## SECTION I: THE ISSUE ## Source details **Canonical URL:** [SECTION I: THE ISSUE](https://www.imf.org/-/media/files/data/statistics/bpm6/fitt/f7-impact-of-fintech-on-macroeconomic-statistics.pdf) ## Other formats - [Markdown version](/-/media/files/data/statistics/bpm6/fitt/f7-impact-of-fintech-on-macroeconomic-statistics.pdf.md) - [Structured JSON version](/-/media/files/data/statistics/bpm6/fitt/f7-impact-of-fintech-on-macroeconomic-statistics.pdf.json) --- ### Background - Fintech is defined by the Financial Stability Board (FSB) as “technology-enabled innovation in financial services that could result in new business models, applications, processes, or products with an associated material effect on the provision of financial services.” - The conceptual frameworks of the System of National Accounts 2008 (2008 SNA) and the sixth edition of the Balance of Payments and International Investment Position Manual (BPM6) implicitly cover many fintech innovations (new entities, instruments, and technological processes) but do not explicitly reference the term “fintech” or many relevant products and technologies. - The guidance note (GN) discusses fintech implications for macroeconomic statistics using the FSB definition and recognizes the need for methodological flexibility given the rapid pace of fintech change. - The GN notes coordination needs with other workstreams in the BPM6/SNA update, including GN B.14 “Treatment of Digital Economy,” FITT GNs F.1 and F.6, the Advisory Expert Group on National Accounts Task Team on Digitalization (DZTT), and a separate joint FITT/DZTT GN F.18 “The Recording of Crypto Assets in Macroeconomic Statistics.” - Fintech is identified as a key data gap to be addressed as part of the planned new G-20 Data Gaps Initiative. ### Issues for Discussion — Institutional Units and Sectors - Fintech companies include entities providing financial services/products enabled by technological innovations and entities providing underlying digital technology supporting those services; they range from small start-ups to large technology firms (big techs). Traditional depository corporations that deploy new technological solutions generally would not be considered “fintech companies.” - Classification principle: fintech companies should be classified within existing institutional sectors/subsectors corresponding to the nature of their activities (2008 SNA, BPM6, and MFSMCG classifications). Many fintech companies will fall under “other financial corporations” (OFCs); some may be classified as nonfinancial corporations (NFCs) if provision of financial services is not their main function. - Introducing a new subsector titled “Fintech” is considered not feasible; instead an “of which” category could be introduced as a subsector/“of which” classification from an institutional perspective to identify fintech entities where needed. - TT-ISIC is considering a proposal to classify fintech related activities in Section K – Financial Services; institutional sector breakdowns for fintech companies in the BPM and SNA could be revisited depending on TT-ISIC outcomes. ### Issues for Discussion — Residence - The statistical concept of residence is, in principle, unaffected by fintech: entities are residents where they have their center of predominant economic interest. - Compilation challenges arise in cross-border contexts: - Electronic-money (e-money) use for cross-border payments at scale can challenge residency-based compilation because compilers may have limited access to foreign issuers of private currencies or e-money. - Smart contracts in decentralized finance (DeFi) transactions or crypto assets without a legal issuer complicate identification of residency. - Where corporations have little or no physical presence, residency can be determined by incorporation/registration under the statistical concept; if no incorporation/registration exists, legal domicile is used. Attribution of residency becomes challenging when legal domicile is unknown or no legal issuer exists. - The DZTT is assessing options to capture activities of platforms and providers of new digital products which tend to be located in specific territories. ### Examples of Fintech Services — Payments Services Enabled by Fintech - Key fintech-enabled payment products include electronic money (e-money), digital currencies (e.g., CBDCs), and other crypto assets. - E-money (MFSMCG paragraphs 4.38–4.41) is defined as a payment instrument whereby monetary value is electronically stored on a physical device or remotely at a server and represents a claim on the issuer. To be e-money, the instrument must represent general purchasing power (usable for direct payments to a variety of entities). - Statistical classification guidance: - E-money that can be used for direct payments to third parties is to be classified as transferable deposits, per MFSMCG (paragraph 4.38). - Examples of e-money: prepaid cards (stored value facilities) and web-based e-money (such as PayPal if monetary value is electronically stored). - Mobile money (MFSMCG paragraph 4.93; IMF FAS definition) is a form of e-money accessible via a mobile phone/device for direct payments to third parties; IMF FAS defines mobile money as a pay-as-you-go digital medium of