## ftnea2023003 — Introduction and Executive Summary

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### Fintech Verticals: Trends and Funding
- Covered verticals:
  - Digital Payments; Digital Banks (including neobanks and challenger banks); Alternative Finance by Fintech (including alternative lending and crowdfunding); Insurtech; Bigtech; regulatory innovations (suptech, sandboxes, open banking).
- Key scale and growth figures:
  - More than 300 million users of digital payments in 2021.
  - More than 30 million users of digital banks in 2021, mostly concentrated in Brazil and Mexico.
  - Digital payments: $89 billion in 2017 → $215 billion in 2021.
  - Transaction volume of fully online digital banks in LA6: $17 billion in 2017 → $123 billion in 2021.
  - Alternative finance lending: $0.7 billion in 2017 → $6 billion in 2020.
  - Number of insurtech companies in Latin America: 352 in 2021.
  - Number of digital banks in region: 10 in 2017 → 60 (55 of 60 in Mexico and Brazil).
- Sectoral startup composition (2021):
  - ~25 percent focused on digital payments and remittances.
  - ~20 percent focused on alternative financing (lending) platforms.
  - ~16.7 percent provided enterprise technologies for financial institutions (scoring, identity, fraud detection).
- Funding trends:
  - Average monthly venture capital and private equity funding for fintech: $38 million in 2015 → $90 million in 2019.
  - Three-month moving averages of total monthly funding (selected):
    - $104 million in December 2019
    - $77 million in May 2020
    - $257 million in January 2022 (peak)
    - $152 million in May 2022
    - $222 million in October 2022
  - LAVCA 2022: $6.1 billion in external investments in Latin American fintech across 258 transactions in 2021.
  - Investor size distribution: two-thirds invest less than $0.5 million; about a third invest between $0.5 and $5 million; about 10 percent invest more than $5 million.

### Causes and Macro Impact of the Fintech Boom
- Principal drivers:
  - Limited access to finance / insufficient competition among banks.
  - Improvements in digital infrastructure (Internet use: 74 percent in 2019 vs 34 percent in 2010).
  - Access to venture capital and risk capital.
- Financial development context:
  - SMEs’ financing gap reached $1 trillion by 2020.
  - Tecnolatinas ecosystem by 2021: 1,005 locally owned tech-based private companies, $221 billion of value, 245,000 jobs, $28 billion raised; fintech and e-commerce account for nearly three-quarters of ecosystem value; one in five tecnolatinas works in fintech, collectively raising one-third of the $28 billion.
- Competition and bank margins:
  - Estimated effect: an increase in digital banks’ transactions and activity is associated with reductions in net interest margins.
  - Quantified associations:
    - Increase in digital banks’ transactions by 1 percentage point in EMDEs and LAC associated with reduction in net interest margin by 0.2 to 1.9 percentage points (main text); Annex and robustness show effects ranging up to –1.862*** for Latin America and Caribbean (coefficient on digital banks’ transactions).
    - Between 2017 and 2020 interest rate margins declined by about 13 percentage points in Brazil; EMDE-sample model suggests digital banks’ activity reduced interest rate margins in Brazil by 3 percentage points.
- Inclusion and distributional links:
  - About three-quarters of digital banks’ customers are previously unbanked and underbanked consumers and SMEs.
  - More than one-third of all fintech companies in LAC serve those excluded from the formal financial system.
  - Two-thirds of digital banks’ loans go to under- and nonbanked consumers and SMEs.
  - Startup focus on underserved markets growing at average annual rate of 19.3 percent since 2017.
  - Fintech adoption associated with lower income inequality and higher female employment:
    - Fintech on Gini coefficient: –2.100*** (standard error 0.688).
    - Fintech on Female employment: 1.049*** (0.400).
    - A 1 percent increase in scale of fintech usage associated with a 1.1 percentage point increase in number of female workers (sample average female employees: 51 percent).

