegal origin should be considered as IFFs when crossing a border, since the origin of the funds is in illicit activities. However, it can be very challenging to determine the illicit origin of certain financial flows as the distance from the illicit origin increases. IFFs can also originate from legal economic activities, but become illicit when financial flows are managed and transferred, for instance, to evade taxes or used to finance illegal activities.

With national laws and country practices differing, and with IFF measurement being a statistical exercise rather than an audit or judicial one, it is not possible to define the scope of measurement in terms of legality. The indicator is, therefore, constructed based on a typology of behaviours and activities generating IFFs. This is in line with the ICCS that lists and defines activities, many of which may generate IFFs. It describes the actions and provides examples of the activities concerned. This classification is a good point of departure for classifying IFFs. It is important to note, however, that not all IFFs would map onto this framework, as IFFs that are not part of illegal activities may not be covered. For complete coverage of IFFs, an additional classification complementing the ICCS would be required.

IFFs can be classified from many angles: sources, channels, impacts, actors involved, motives, etc. The typology should prioritize the main activities from which these flows, arise, therefore enabling effective policy action. Figure 1 looks at the types of activities that generate IFFs, i.e. the underlying activities rather than IFFs themselves.

Figure 1. Categories of activities that may generate IFFs
Source: UNCTAD and UNODC.

According to this typology, four main categories of IFFs are distinguished.

  • Illicit tax and commercial IFFs. This category includes illicit practices by legal entities as well as arrangements and individuals with the objective of concealing revenues, reducing tax burden, evading controls and regulations and other purposes. This category can be divided into two components:
    • Illegal tax and commercial IFFs. These include illegal practices such as tariff, duty and revenue offences, tax evasion, corporate offences, market manipulation and other selected practices. Some activities that are non-observed, hidden or part of the so-called shadow economy, the underground economy or the informal economy may also generate IFFs. Related activities included in the ICCS comprise tax evasion, tariff, duty and revenue offences, competition offences, import/export offences, acts against trade regulations, restrictions or embargoes and investment or stack/shares offences.
    • IFFs related to tax avoidance. Illicit flows can also be generated from legal economic activities through what is sometimes called harmful or aggressive tax avoidance (see box 1 for more detail on the distinction between legal and illegal illicit flows). Aggressive tax avoidance can take place through a variety of forms, such as manipulation of transfer pricing, strategic location of debt and intellectual property, tax treaty shopping, and the use of hybrid instruments and entities. For the purposes of the measurement of the indicator, these flows need to be carefully considered, as they generally arise from licit business transactions and only the illicit part of the cross-border flows belongs within the scope of IFFs.
  • IFFs from illegal markets. These include trade in illicit goods and services, when the money flows generated cross country borders. Such processes often involve a degree of criminal organisation aimed at creating profit. They include any type of illegal trafficking of goods, such as drugs and firearms, or services, such as smuggling of migrants. IFFs are generated by the flows related to international trade of illicit goods and services, as well as by cross-border flows from managing the illicit income from such activities.
  • IFFs from corruption. The United Nations Convention against Corruption (UNODC, 2004) defines acts considered as corruption, which are consistently defined in the ICCS. These include bribery, embezzlement, abuse of functions, trading in influence, illicit enrichment and other acts. When the economic returns from these acts directly or indirectly generate cross-border flows, they are considered IFFs.
  • IFFs from theft-type activities and financing of crime and terrorism. Theft-type activities are non-productive activities that entail a forced, involuntary and illicit transfer of economic resources between two actors. Examples include theft, extortion, illicit enrichment, and kidnapping. In addition, terrorism financing and financing of crime are illicit, voluntary transfers of funds between two actors with the purpose of funding criminal or terrorist actions. When the related financial flows cross country borders, they constitute IFFs.
Box 1: Aggressive tax avoidance and IFFs

A specific conceptual challenge is to specify what kinds of activities should be designated as illicit or licit. This issue is particularly challenging in the area of tax avoidance. It is noteworthy that SDG 16.4 refers to ‘illicit’ instead of ‘illegal’ financial flows. Aggressive tax avoidance, including by MNEs, could have similar economic consequences to illegal financial flows and can drain resources from countries and thus can be considered illicit.

The inclusion of tax avoidance in the definition of IFFs creates some challenges, as it blurs the line between legal and illegal activities. For example, while aggressive tax avoidance can be considered detrimental to sustainable development, it generally involves activities that are not illegal. For the purposes of the indicator, aggressive tax avoidance is included as an IFF, while noting that these activities are generally legal.

Noting that the boundary between legal and illegal tax practices may be unclear, the Institute for Advanced Studies (2017) describes a continuum of activities from legal tax planning to illegal tax evasion (see figure 2). They describe aggressive tax planning as “taking advantage of the technicalities of a tax system or of mismatches between two or more tax systems for the purpose of reducing tax liability.”