exchange and store of value using mobile money accounts, facilitated by a network of mobile money agents. - The GN recommends the next edition of the SNA and BPM include explicit guidance on the treatment of “e-money” including “mobile money” consistent with the MFSMCG, and notes that e-money that meets the definition of broad money should be included in broad money within transferable deposits. ### Examples of Fintech Services — Deposits and Lending - Peer-to-Peer (P2P) lending companies and marketplace lending platforms (including DeFi) facilitate lending from individuals and other lenders, often unsecured to unrelated individuals or small businesses, circumventing traditional intermediaries. - Within 2008 SNA and BPM6, all sectors can potentially provide loans, including households. - Platforms that facilitate P2P lending but do not take ownership would, a priori, appear to be financial auxiliaries (BPM6, paragraph 4.79). The GN suggests explicit reference to this activity in the updated SNA/BPM akin to MFSMCG (paragraph 3.179). ### Examples of Fintech Services — Insurance (InsurTech) - InsurTech refers to innovative technologies and digital tools developed to optimize insurance company performance (International Association of Insurance Supervisors 2017). - Fintech improves efficiency in (re)insurance, delivers better customer experience, and leverages advanced analytics (e.g., AI, big-data) for risk prediction (climate-related or longevity risks). - Smart contracts on blockchains represent an example of fintech innovation affecting insurance processes. - InsurTech activities are implicitly covered by existing statistical frameworks; the GN proposes including a brief section on “insurance-related fintech activities” in the updated SNA and BPM without creating a new sectoral classification beyond existing classification of insurance companies under other financial corporations. ### Examples of Fintech Services — Other Financial Services - Fintech-enabled capital raising, investment management, and market provisioning do not require methodological amendments: - Crowdfunding: equity-based funding recorded as investment in equity; philanthropic/sponsorship funding recorded as current transfers (BPM6 and 2008 SNA). - Platforms facilitating such activities would a priori appear as financial auxiliaries, but classification depends on circumstances. - Asset management is already covered under financial services in BPM6 and 2008 SNA. - Big techs providing financial services are classified as NFCs according to main business characteristics; NFCs providing underlying technology but not insurance are classified as NFCs. NFCs that establish subsidiaries engaged in financial services have those subsidiaries classified according to their main characteristics (e.g., OFCs) while parents remain NFCs. ### Outcomes and Compilation Challenges - Finding: existing international statistical standards allow for proper treatment and recording of fintech companies and fintech-related activities in most cases. - Recommendation preference: do not introduce separate sectors or financial instruments for fintech; consider introducing an “of which” category for fintech companies within subsector classification if a country needs to separately identify them. - Targeted data collection (e.g., surveys) should be used to meet specific data needs for fintech activities (credit extended by fintech companies, asset management by fintech), designed to be flexible to accommodate ongoing developments. - Compilation challenges persist despite methodological adequacy: - Source data availability. - Decomposing spending on fintech technologies between intermediate consumption, final consumption, and gross fixed capital formation. - Treatment of multi-use applications (smartphone apps) that include fintech services. - Compilation guides for the next edition of BPM and SNA should address practical compilation issues and use outcomes of relevant GNs (e.g., GN F.18 on crypto assets, DZTT GNs on digital products/services). ### Recommendations (as proposed by the GN) - Recommendation 1: - Fintech companies should be classified within the existing institutional sectors/subsectors depending on the economic objectives, functions, and behavior (see BPM6, paragraph 4.57 and subsection 3 in Chapter 4 of the 2008 SNA) without introducing a new sector “Fintech”. - Depending on TT-ISIC discussion results, institutional sector breakdowns for fintech companies in the BPM and SNA could be revisited. - Recommendation 2: - Countries with significant fintech activities could consider introducing an “of which” category from an institutional perspective (i.e., which institutions may be considered as fintech companies) depending on statistical and analytical needs. - “Of which” categories could be introduced at the sector level (e.g., other sectors in ESS) or the sub-sector level (e.g., other financial corporations) reflecting specific country needs. - Compilers should be aware that such “of which” categories could become irrelevant in some years given fast technological developments (fintech today could become a traditional service tomorrow). - Recommendation 3: - Financial instruments and services provided by fintech should be classified in existing