Frequently Asked Questions (FAQs) for the Reporting and Analysis of Remittances 

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The FAQs for the Reporting and Analysis of Remittances serve as a handy reference for development partners and regulators, especially central bank officers involved in data compilation and analysis around payment systems and remittances. The FAQs cover everything from Balance of Payments to remittance measurement and reporting at the country level—including the challenges in measuring remittances, estimations on informal remittances, transaction-level data, or the importance of collecting sex-disaggregated data. The FAQs also cover references to our published papers and remittance guides, tools, and data collection systems.

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Section 1: Balance of Payments and Remittances

Section 2: Remittance Measurement and Reporting

Section 3: Remittance Guides, Tools, and Data Collection Systems

Section 1: Balance of Payments and Remittances

What are Remittances?

As defined by the International Monetary Fund (IMF)’s Balance of Payments and International Investment Position Manual, 6th edition (BPM6), remittances represent “household income from foreign economies arising mainly from people’s temporary or permanent move to those economies. Remittances include cash and noncash items that flow through formal channels, such as via electronic wire, or through informal channels, such as money or goods carried across borders. They largely consist of funds and noncash items sent or given by individuals who have migrated to a new economy and become residents there and the net compensation of border, seasonal, or other short-term workers who are employed in an economy in which they are not resident.”

Why do Remittances matter?

Remittances are a rapidly growing and stable foreign exchange inflow to many countries worldwide. Central banks are increasingly relied upon by policymakers and the private sector to collect and process remittance data that support macro and microeconomic policies and to inform investment and innovation decisions. In particular, accurate data on remittances enables (i) an understanding of household consumption and savings trends, (ii) the identification and investigation of significant changes in international fund flows, (iii) combating terrorist financing and money laundering, (iv) policy and regulatory responses in areas such as financial stability and financial inclusion, and (v) a private sector understanding of market dynamics and operational and strategic decision-making.

What is the Balance of Payments?

The balance of payments (BoP) is a statistical statement that summarizes transactions between residents and non-residents during a given period. The BoP statement provides a clear picture of the economic relations between different countries and consists of three main components: current accounts, capital accounts, and financial accounts. The BoP uses a double-entry accounting system where each transaction is recorded as consisting of two entries, with the sum of the credit entries and the sum of the debit entries being the same. The capital and financial account always offset the current account, so the sum of these accounts (the balance of payments) is zero. It is difficult to accurately record every single transaction between residents in a country with the rest of the world due to measurement errors[1]. Hence, some transactions are not measured and are ‘omitted’. Therefore, an additional item is included in the balance of payments, known as ‘net errors and omissions’, to ensure that it always balances.

([1] For example, if net lending/net borrowing measured from the current and capital accounts is 29, while net lending/net borrowing measured from the financial account is 31, then net errors and omissions is +2. See International Monetary Fund (2010). Balance of payments and international investment position manual. Washington, D.C.: IMF. (2014, pp11).

Why does the Balance of Payments matter?

The balance of payments is a vital source of information for a country, specifying information on important economic indicators (significant for the Least Developed Counties (LDCs)), such as goods and services, development assistance, remittances, and foreign direct investment, among other vital indicators. Most countries report the BoP every quarter, enabling data comparisons between countries over time. In a world with increasingly fluid labour markets, free trade areas, common markets, and economic unions, we observe political, economic, and technological barriers rapidly disappearing, and the ability of a country to participate in global activity becomes an essential indicator of its performance and competitiveness (Eurostat).

The BoP offers vital information on the outlook of an economy to a wide variety of users, starting from central banks, policymakers, investors, business owners, economists, researchers, and other parties interested in this information.

Where can I find Data on the Balance of Payments and Remittances?

The official remittance data is published by central banks as a standard component of the BoP statistics under the current account. The current version of the BoP is an essential indicator of an economy’s health and consists of the goods and services account, the primary income account, and the secondary income account. The main part of the remittance data is included in the secondary income account.  

The data on remittances is generally available on the official web pages of respective central banks under BoP statistics. Data on remittances is also available from international organizations such as IMF (International Monetary Fund) and the World Bank (World Bank Indicators).

Where can I find Information on the Methodologies of the Balance of Payments?

The IMF’s BPM6 Manual, guides IMF Member States in compiling BoP statistics. Important information on the metadata for the compilation of BoP for the IMF Member States can be found on the IMF’s Dissemination Standards Bulletin Board, DSBB page. The IMF’s National Summary Data Pages (NSDPs) also include links to the data and the methodologies used for statistics on BoP.