Figure 2. Boundaries of aggressive tax planning

IFFs stemming from aggressive tax avoidance are considered in detail in OECD (2013), and can include BEPS through interest payments, strategic location of intangible assets, abuse of tax treaties, artificial avoidance of permanent establishment and transfer pricing manipulation. The BEPS package, released in 2015 by OECD and G20 countries, delivers guidance for governments to close gaps in existing international rules that allow corporate profits to be artificially shifted to low-tax jurisdictions where companies have little or no economic activity. Work to address outstanding BEPS issues by the Inclusive Framework is ongoing (OECD, 2020b). As part of the OECD Inclusive Framework on BEPS, progress has also been made in improving the data availability to support the measurement of MNE tax avoidance, including through the forthcoming public release of aggregated and anonymised country-by-country report statistics.

As mentioned, the ICCS is a good point of departure for listing and defining some of the activities that could generate IFFs, such as theft-type activities and terrorism, illicit trafficking and corruption, as well as many activities related to tax and commercial malpractices. Table 1 provides examples of such activities and how to link the main categories of IFFs to activities that generate them.6

Table 1. Examples of activities generating IFFs from crime, by ICCS categories
Categories of IFFsExamples
Tax and commercial practices08041 Tariff, taxation, duty and revenue offences
08042 Corporate offences including competition and import/export offences; acts against trade regulations
08045 Market manipulation or insider trading, price fixing
Theft-type activities and terrorism financing (parts of sections 02, 04, 09)020221 Kidnapping
020222 Illegal restraint
020223 Hijacking
020229 Other deprivation of liberty
0204 Trafficking in persons
0205 Coercion
0401 Robbery
0501 Burglary
0502 Theft
09062 Financing of terrorism
Illegal marketsICCS includes a long list of activities, including for example drug trafficking (060132), firearm trafficking (090121), illegal mining (10043), smuggling of migrants (08051), smuggling of goods (08044), wildlife trafficking (100312)
Corruption (section 0703)07031 Bribery
07032 Embezzlement
07033 Abuse of functions
07034 Trading in influence
07035 Illicit enrichment
07039 Other acts of corruption
Source: UNODC.
Note: This list is only intended to provide some examples and it is not exhaustive.

It would also be useful to link the categories of IFFs and their source activities to their transmission channels. This requires further consideration since similar financial flows may apply to a variety of channels. Data availability and the selection of statistical methods are likely to depend on the type of activity generating IFFs and the channels used.

Factors defining the statistical methodologies for IFFs

There is a relevant stream of literature that proposes methods to measure IFFs from illegal economic activities, and illicit tax and trade-related practices. The methods proposed can be grouped in two general approaches:

  1. Top-down methods attempt to measure IFFs by interpreting or modelling inconsistencies in different types of aggregated data, such as currency demand, international trade, and capital account of BoP.
  2. Bottom-up approaches attempt to measure IFFs starting from the analysis of a given illicit activity, defining the set of flows that can be identified as IFFs and then producing estimates for each of them. Overall estimates are obtained by aggregating from a lower to a higher level.

Consistently with the statistical framework presented here, where different types of IFFs are defined in relation to the activity generating them, a bottom-up and direct measurement approach is proposed.7

An important distinction is made between two different stages where IFFs can be generated, which reflect two different finalities:8

  • IFFs linked to income generation, as the set of cross-border transactions that are performed in the context of the production of illicit goods and services or the set of cross-border operations that directly generate illicit income for an actor during a non-productive illicit activity. Inward or outward IFFs occur when the operation in question is performed across a border.
  • IFFs linked to income management, as the set of cross-border transactions finalised to use the (illicit) income for investment in (legal or illicit) financial and non-financial assets or for consuming (legal or illegal) goods and services. If spent abroad, the operation is an outward IFF. If stemming from illicit activity outside a jurisdiction but is spent in the domestic jurisdiction, an inward IFF is generated.

In sum, this approach considers the multi-dimensional nature of IFFs, comprising several different kinds of activities, including flows originating from illicit activities, illicit transactions to transfer funds that have a licit origin, and flows stemming from licit activity being used in an illicit way. It identifies the main types of IFFs to be measured and lays out a framework based on existing statistical definitions, classifications and methodologies, in line with the SNA and BoP. A disaggregated and bottom up measurement approach is proposed in line with these frameworks and following international efforts to measure non-observed or illegal economic activities.

Data requirements for measuring IFFs

National statistical systems already have some of the data needed for the measurement of IFFs, but these data are scattered across a range of authorities and statistical domains. For instance, existing national accounts and BoP statistics include estimates of illegal economic activities and the non-observed economy, provide a good starting point for the measurement of IFFs.