### Digital Payments and Notable Systems
- Pandemic effect: transactions increased by 50 percent between 2019 and 2021.
- Selected national retail payment system metrics:
  - Pix (Brazil):
    - Started operating in 2020.
    - As of December 2022: about 145 million users and 2,890 million transactions per month.
    - 66 percent of transactions are peer-to-peer payments.
    - Average cost to merchants: about 0.2 percent vis-à-vis credit card fees of 2.2 percent.
    - Nearly 800 payment service providers participate; technology companies account for about 10 percent of companies that provide financial services through Pix.
  - CoDi (Mexico):
    - Launched in 2019; by 2022 had 12 million accounts.
    - Uses QR codes and NFC; only licensed financial institutions can access the system.
    - Payments processed instantly, any time, without fees.
  - SINPE Móvil (Costa Rica):
    - Existed since late 2015.
    - In 2022 had about 3.4 million active users vis-à-vis Costa Rica’s population of slightly more than 5 million people.
- Digital remittances:
  - Grew almost threefold in the Caribbean and Central America and twofold in South America between 2017 and 2021, despite a fall in average transaction value.
  - Most digital remittances use e-money or existing infrastructure; blockchain/crypto use limited.

### Digital Banks: Scale, Inclusion, and Risks
- Growth and examples:
  - Nubank (Brazil):
    - Established 2013.
    - Serves 70 million customers in Brazil, Mexico, and Colombia, including more than 5 million first-time credit card or bank account owners and 2 million small businesses.
    - IPO in December 2021 valued at $41 billion.
    - Raised $3.9 billion since inception.
    - Total assets about $19.8 billion in 2021 vis-à-vis the largest bank’s total assets of $389 billion.
  - Neon (Brazil):
    - Founded 2016.
    - Client base increased 50-fold to 10 million between 2017 and 2021.
    - Processes about $1.1 billion transactions a month.
- Risks:
  - Rapid loan portfolio growth during a low global interest rate environment raises questions on credit quality as global rates increase.
  - Vulnerability to liquidity shocks and faster bank runs due to instantaneous transfer capabilities.

### Alternative Finance and Insurtech
- Alternative finance:
  - Volume expanded ninefold between 2017 and 2020 to about $6 billion.
  - Number of alternative finance providers more than quadrupled between 2017 and 2022.
  - Brazil accounted for about two-thirds of alternative finance volume, followed by Chile and Mexico.
  - Table of capital provided by alternative finance providers in LAC, 2013–2020 (selected exact entries preserved):
    - 2013: 0.0; 34; 66
    - 2014: 0.1; 24; 76
    - 2015: 0.1; 31; 69
    - 2016: 0.5; 9; 91
    - 2017: 0.7; 16; 84
    - 2018: 1.8; 5; 95
    - 2019: 5.2; 2; 98
    - 2020: 6.0; 2; 98
  - Importance for MSMEs: in some countries MSME loans on P2P platforms have been the only available financing source; associated with improvements in financial health, productivity, and increased use of savings/checking accounts.
- Insurtech:
  - Insurance penetration: from 1 percent of GDP in Venezuela to about 4 percent in Chile vis-à-vis 9.4 percent in OECD countries.
  - Startups: 28 in 2017 → 127 in 2021 (selected subsector growth); industry report figure: 352 insurtech companies in Latin America in 2021.
  - About half of insurtech clients are SMEs and low-income consumers.
  - Insurtech companies provide technological solutions to a quarter of traditional insurance companies.