Where can I find Information on the Methodologies for Remittances?

The conceptual framework of statistical information on remittances comprises the IMF’s BPM6 Manual  on recommended data definitions and classifications and the IMF, 2009  International Transactions in Remittances: Guide for Compilers and Users, for more detailed information on sources and methods that can be used when measuring remittances.

Remittances in the IMF’s BPM6 Manual are derived mainly from two items in the balance of payments framework, i.e., income earned by workers in economies where they are not resident (or from non-resident employers) and transfers from residents of one economy to residents of another. Namely, standard components used to calculate remittances are compensation of employees and personal transfers, as shown below:

  • compensation of employees that refers to the income of border, seasonal, and other short-term workers employed in an economy where they are not residents and residents employed by non-resident entities.
  • personal transfers consist of current and capital transfers made to or received by residents or non-residents

The following items are reported as supplementary items for remittances in BoP: capital transfers, capital transfers between households, social benefits, current transfers, and capital transfers to Nonprofit institutions serving households (see table 1).

Table 1. Presentation of remittance concepts in BPM6:

Source: IMF’s BPM6 Manual, Appendix 5, Remittances, Table A5.2

What are the primary Sources of statistical Information on Remittances?

The recommendations on data sources for measuring remittances are provided in the IMF Guide on remittances: IMF, 2009, International Transactions in Remittances: Guide for Compilers and Users. They are as follows:

  • International Transactions Reporting System (ITRS) reported by commercial banks
  • Remittance transfer operators such as banks or money transfer operators (MTOs), postal networks, telecommunications companies, and other fintech with money service business licenses or as applicable
  • Surveys (labour market surveys, household surveys, income and expenditure surveys, demographic surveys, specialized surveys with migrants, etc.)
  • Indirect data sources or estimation models (demographic models, econometric models, residual models, etc.)

Section 2: Remittance Measurement and Reporting

Who has the legal Mandate to produce Data on Remittances at a Country Level?

The mandate to produce official data on remittances is established at a country level by law. This mandate generally falls under that country’s central bank. The data on remittances are measured as part of the BoP under the statistics department specifying the reporting requirements for individuals, companies, and institutions. Central banks are expected to cooperate closely with other national institutions responsible for producing official statistics, such as the respective country’s national statistics office, the ministry of finance, other relevant line ministries, and national stakeholders.

What are the main Challenges in measuring Remittances?

One of the main obstacles to obtaining data on remittances is having accurate data sources that are methodologically sound and are reported timely and frequently[2]. Other factors that need to be considered are cost, feasibility, and legal and institutional environment[3]. Central banks face a challenge in clearly specifying and routinely updating the legal mandate for reporting data related to remittances as part of the BoP as the financial market develops rapidly with new RSPs entering the markets and bringing new technologies for money transfers (such as mobile wallets, etc.). These changes make it more time-consuming for central banks to update reporting forms and harmonize the legal mandate with cash transaction report (CTR) and suspicious transaction report (STR)[4] requirements at both country and international levels.

Remittances are a challenge to measure because there are many ways for individuals to send and receive money in numerous small transactions through various channels. These channels can be formal (e.g., banks, nonbank financial institutions, and money transfer operators) and “informal” channels (e.g., hawala, cash carried in person, in-kind transfers),[5] making the process of measuring the remittance data complex and challenging. Remittance data are critical in least developed countries (LDCs), where resources are lacking to develop advanced systems for measuring remittances.

References:

  • [2] IMF, 2009 International Transactions in Remittances: Guide for Compilers and Users, Table 4.6. Summary of Data Source Characteristics
  • [3] IMF, 2009 International Transactions in Remittances: Guide for Compilers and Users, Appendix 2, Data Quality Assessment Framework: Generic Framework
  • [4] UN Security Council Resolution (UNSCR) 2195 (2014) on Threats to international peace and security and UNCSRs 2199(2015) and 2253(2015) on Threats to international peace and security caused by terrorist acts.
  • See also: FATF 2021: “Digital Transformation Of AML/CFT For Operational Agencies”.
  • [5] IMF, 2009 International Transactions in Remittances: Guide for Compilers and Users, (pp 13)

Can the available Data on Remittances be further improved?