Other relevant data may be held by the police and ministries of justice, councils of justice, financial intelligence units and other government agencies collecting information on seizures and criminal offences. In addition, tax authorities collect relevant data for assessing tax gaps and exchange country-by-country reporting data on multinational enterprises, although these data are often collected for purposes other than statistical analysis. Statistics on international trade in goods and services can provide useful information on commercial IFFs.

According to a recent IMF survey on the measurement of the informal economy, over 60 per cent of national statistical offices collate relevant data on underground, illegal and informal activities using surveys, administrative sources, mirror statistics, international studies and expert assessment (IMF, 2018). While informal activities are largely domestic, many of them also generate cross-border flows, and while the statistical sources may not cover all kinds of IFFs, they typically focus on those flows that are most relevant to a country. There are also systematic data collections on crime and related IFFs; UNODC, for instance, compiles statistics on drugs as reported directly by countries, including detailed data on demand, supply, prices, drug characteristics, seizure data, etc.

It is likely, however, that additional sources of information will need to be identified to measure IFFs consistently. Compiling statistics on IFFs requires access to many data sources held by different authorities. Central banks, tax authorities and national statistical offices often have the strongest mandate to collect and access such data. National statistical offices, as the focal point for coordinating the compilation of SDG indicators, should lead the work to bring the necessary stakeholders together to measure IFFs.

Next steps in developing SDG indicator 16.4.1

While some elements of IFFs are more readily measurable, others are more challenging to estimate, including bribery, abuse of functions, illicit enrichment and illicit tax practices. Data on these activities remain scattered. Further work is needed to develop methods to measure the various types of IFFs separately, starting from those for which data are available. Adjustments will be needed to avoid double counting. Furthermore, in practice it may be necessary to estimate separately some of the IFFs with the highest uncertainties.

The next steps in the methodological development of SDG indicator 16.4.1 will be to further develop and test a range of statistical methodologies consistent with the definitions above and the SNA and BoP statistics. While many countries already collect data on a number of illegal activities and other statistics, it will still be important to strengthen countries’ capacities for comprehensive data collection and compilation of IFFs statistics. UNCTAD and UNODC, with partner organizations, will support countries in improving their statistical capacity to understand and estimate IFFs. A series of pilot studies are being conducted with volunteer countries and they are providing critical information to refine the conceptual framework and to develop guidance on statistical methods to measure IFFs.9

The statistical Task Force will continue its work to support countries in national data collection and compilation with a view to developing a Practical Compilation Guide for the Measurement of Illicit Financial Flows based on this conceptual framework. This will include a full classification of activities generating IFFs, linked to the types and channels of IFFs, with recommended methods to measure them. Further work will also aim at developing a more nuanced measurement of IFFs to support policy action. In the future, the measurement of IFFs as a satellite account taking into consideration national accounts concepts and definitions could be worth exploring.


  1. This chapter is an abridged version of UNCTAD and UNODC (forthcoming).
  2. The Balance of Payments Manual 6th edition (IMF, 2009) defines illegal transactions as those that are forbidden by law, and only when the institutional units involved enter the actions by mutual agreement. Otherwise, they are considered as other flows. Illegal transactions are treated the same way as legal actions in BoP statistics
  3. The Task Force is composed of statistical experts from Brazil, Finland, Ireland, Italy, Peru, South Africa and the United Kingdom, representing national statistical offices, central banks, customs or tax authorities. The Task Force also includes experts from international organisations with recognised expertise in this field. Eurostat, IMF, OECD, UNECA, UNSD, UNCTAD and UNODC are represented.
  4. This includes work carried out previously by Eurostat, Global Financial Integrity, IMF, OECD, UNECA, United Nations Statistics Division, World Bank, UNCTAD and UNODC, as well as findings from academic studies.
  5. The proposed bottom-up measurement approach described below considers domestic illicit financial flows as part of the illegal economy too. These flows would not fall under the definition of IFFs for SDG indicator 16.4.1, but are of high relevance to understand organised cross-border illicit flows.
  6. It is important to note that not all IFFs would map onto this framework. Notably, IFFs related to tax avoidance and other tax malpractices may not be covered in the ICCS.
  7. This approach is consistent with Eurostat (2018).
  8. This basic typology is coherent with the main concept of national accounts. Indeed, income generation refers to the set of operations that in national accounts relate to production account, and generation and distribution of income account, while income management refers to the set of operations that in national accounts refer to capital and use of income account.
  9. Pilots are carried out as part of UNCTAD and UNODC projects, in collaboration with countries and UN Regional Commissions in Africa and Latin America, where Africa will be focused mostly on illicit tax and commercial practices and Latin America on illegal markets (illicit drugs, smuggling of migrants, human trafficking and illegal mining). In 2020, pilots will be extended to Asia and the Pacific in collaboration with the UN Economic and Social Commission for Asia and the Pacific.


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