### COVID-19: Sector Resilience, Funding, and Risks
- Lending dynamics:
  - Traditional bank lending slowed significantly in 2020–21.
  - Fintech lending, digital payments, and digital banks’ transactions continued strong growth.
- Funding patterns:
  - After a short slowdown early in the pandemic, funding accelerated sharply between Q2 2020 and end-2021.
  - Machine learning analysis finds young fintech startups benefited more from the financing boom than mature ones.
- Risk perceptions from World Bank–CCAF survey (percent reporting perceived increase in risk):
  - Cybersecurity: 78 percent
  - Operational risks: 54 percent
  - Consumer protection: 27 percent
  - Fraud and scams: 18 percent
- Regulatory responses:
  - Around two-thirds of EMDE regulators consider fintech priority increased; 60 percent in advanced economies indicated fintech remains a high priority.
  - Regulators introduced/accelerated innovation offices, regulatory sandboxes (including digital sandboxes), digital infrastructure, and increased use of regtech and suptech.
  - Half of regulators took measures to facilitate AML/CFT via digital tools (including eKYC); about one-third undertook measures related to digital payments and remittances (waived fees, increased limits, etc.).
- Selected product responses to COVID-19 (examples extracted from Table 3):
  - Digital lending: loan facility collaboration between digital lending platform and food delivery service for restaurants in Mexico.
  - Digital lending: two Brazilian platforms intermediated government SME aid loans.
  - Insurtech: Chilean insurtech introduced insurance per kilometer.
  - Digital custody: Colombia and Paraguay partnered with digital wallets to distribute COVID-19 stimulus.
  - Digital payments: a digital payment firm increased remote delivery of digital payment accounts linked to personal loans and money market savings funds (with restrictions on deposits/receiving salaries/state benefits).

### Risks Associated with Fintech (summary)
- Financial stability: potential for losses, faster bank runs, contagion through collaborations, systemic disruption from large-scale failures.
- Financial integrity: cross-border fraud, theft, money laundering risks.
- Market integrity: risks from bigtechs operating across jurisdictions and sectors.
- Cybersecurity: vulnerability to cyberattacks with financial and reputational losses.
- Data privacy: handling of sensitive financial/personal information increases exposure to data breaches.
- Mitigants: Regtech and suptech adoption for compliance and supervision, safeguards (licensing, minimum capital, interoperability, AML/CFT, risk management, consumer protection).

### Policy, Regulation, and Supervisory Tools
- Regulatory approaches (four options):
  - Wait and see
  - Test and learn (innovation hubs and sandboxes)
  - Expanding the perimeter (adapt existing rules)
  - Bespoke regulation (entity- or innovation-specific)
- Activity- versus entity-based regulation in region:
  - Most jurisdictions apply activity-based regulation.
  - Mexico applies entity-based regulation (Fintech Law).
  - Argentina, Brazil, and Colombia have acts or amendments specific to credit, payments, and crowdfunding.
- Nonbank Payment Service Providers (NBPSP): regulatory tools include licensing, minimum capital, safeguards, interoperability, AML/CFT, risk management, cyber security, data protection, consumer protection.
  - Example capital rule: Colombia requires capital for e-money issuance at 2 percent of total payments or transfers in past 12 months.
- Open Banking / Open Finance:
  - Brazil and Mexico have open finance regulation with mandatory models for sharing information with client consent.
  - Chile and Colombia are finalizing/early-stage; Colombia plans a voluntary system.
  - Mexico: open finance included in Fintech Law; regulation by Central Bank and CNBV in 2020 (interoperability, API authentication).
  - Brazil: Central Bank regulates and supervises open finance; 2020 regulation and phased rollout (Phase 1–4 between February and December 2021).
- Crowdfunding:
  - Regulation exists in 16 out of 37 jurisdictions in the region.
  - Reported ranges:
    - Minimum capital: $179,000 in Brazil to $234,000 in Chile; Colombia imposes no minimum capital.
    - Maximum investment for nonqualified investors: $200 in Argentina to $2,700 in Brazil; Colombia: limit as 20 percent of annual revenue or capital.
- Bigtech:
  - Risks: rapid lending expansion, data/reporting gaps, concentration (four bigtechs provide around two-thirds of global cloud services), cross-border complexity.
  - Recommended approach:
    - Short term: bigtech codes of conduct.
    - Long term: hybrid regulation — home supervisors entity-based; host supervisors activity-based.