categories of macroeconomic statistics (e.g., deposits, financial services) without introducing new financial instruments or services categories. - New manuals and guides should elaborate on description and statistical recording of items that require clarification (e.g., insurance-related fintech activities, peer-to-peer lending, fintech-enabled capital raising through crowdfunding). - Recommendation 4: - The new edition of BPM and SNA should include explicit guidance on “e-money” including “mobile money” consistent with the MFSMCG to indicate that e-money that can be used for direct payments to third parties, including when used for cross-border payments, is to be classified as transferable deposits. - Recommendation 5: - Compilation guides for the next edition of BPM and SNA should address compilation issues related to fintech and can use recommendations of other GNs (e.g., DZTT GNs on digital products/services) to provide guidance to compilers. ### FITT discussion: Impact of Fintech on Macroeconomic Statistics - Classification and recommendations - FITT members showed strong support to the recommendations of this GN, including classifying fintech companies within the existing institutional sectors without introducing a new “fintech sector”. - Members also supported the separate identification of fintech companies within supplementary “of which” categories for countries that have a strong need to identify them separately in the SNA and the BPM. - One author of this GN suggested an international initiative to explore source data from commercial data providers. - These issues could be further discussed and included in the updated compilation guides. - Risks, definitional challenges, and data fragmentation - Some members indicated the risk of fragmented data, particularly if “of which” categories are introduced at the subsector level. - Members underlined the challenges in defining fintech in the statistical context because fintech today could become a traditional way of providing financial services tomorrow. - Compilation challenges were noted because traditional surveys might not be able to capture some fintech activities (e.g., those by households). - Recommendation: Compilation challenges should be continuously discussed reflecting the latest developments in fintech. - Questions for discussion (as presented) - 1) Do you agree with the recommendations provided above? - 2) Are you aware of other fintech or financial innovations that may be relevant from the perspective of macroeconomic statistics including any other payment services by fintech? - 3) Do you have any other recommendations related to fintech? *Guidance Note by the IMF Financial and Payments Systems Task Team (FITT) — SECTION I: THE ISSUE* ### SECTION I: THE ISSUE ### SECTION I: THE ISSUE ### Background - Fintech is defined by the Financial Stability Board (FSB) as “technology-enabled innovation in financial services that could result in new business models, applications, processes, or products with an associated material effect on the provision of financial services.” - The conceptual frameworks of the System of National Accounts 2008 (2008 SNA) and the sixth edition of the Balance of Payments and International Investment Position Manual (BPM6) implicitly cover many fintech innovations (new entities, instruments, and technological processes) but do not explicitly reference the term “fintech” or many relevant products and technologies. - The guidance note (GN) discusses fintech implications for macroeconomic statistics using the FSB definition and recognizes the need for methodological flexibility given the rapid pace of fintech change. - The GN notes coordination needs with other workstreams in the BPM6/SNA update, including GN B.14 “Treatment of Digital Economy,” FITT GNs F.1 and F.6, the Advisory Expert Group on National Accounts Task Team on Digitalization (DZTT), and a separate joint FITT/DZTT GN F.18 “The Recording of Crypto Assets in Macroeconomic Statistics.” - Fintech is identified as a key data gap to be addressed as part of the planned new G-20 Data Gaps Initiative. ### Issues for Discussion — Institutional Units and Sectors - Fintech companies include entities providing financial services/products enabled by technological innovations and entities providing underlying digital technology supporting those services; they range from small start-ups to large technology firms (big techs). Traditional depository corporations that deploy new technological solutions generally would not be considered “fintech companies.” - Classification principle: fintech companies should be classified within existing institutional sectors/subsectors corresponding to the nature of their activities (2008 SNA, BPM6, and MFSMCG classifications). Many fintech companies will fall under “other financial corporations” (OFCs); some may be classified as nonfinancial corporations (NFCs) if provision of financial services is not their main function. - Introducing a new subsector titled “Fintech” is considered not feasible; instead an “of which” category could be introduced as a subsector/“of which” classification from an institutional perspective to identify fintech entities where needed. - TT-ISIC is considering a proposal to classify fintech related