Available remittance data is often highly aggregated, published with a significant time delay, and often in non-machine-readable formats. Financial regulators can use technology to improve remittance data and guide the market through policy and regulation. They can also empower the private sector to make smarter decisions and support other government areas to enact more appropriate policies by acting as the trusted aggregator and provider of complete, high-quality, timely, disaggregated (transactional data) market information.

Why are Estimations on informal Remittances important?

Very often, the available data on remittances only includes the data sent/received via formal channels (personal transfers and compensation of employees sent via commercial banks and MTOs). Unfortunately, there are still gaps in the data, especially for remittances sent through informal channels (e.g., hawala, cash carried in person, in-kind transfers), hindering evidence-based policymaking and product innovation. These gaps in data can be eliminated by estimating remittances received via informal channels. Estimations on informal remittances can be used to assess whether informal remittances are an issue for a specific region, country, or migration corridor. These estimations also provide information on the size, nature, direction, and usage of informal remittances in a country or region.

What is the Difference between aggregated, highly disaggregated, and transaction-level Data?

Remittances data can be reported in the following forms:

  • Aggregated data: Data where one or more attributes aggregate volumes and values of transactions. For example, the value of remittances is reported and summarized by the country of origin or the channel (i.e., bank or money transfer operator (MTO)). This would allow a central bank to analyse data by country or channels (but not both).
  • Highly disaggregated data: Data aggregated using multiple, not singular, attributes, e.g., if remittance values and volumes were reported summarized by country of origin, channel, currency, sex, and location of residence of the sender or recipient. This would, for example, enable a central bank to see how many women in a particular region received the total value of remittances from the United States through a transfer via a commercial bank.
  • Transaction data: This includes data that could be expected to be present within the transfer instruction. This would include country of origin and destination, entity type (i.e., bank or MTO), the currency of transfer, and the transfer’s value, allowing multiple data attributes to inform a single analysis.

For more information, read The case for the collection and analysis of transaction-level, supply-side data on remittances.

Why is transaction-level Data on Remittances important?

Detailed remittance transaction-level data allows the most detailed analysis possible, enabling data to be filtered, cut, and analysed using attributes such as country of origin, time, currency, location, and sex. These filters can be combined in multiple ways, creating new lenses for insight generation. Central banks and other key policymakers, including financial intelligence agencies, ministries of labour, immigration and education, and market players, can benefit from the insights generated by analysing transaction-level, supply-side data to inform policy direction. For examples of policymakers collecting and analysing remittance data, please refer to  The case for the collection and analysis of transaction-level, supply-side data on remittances.

The collection and analysis of transaction-level data on the remittance market can improve the ability of central banks and policymakers to influence the market through a better understanding of the economic role of remittances and more detailed information on dimensions and drivers of usage and exclusion. This will result in data-informed policies and product development, which is especially important for least developed countries (LDC).

Why is sex-disaggregated Data on Remittances important?

Due to gender inequalities, financial exclusion and discrimination, women in some countries lack access to financial services. Without access to safe, affordable, and convenient remittance services, it is unsurprising that many migrants, especially women, choose to bypass formal channels and instead use the unregulated networks ubiquitous in many countries. This decision jeopardizes the well-being of migrants and their families, limiting their resilience when faced with shocks, including natural disasters, income disruptions, death or illness, violence, and harassment or crop failure. Women, like men, may encounter barriers when sending and receiving money internationally via formal channels. However, women may face these barriers more often, to a greater extent, and in different ways because of their gender[6]. Disaggregated data to understand and develop supportive policies to redress these barriers may be one of the most efficient and effective ways of combatting informality in some remittance markets. With sex-disaggregated data, policymakers can make targeted interventions to help overcome these barriers and inequalities. For more information, read The case for the collection and analysis of transaction-level, supply-side data on remittances.

[6] Dhrodia, Azmina, “Exploring the Gender Gap in Identification: Policy insights from 10 countries”, GSMA, Gender Gap – Mobile for Development, 23 February 2019 (https://www.gsma.com/mobilefordevelopment/ blog/exploring-the-gender-gap-in-identification-policy-insights-from-10-countries/, accessed 10 December 2021); Hanmer, Lucia and Marina Elefante, Achieving Universal Access to ID : Gender-based Legal Barriers Against Women and Good Practice Reforms, World Bank, Washington DC, USA, 2019 (https://openknowledge. worldbank.org/handle/10986/32474, accessed 10 December 2021); Hasler, Andrea and Annamaria Lusardi, The Gender Gap in Financial Literacy: A Global Perspective, GFLEC, July 2017 (https://gflec.org/wp-content/ uploads/2017/07/The-Gender-Gap-in-Financial-Literacy-A-Global-Perspective-Report.pdf, accessed 10 December 2021); OECD, “Gender gaps in financial literacy and financial education”, in The Pursuit of Gender Equality: An Uphill Battle, OECD Publishing, Paris, 2017 (https://doi.org/10.1787/9789264281318-13-en, accessed 10 December 2021).