### Making Regulation Work: Regtech, Suptech, Data, and Capacity
- Regtech and suptech features: cloud-based, APIs, facilitate data management, reporting, AML/CFT, customer due diligence, supervisory analytics.
- Regional examples:
  - Mexico: National Strategy for Financial Inclusion adjusted KYC; CNBV partnered with Regtech for Regulators Accelerator (2017); uses tools for suspicious pattern detection and NLP for name-flagging.
  - Bank of Mexico: web-scraping and text mining for AML and anti-fraud auditing.
  - Colombia: Financial Superintendency promoting local regtech within Fintech division.
- Regtech firms: OriginalMy and Idwall (Brazil); Ceptinel (Chile); Pronus (Colombia).
- Suptech tools in Brazil:
  - ADAM (machine learning): can analyze 3 million exposures in 24 hours (equivalent team of 10 inspectors would take 30 years).
  - EVE (automated inspection tool): automates working paper creation and communications; simulations show it can do the job 200 times faster than inspection teams; piloted in 2020 and shared with other supervisors.
- Implementation constraints: limited data science skills among supervisors; need for improved IT infrastructure and data collection.

### Innovation Hubs and Regulatory Sandboxes: Use and Evidence
- Definitions:
  - Innovation hub: dedicated space inside regulator for open dialogue with innovators.
  - Sandbox: experimental supervised testing environment with temporary regulatory relief.
- Regional counts and uptake:
  - Eight innovation hubs; nine sandboxes reported.
  - Regulatory Sandbox expanded to nonsupervised companies and has 9 pilot projects (status noted for 2022).
  - IDB-Finnovista survey: sandboxes perceived as useful by fintech companies in both countries with and without sandboxes; participation can help firms attract financing.
  - BIS evidence: firms entering the UK regulatory sandbox exhibit higher probability of raising funding and an increase of about 15 percent in average funding relative to non-participants.
- Trade-offs:
  - Innovation hubs: lower resource intensity; require clear objectives and buy-in; can be costly/divert resources.
  - Sandboxes: resource-intensive, hypothesis-led, allow live consumer testing; expensive and reputational risk if regulatory standards lowered.
- Selected promoters and years (innovation hubs and sandboxes listed for multiple countries; examples include Brazil, Mexico, Colombia, Peru, Jamaica, Barbados, Trinidad and Tobago).

### Machine Learning Analysis of Fintech Funding (Annex III)
- Objective: predict firm financing and reveal nonlinear patterns in financing boom during COVID-19 using Crunchbase firm-level data and World Bank country indicators (sample 2010–2022).
- Model and training:
  - XGBoost (gradient boosting trees).
  - 55 features (firm-level and country-level variables).
  - 80 percent training set / 20 percent testing set; training set adjusted for class imbalance.
  - Hyperparameters (from Annex Table 3.1):
    - Alpha: 0
    - Lambda: 0.79
    - Eta: 0.066
    - Gamma: 0.83
    - Max depth: 6
    - Number of estimators: 100
  - Interpretation via SHAP values.
- Key quantitative findings:
  - Higher likelihood of firms receiving financing in 2021 and 2022, conditional on characteristics and macroconditions (SHAP values for 2021 and 2022 larger).
  - Young firms (age < 8) benefited disproportionately in 2021–22.
  - Fintech firms had higher probability of receiving financing in 2021–22 than nonfintech firms, after controls; surge stronger for fintech than nonfintech.
- Funding-stage dynamics and timing (Crunchbase snapshot up to September/October 2022):
  - Series A funding for fintech increased 344 percent from 2019 to 2021 and 495 percent from 2019 to 2022 (up to September) for fintech; comparators for nonfintech were 304 percent and 245 percent respectively.
  - Average deal size increased most strongly for Series A.
  - Temporal funding three-month averages reiterated: $104 million (Dec 2019) → $77 million (May 2020) → $257 million (Jan 2022 peak).