activities in Section K – Financial Services; institutional sector breakdowns for fintech companies in the BPM and SNA could be revisited depending on TT-ISIC outcomes. ### Issues for Discussion — Residence - The statistical concept of residence is, in principle, unaffected by fintech: entities are residents where they have their center of predominant economic interest. - Compilation challenges arise in cross-border contexts: - Electronic-money (e-money) use for cross-border payments at scale can challenge residency-based compilation because compilers may have limited access to foreign issuers of private currencies or e-money. - Smart contracts in decentralized finance (DeFi) transactions or crypto assets without a legal issuer complicate identification of residency. - Where corporations have little or no physical presence, residency can be determined by incorporation/registration under the statistical concept; if no incorporation/registration exists, legal domicile is used. Attribution of residency becomes challenging when legal domicile is unknown or no legal issuer exists. - The DZTT is assessing options to capture activities of platforms and providers of new digital products which tend to be located in specific territories. ### Examples of Fintech Services — Payments Services Enabled by Fintech - Key fintech-enabled payment products include electronic money (e-money), digital currencies (e.g., CBDCs), and other crypto assets. - E-money (MFSMCG paragraphs 4.38–4.41) is defined as a payment instrument whereby monetary value is electronically stored on a physical device or remotely at a server and represents a claim on the issuer. To be e-money, the instrument must represent general purchasing power (usable for direct payments to a variety of entities). - Statistical classification guidance: - E-money that can be used for direct payments to third parties is to be classified as transferable deposits, per MFSMCG (paragraph 4.38). - Examples of e-money: prepaid cards (stored value facilities) and web-based e-money (such as PayPal if monetary value is electronically stored). - Mobile money (MFSMCG paragraph 4.93; IMF FAS definition) is a form of e-money accessible via a mobile phone/device for direct payments to third parties; IMF FAS defines mobile money as a pay-as-you-go digital medium of exchange and store of value using mobile money accounts, facilitated by a network of mobile money agents. - The GN recommends the next edition of the SNA and BPM include explicit guidance on the treatment of “e-money” including “mobile money” consistent with the MFSMCG, and notes that e-money that meets the definition of broad money should be included in broad money within transferable deposits. ### Examples of Fintech Services — Deposits and Lending - Peer-to-Peer (P2P) lending companies and marketplace lending platforms (including DeFi) facilitate lending from individuals and other lenders, often unsecured to unrelated individuals or small businesses, circumventing traditional intermediaries. - Within 2008 SNA and BPM6, all sectors can potentially provide loans, including households. - Platforms that facilitate P2P lending but do not take ownership would, a priori, appear to be financial auxiliaries (BPM6, paragraph 4.79). The GN suggests explicit reference to this activity in the updated SNA/BPM akin to MFSMCG (paragraph 3.179). ### Examples of Fintech Services — Insurance (InsurTech) - InsurTech refers to innovative technologies and digital tools developed to optimize insurance company performance (International Association of Insurance Supervisors 2017). - Fintech improves efficiency in (re)insurance, delivers better customer experience, and leverages advanced analytics (e.g., AI, big-data) for risk prediction (climate-related or longevity risks). - Smart contracts on blockchains represent an example of fintech innovation affecting insurance processes. - InsurTech activities are implicitly covered by existing statistical frameworks; the GN proposes including a brief section on “insurance-related fintech activities” in the updated SNA and BPM without creating a new sectoral classification beyond existing classification of insurance companies under other financial corporations. ### Examples of Fintech Services — Other Financial Services - Fintech-enabled capital raising, investment management, and market provisioning do not require methodological amendments: - Crowdfunding: equity-based funding recorded as investment in equity; philanthropic/sponsorship funding recorded as current transfers (BPM6 and 2008 SNA). - Platforms facilitating such activities would a priori appear as financial auxiliaries, but classification depends on circumstances. - Asset management is already covered under financial services in BPM6 and 2008 SNA. - Big techs providing financial services are classified as NFCs according to main business characteristics; NFCs providing underlying technology but not insurance are classified as NFCs. NFCs that establish subsidiaries engaged in financial services have those subsidiaries classified according to their main characteristics (e.g., OFCs) while parents remain NFCs. ### Outcomes and Compilation Challenges - Finding: existing international statistical standards allow for proper