How can Technology improve remittance Data? 

A modular design for remittance reporting enables capturing, managing, and analysing data on remittances and BoP. This would enable regulators to explore new and emergent technology trends to increase the efficiency and effectiveness of existing systems. The model can also be used to build a standalone remittance reporting system and allow transaction-level reporting to be combined, as far as possible, with the implementation of system-generated data and system-to-system data transfer. By using data validation techniques and appropriate data storage options, central banks can reduce the burden of manually generating, validating, reformatting, and editing data for themselves and the reporting entities. Consequently, disaggregated data can be reported to create meaningful insights for policymakers and support the development of appropriate remittance products. For more information, read A model for the systematic capture, management and analysis of remittance data by central banks.

Section 3: Remittance Guides, Tools, and Data Collection Systems

Where can I find Guides and Tools to help establish a Baseline for creating or improving the Remittance Data Collection System?

Since 2021, the United Nations Capital Development Fund (UNCDF), in consultation with central banks, published two guides (Assessment guide of the remittance collection landscape and Reference guide: Design and Implement a remittance reporting and analysis system) to support regulators and development partners in their journeys to develop remittance reporting and analysis systems. UNCDF also published three working papers (Lessons learned from central banks on building an ITRS to collect remittance data, A model for the systematic capture, management, and analysis of remittance data by central banks, and The case for the collection and analysis of supply-side data on remittances) to provide central banks with a model to collect, manage and analyse transaction-level data in a manner that supports the development of data-driven policy and for use in informing private sector investment and product development.

These guides and working papers provide guidance and steps on how financial regulators can utilize technology to guide the market through policy and regulation and empower the private sector to make smarter decisions and support other areas of government to enact more appropriate policies by acting as the trusted aggregator and provider of complete, high quality, timely, disaggregated market information.

In addition, these documents provide central banks and financial regulators, especially those in environments with limited financial and human resources, a path and the tools to explore and define use cases and insights most supportive to their needs, most appropriate to their market/economy and most achievable in their operating environment, the scope of the reporting and analysis system, feasibility and value of a system for reporting disaggregated data and key system-design considerations.

What Lessons were learned from Consultations with Central Banks regarding the Systems in place to collect and analyse remittance Data? 

Over the last two years, UNCDF has consulted with over 60 central banks. Below are some key findings garnered from the experience of central banks developing the International Transaction Reporting System and data-gathering systems:

  • The International Transaction Reporting System (ITRS) offers the potential to capture and analyse data but is underutilized or neglected. The ITRS is mainly used to produce data for extracting information based on the BoP reporting structure at an aggregated level (e.g., remittances by country), leaving out potentially valuable information (e.g., transactional data, information on sex, location, etc.).
  • Successful implementation relies on institutional willingness, the needs of policymakers, and the availability of resources. Especially important for the successful implementation of the ITRS are the legal mandate for reporting data, precise reporting forms and available guidelines for reporters to follow, and excellent communication and cooperation with reporters.
  • The choice of data collection methods will impact IT (Information Technology) architecture, the imposed compliance burden, data availability and implementation, and running costs. ITRS should contain some basic features to produce statistics of good quality. The ITRS should establish the reporting institutions, the level of detail (aggregated versus transaction by transaction), frequency, collection method, reporting forms, reporting channels, data security and quality assessment, and management.
  • Data transfer applications and electronic data-reporting portals offer a more secure, technically advanced, and efficient system. As the need for more detailed information grows, these reporting systems need to be updated by implementing new and more advanced technologies to meet these growing demands for data.
  • It is challenging to classify transactions used in the ITRS to conform as closely as possible to the classification required for the BoP statement. The main reasons for this are the lack of information (or low quality) for transactions and the lack of tools to handle high volumes of data reported.  
  • One of the most pronounced challenges to measuring remittances using ITRS data is the availability of the purpose of transactions in the ITRS system. The most frequent obstacles to having quality information for transaction purposes concern compliance with laws and regulations related to customer data privacy and reporting burdens due to the high volume of data reported, which takes considerable resources to process.
  • Capturing more granular data using sophisticated computer processes minimizes the reporting burden, especially electronic data transmission between the provider and the compiler. Advances in IT can make a large volume of raw data available to compilers at a low cost, facilitate compliance with reporting requirements, and reduce the burden on the banking system and reporting institutions.
  • The ITRS is reported and used independently, although it is not the sole reporting method used by central banks for BoP compilation. Therefore a greater integration of the ITRS system is needed combining other information systems and databases used by central banks.
  • New or alternative data sources and solutions could provide additional checks and validations, thereby strengthening the reliability and accuracy of BoP and remittance statistics. The availability of validation modules for ITRS increases data quality and reduces errors and burdens for reporters and compilers by checking data quality, identifying outliers, validating data formatting, and ensuring completeness.
  • Staff resources and costs can be reduced significantly by capturing more granular data using sophisticated computer processes and electronic data transmission between the provider and the compiler.
  • ITRS reporting usually covers only institutions regulated by the central banks. Other forms of transferring money (MTOs, RSPs, mobile money, informal agents, and other informal channels, etc.) can make up a significant percentage of remittance data in a country, which is potentially left uncovered.
  • Currently, most systems for capturing data on remittances lack the data analysis tools that enable the authorities to view consolidated and continuously updated data and remittance statistics. The availability of data analysis and visualization tools is essential for making the data available to different audiences, as dashboards and interactive analysis tools enhance the potential for insight generation.
  • Since remittances are sent/received mostly in small-value transactions, current transaction limits would have to be scrapped, and all transactions, regardless of value, would need to be reported to obtain the accurate data required to support policymaking and investment decisions.