### Regulatory Perceptions and Recent Policy Changes (Annex IV and V)
- Perception of regulatory dialogue (Annex Table 4.1 — percentages preserved exactly):
  - All: Strong openness to dialogue 41.5; Weak openness to dialogue 53.3; No openness to dialogue 5.3
  - Argentina: 22.6; 71.0; 6.5
  - Brazil: 61.9; 32.0; 6.2
  - Chile: 13.7; 78.4; 7.8
  - Colombia: 51.2; 46.3; 2.4
  - Mexico: 45.2; 52.3; 2.8
  - Dominican Republic: 79.0; 15.8; 5.3
  - Peru: 26.0; 70.0; 4.0
  - Costa Rica: 28.6; 57.1; 14.3
  - Ecuador: 14.3; 64.3; 21.4
  - Uruguay: 20.0; 70.0; 10.0
- Selected recent regulatory developments:
  - Brazil:
    - March 2022: Central Bank announced payment-institution-led financial conglomerates (e.g., Nubank) will need to comply with same capital requirements as traditional banks; new regulation (first issued in 2013 updated) to take effect January 2023 and be implemented over eighteen months until January 2025, with simplified rules for new fintech entrants.
    - Open finance phased rollout: Phase 1 February 2021; Phase 2 August 2021; Phase 3 October 2021; Phase 4 December 2021.
  - Colombia:
    - 2021: regulatory sandbox launched with trial periods up to two years; available to supervised and new companies.
    - Open finance early-stage: voluntary model planned; foundational documents (URF technical document and draft decree from Ministry of Finance) issued end-2021 (draft approved July 2022) outlining rules on consumer data transfer, commercialization of personal data with express authorization, and third-party offerings with authorization.

*International Monetary Fund — FINTECH NOTES: The Rise and Impact of Fintech in Latin America — Introduction and Executive Summary*

### Introduction and Executive Summary .....................................................................................

### Introduction and Executive Summary

### I. Fintech Verticals: Trends and Funding
- Presents the main fintech verticals covered:
  - Digital Payments
  - Digital Banks (including neobanks and challenger banks)
  - Alternative Finance by Fintech (including alternative lending and crowdfunding)
  - Insurtech
  - Bigtech
- Examines funding patterns for fintech in the region, including venture capital and private equity funding raised for fintech.
- Figures and tables referenced for this section include:
  - Number of fintech users by segment, fintech startups, firms founded by year, digital payments, digital remittances in the Caribbean and Central America, digital banks in LAC, most valued independent digital banks (2021), alternative finance metrics, insurtechs, and sources of funds for fintech (2018 versus 2020).

### II. Causes and Impact of the Fintech Boom
- Identifies factors fueling the fintech boom in Latin America and the Caribbean.
- Discusses fintech’s macro-critical impact on the financial sector and broader economy.
- References measures of financial development and digital infrastructure (e.g., Internet use and secure server counts) and indicators of financial inclusion and bank interest rate spreads.

### III. Weathering Shocks: COVID-19
- Describes regulatory responses to the pandemic.
- Evaluates whether fintech helped weather the COVID-19 shock.
- Assesses fintech’s access to funding during the pandemic.
- Includes boxed or tabulated material such as examples of new or updated products launched in response to COVID and figures on the impact of the pandemic on fintech risks and activity.

### IV. Good Policies: Controlling Risks and Enabling Growth
- Outlines approaches to fintech regulation in the region and broader regulatory issues, including:
  - Nonbank Payment Service Providers
  - Open Banking and Open Finance
  - Crowdfunding
  - Bigtech
- Discusses practical measures for making regulation effective:
  - Using technology for managing regulatory compliance (Regtech)
  - Collection and processing of data
  - Innovation hubs and regulatory sandboxes (including regional listings)
- Annexes provide focused analysis and case studies:
  - Annex I: Fintech and Competition Among Banks
  - Annex II: Fintech and Inclusion: Evidence from Latin America
  - Annex III: How Venture Capital and Private Equity Funding of Fintech in the Western Hemisphere Was Affected by the COVID-19 Pandemic — firm-level and machine learning analyses (data, methodology, hyperparameter tuning, quantitative results)
  - Annex IV: Views of Fintech Companies of Regulation
  - Annex V: Recent Regulatory Changes in Brazil and Colombia

### Data, Figures, and Tables (selected)
- The chapter references multiple figures and tables to support findings, including:
  - Figures on fintech users, startup counts, funding time series, and sector valuations.
  - Tables on capital provided by alternative finance providers, insurtech deals, innovation hubs, and sandboxes.
  - Annex tables detailing data sources, regressions, fintech and inclusion metrics, and hyperparameter tuning outcomes.