treatment and recording of fintech companies and fintech-related activities in most cases. - Recommendation preference: do not introduce separate sectors or financial instruments for fintech; consider introducing an “of which” category for fintech companies within subsector classification if a country needs to separately identify them. - Targeted data collection (e.g., surveys) should be used to meet specific data needs for fintech activities (credit extended by fintech companies, asset management by fintech), designed to be flexible to accommodate ongoing developments. - Compilation challenges persist despite methodological adequacy: - Source data availability. - Decomposing spending on fintech technologies between intermediate consumption, final consumption, and gross fixed capital formation. - Treatment of multi-use applications (smartphone apps) that include fintech services. - Compilation guides for the next edition of BPM and SNA should address practical compilation issues and use outcomes of relevant GNs (e.g., GN F.18 on crypto assets, DZTT GNs on digital products/services). ### Recommendations (as proposed by the GN) - Recommendation 1: - Fintech companies should be classified within the existing institutional sectors/subsectors depending on the economic objectives, functions, and behavior (see BPM6, paragraph 4.57 and subsection 3 in Chapter 4 of the 2008 SNA) without introducing a new sector “Fintech”. - Depending on TT-ISIC discussion results, institutional sector breakdowns for fintech companies in the BPM and SNA could be revisited. - Recommendation 2: - Countries with significant fintech activities could consider introducing an “of which” category from an institutional perspective (i.e., which institutions may be considered as fintech companies) depending on statistical and analytical needs. - “Of which” categories could be introduced at the sector level (e.g., other sectors in ESS) or the sub-sector level (e.g., other financial corporations) reflecting specific country needs. - Compilers should be aware that such “of which” categories could become irrelevant in some years given fast technological developments (fintech today could become a traditional service tomorrow). - Recommendation 3: - Financial instruments and services provided by fintech should be classified in existing categories of macroeconomic statistics (e.g., deposits, financial services) without introducing new financial instruments or services categories. - New manuals and guides should elaborate on description and statistical recording of items that require clarification (e.g., insurance-related fintech activities, peer-to-peer lending, fintech-enabled capital raising through crowdfunding). - Recommendation 4: - The new edition of BPM and SNA should include explicit guidance on “e-money” including “mobile money” consistent with the MFSMCG to indicate that e-money that can be used for direct payments to third parties, including when used for cross-border payments, is to be classified as transferable deposits. - Recommendation 5: - Compilation guides for the next edition of BPM and SNA should address compilation issues related to fintech and can use recommendations of other GNs (e.g., DZTT GNs on digital products/services) to provide guidance to compilers. *Guidance Note by the IMF Financial and Payments Systems Task Team (FITT) — SECTION I: THE ISSUE* ### 22. FITT members showed strong support to the recommendations of this GN, including ### Impact of Fintech on Macroeconomic Statistics ### Classification and recommendations - FITT members showed strong support to the recommendations of this GN, including classifying fintech companies within the existing institutional sectors without introducing a new “fintech sector”. - Members also supported the separate identification of fintech companies within supplementary “of which” categories for countries that have a strong need to identify them separately in the SNA and the BPM. - One author of this GN suggested an international initiative to explore source data from commercial data providers. - These issues could be further discussed and included in the updated compilation guides. ### Risks, definitional challenges, and data fragmentation - Some members indicated the risk of fragmented data, particularly if “of which” categories are introduced at the subsector level. - Members underlined the challenges in defining fintech in the statistical context because fintech today could become a traditional way of providing financial services tomorrow. - Compilation challenges were noted because traditional surveys might not be able to capture some fintech activities (e.g., those by households). - Recommendation: Compilation challenges should be continuously discussed reflecting the latest developments in fintech. ### Questions for discussion (as presented) - 1) Do you agree with the recommendations provided above? - 2) Are you aware of other fintech or financial innovations that may be relevant from the perspective of macroeconomic statistics including any other payment services by fintech? - 3) Do you have any other recommendations related to fintech? --- _Source: https://www.imf.org/-/media/files/data/statistics/bpm6/fitt/f7-impact-of-fintech-on-macroeconomic-statistics.pdf_