For more information, read Lessons learned from central banks on building an ITRS to collect remittance data. More documents on learnings from these consultations are forthcoming.

What are the key Requirements for Central Banks to systematically capture, manage, and analyse remittance Data?

The key aspects for the systematic capture, management and analysis of remittance data are outlined below:

  • Insight generation, data granularity, and the role of the regulator: This includes a shift from traditional aggregated data reporting to transaction-level data reporting, giving regulators access to the raw transactional data that enables data users to generate the insights necessary to regulate these complex and fast-changing markets.
  • Transactional data: This enables regulators to drill down into data for insights into the drivers of remittances, removes the potential for human error from data entry transcription or analysis and reduces aspects of the reporting burden from reporting institutions.
  • Supplemental data: These data include attributes that are not contained within the transfer instruction (date and time of transfer, sex of the recipient, date of birth and address of the recipient, account type (if direct deposit), transaction type, the reason for the transfer, etc.).
  • System-generated data: Implementing system-generated data and system-to-system data transfer is a more effective and efficient method for transaction-level reporting.
  • Insight generation and communication: The disaggregated data on remittances makes it easier to estimate missing data on remittances sent or received through informal channels, enabling data compilers to design more targeted surveys and estimating techniques to collect and analyse remittance data.

For more information, read A model for the systematic capture, management and analysis of remittance data by central banks.

What are some good Examples of Countries using highly disaggregated and transaction-level Data for Remittances?

In 2021 and 2022, UNCDF conducted interviews with more than 60 central banks across various regions.

Examples of countries that have moved beyond high-level aggregate reporting of supply-side data:

  • Nepal: Highly disaggregated data
  • South Africa: Implementing a transaction-level remittance reporting and analysis system

Examples of countries that have remittances reported at the subnational level:

  • Mexico: Leveraging subnational reporting of remittance receipts
  • Egypt: Leveraging subnational reporting of remittance receipts

Examples of countries that have moved beyond using data to compile BoP data:

  • Kenya: Understanding market drivers and informing non-financial policy
  • Australia: Data sharing and leveraging transaction-level remittance data to improve financial intelligence

Examples of countries that use supplemental data on remittances:

  • Colombia: Sex-disaggregated data on the sender and recipient side
  • Rwanda: Sex-disaggregated data on the recipient side

Examples of countries that have implemented sex-disaggregated data for remittances:

  • South Africa: Implementing a transaction-level sex-disaggregated remittance reporting and analysis system

Examples of countries that use data analysis dashboards for analysing the remittance data:

  • El Salvador: Data analysis of transactional data on remittances using Power BI software
  • Thailand: Data analysis of transactional data on remittances using Tableau and Hadoop

Each case study describes a unique insight into the potential value of disaggregated data or how this data can be effectively collected or analysed. For more details about these case studies, read The case for the collection and analysis of supply-side data on remittances.