### Glossary (key definitions included verbatim)
- Alternative finance: financial channels and instruments that have emerged outside of the traditional finance system.
- Alternative lending: a form of alternative financing; fintech lending or online lending bypasses traditional intermediaries.
- Artificial intelligence (AI): the application of computational tools to address tasks traditionally requiring human sophistication.
- Digital banks: include neobanks and challenger banks.
- Digital payments: use technology to substitute/avoid cash and transfer payments through digital modes.
- Fintech: the use of technology to deliver financial services and products across payments, transfers, investments, insurance, and lending.
- Fintech vertical: a specific area or segment within the fintech industry.
- Insurtech: technological innovations applied to the insurance industry including tailor-made policies, smart contracts, alternative data, and dynamic pricing.
- Innovation hub: a dedicated space inside the regulator’s office promoting open dialogue between innovators and the regulator.
- Machine learning (ML): a subcategory of AI optimizing actions through experience with limited or no human intervention.
- Neobanks: banks that rely exclusively on digital technologies and often lack physical presence or full banking licenses.
- Regulatory sandboxes: frameworks encouraging fintech experimentation through controlled testing with appropriate safeguards and temporary regulatory forbearance.
- Regtech: use of innovative technology by institutions to meet regulatory requirements.
- Suptech: use of innovative technology by financial authorities to support market oversight, supervision, and data analytics.

*International Monetary Fund — FINTECH NOTES: The Rise and Impact of Fintech in Latin America — Introduction and Executive Summary*

### Introduction and Executive Summary

### Introduction and Executive Summary

### Overview
- In 2021 there were more than 300 million users of digital payments and more than 30 million users of digital banks, mostly concentrated in Brazil and Mexico.
- One of the largest digital banks in the world is in Brazil.
- Fintech verticals in focus: digital payment systems, digital banks, alternative finance, bigtech, insurtech, and regulatory innovations such as suptech, sandboxes, and open banking.

### Key Benefits and Impacts
- Fintech is innovation: transactions that took days now can be completed instantaneously on Mexico’s CoDi, Costa Rica’s SINPE Móvil or Brazil’s Pix payment systems.
- Bank services such as opening an account or getting a loan can now be done online at digital banks.
- Digital wallets are nearly as ubiquitous as cellphones.
- Competition: proliferation of new financial technology and digital banks is associated with a reduction in lending spreads.
- Inclusion: about three-quarters of digital banks’ customers are previously unbanked and underbanked consumers and small and medium enterprises (SMEs).
- Higher fintech adoption is associated with lower income inequality.
- Alternative finance has boosted access to finance for micro, small, and medium enterprises (MSMEs).
- COVID-19 resilience: while lending by traditional banks slowed significantly in 2020–21, fintech lending, digital payments, and digital banks’ transactions continued strong growth; investors significantly increased funding for fintech companies during the pandemic.

### Risks Associated with Fintech
- Financial stability risks:
  - Fintech companies may not be fully equipped to handle market volatility, leading to losses for customers.
  - Instantaneous transfer technologies may boost the speed of bank runs.
  - Collaboration and information sharing between fintechs and other financial institutions could spread failures or disruptions.
  - Large-scale failures could result in widespread disruption to the financial system.
- Financial integrity risks:
  - Fintech platforms could facilitate cross-border fraud, theft, and money laundering.
- Regulatory risks:
  - Regulatory gaps or inconsistencies may negatively affect stability.
- Market integrity risk:
  - Risks emerge from bigtechs located in other jurisdictions with core businesses in nonfinancial sectors (for example, e-commerce).
- Cybersecurity risk:
  - Vulnerability to cyberattacks could result in significant financial losses and reputational damage.
- Data privacy risk:
  - Handling of sensitive financial and personal information makes fintechs prime targets for cybercriminals.
- Risk-mitigating tools:
  - Regtech and suptech are increasingly used by financial authorities and supervisees to manage regulatory compliance and process data.

### Policy and Regulatory Developments
- Policymakers are supporting fintech development through innovation hubs and regulatory sandboxes.
- Open banking and open finance may boost innovation but should be matched with a developing regulatory environment—so far only Brazil and Mexico have it in place.
- This paper is guided by the Bali Fintech Agenda, a set of 12 policy elements to harness fintech benefits while managing risks.
- Explored Bali Fintech Agenda principles include (1) embrace the promise of fintech; (2) enable new technologies to enhance financial service provision; (3) reinforce competition and commitment to open, free, and contestable markets; (4) foster fintech to promote financial inclusion and develop financial markets; (5) monitor developments closely and deepen understanding of evolving financial systems; (6) adapt regulatory framework and supervisory practices for orderly development and stability of the financial system; (7) modernize legal frameworks to provide an enabling legal landscape; (8) ensure the stability of domestic monetary and financial systems.

### Fintech Verticals: Trends and Funding
- Fintech penetration in LAC varies across sectors; largest subsectors by users and transaction volumes are digital payments and digital banking.
- Insurtech and alternative finance are smaller but growing rapidly; insurtech improves risk assessment and product targeting, potentially boosting insurance penetration.
- Alternative finance platforms allow bypassing intermediaries for lending or investing in unlisted companies.
- Growth since 2017:
  - Digital payments grew from $89 billion in 2017 to $215 billion in 2021.
  - Transaction volume of fully online digital banks in LA6 grew from $17 billion in 2017 to $123 billion in 2021.
  - Alternative finance lending expanded from $0.7 billion in 2017 to $6 billion in 2020.
  - Number of insurtech companies operating in Latin America reached 352 in 2021.
- Sectoral composition of fintech startups in 2021:
  - A quarter focused on digital payments and remittances.
  - About a fifth focused on alternative financing (lending) platforms.
  - About a sixth provided services related to enterprise technologies for financial institutions (scoring, identity services, fraud detection).
- B2B fintech startups providing technological solutions to existing financial institutions grew on average by almost 50 percent annually between 2017 and 2021; about half of their revenue comes from digital banks.
- Overall number of fintech startups in LAC peaked in 2017 and has since declined, indicating concentration among incumbents.

### Digital Payments: Trends and Notable Systems
- Digital payments include mobile wallets, mobile payment service apps and QR codes, online-based purchases, and crypto payments.
- Pandemic effect: transactions increased by 50 percent between 2019 and 2021.
- By July 2022, Mercado Libre registered more than 400 million monthly visitors.
- More than 10 percent of e-commerce spending is made using digital wallets.
- Central bank retail payment systems:
  - Pix (Brazil):
    - Started operating in 2020.
    - As of December 2022, had about 145 million users and 2,890 million transactions per month.
    - 66 percent of transactions are peer-to-peer payments.
    - Average cost to merchants is about 0.2 percent vis-à-vis credit card fees of 2.2 percent.
    - Nearly 800 payment service providers participate in Pix; technology companies account for about 10 percent of companies that provide financial services through Pix.
  - CoDi (Mexico):
    - Launched in 2019; by 2022 had 12 million accounts.
    - Uses QR codes and NFC; only licensed financial institutions can access the system.
    - Payments are processed instantly, any time, without fees.
  - SINPE Móvil (Costa Rica):
    - Existed since late 2015.
    - In 2022 had about 3.4 million active users vis-à-vis Costa Rica’s population of slightly more than 5 million people.
- Digital remittances:
  - Grew almost threefold in the Caribbean and Central America and twofold in South America between 2017 and 2021, despite a fall in average transaction value.
  - Most digital remittances are sent using e-money or existing infrastructure; blockchain and crypto use for remittances is limited.

### Digital Banks: Scale, Inclusion, and Risks
- Definition: a digital bank operates online with no physical presence and provides services previously available only at a bank branch.
- Growth:
  - Number of digital banks in the region grew from 10 in 2017 to 60.
  - 55 of the 60 digital banks are in Mexico and Brazil.
- Customer base:
  - About three-quarters of digital banks’ customers are unbanked and underbanked consumers and SMEs.
- Concentration and examples:
  - Nubank (Brazil):
    - Established in 2013.
    - Serves 70 million customers in Brazil, Mexico, and Colombia, including more than 5 million first-time credit card or bank account owners and 2 million small businesses.
    - Completed an IPO in December 2021 valued at $41 billion.
    - Raised $3.9 billion since inception.
    - Total assets were about $19.8 billion in 2021 vis-à-vis the largest bank’s total assets of $389 billion.
  - Neon (Brazil):
    - Founded in 2016.
    - Between 2017 and 2021 client base increased 50-fold to 10 million.
    - Processes about $1.1 billion transactions a month.
- Risks:
  - Rapid loan portfolio growth during a low global interest rate environment raises questions on credit quality as global rates increase.
  - Vulnerability to liquidity shocks and faster bank runs due to technology enabling instantaneous transfers and withdrawals.

### Alternative Finance by Fintech
- Composition: debt-based platforms (peer-to-peer lending), equity-based platforms (investment in unlisted shares), and reward- or donation-based crowdfunding.
- Growth:
  - Volume expanded ninefold between 2017 and 2020 to about $6 billion.
  - Number of alternative finance providers more than quadrupled between 2017 and 2022.
  - Lending platforms accounted for most growth; capital-raising platforms remained small.
  - Brazil accounted for about two-thirds of alternative finance volume, followed by Chile and Mexico.
- Table of capital provided by alternative finance providers in LAC, 2013–2020 (Total capital raising, In billions of dollars; Lending, Percent of total):
  - 2013: 0.0; 34; 66
  - 2014: 0.1; 24; 76
  - 2015: 0.1; 31; 69
  - 2016: 0.5; 9; 91
  - 2017: 0.7; 16; 84
  - 2018: 1.8; 5; 95
  - 2019: 5.2; 2; 98
  - 2020: 6.0; 2; 98
- Importance:
  - Alternative finance has been critical for MSME access to finance; in some countries, MSME loans on P2P platforms have been the only available financing source.
  - Use of alternative finance is associated with improvements in MSMEs’ financial health and productivity and increased use of savings and checking accounts.

*Source: ftnea2023003 - Introduction and Executive Summary*

### 1. Startups in Alternative Finance

### 1. Startups in Alternative Finance

### Insurtech: market potential and dynamics
- Insurance penetration in the region: from 1 percent of GDP in Venezuela to about 4 percent in Chile vis-à-vis 9.4 percent in OECD countries.
- Most people in Latin America do not have life insurance, and 70 percent of cars operate without insurance.
- Insurtech value propositions: targeted products, process efficiency, alternative data usage, accessibility via digital means.
- Growth in number of startups in the subsector: increased from 28 in 2017 to 127 in 2021.
- Industry report figure: 352 insurtech companies were in Latin America in 2021.
- Client composition and market integration:
  - About half of insurtech companies’ clients are small and medium enterprises and low-income consumers.
  - Insurtech companies provide technological solutions to a quarter of all traditional insurance companies.
- Selected deal and funding snapshots (as presented):
  - Table 2 entries (as shown):  
    - Brazil: 27 0 12 305 ...  
    - Chile: 14 4 15 123 158  
    - Mexico: 13 1 18 24 1  
    - Argentina: 2 2 25 3 10  
    - Colombia: 2 0 27 2 ...  
    - Peru: 1 0 28 2 ...  
    - El Salvador: 0 1 28 0 2  
  - Memorandum items (as shown):  
    - US: 1,124 67 1 26,500 970  
    - Canada: 46 3 7 219 100

### Bigtech entry and implications
- Definition: large technology conglomerates with extensive customer networks and core business across markets (examples given in text).
- Bigtech business model contrast: reverse the unbundling of financial services by providing a wide range of financial services within one group, leveraging large proprietary data sets and advanced analytics (AI, machine learning).
- Regional examples of bigtech-style expansion: Rappi and MercadoLibre offering payment services, credit cards, and savings accounts via bank partnerships.
- Benefits and risks: higher access to formal credit but potential creation of systemic risks through rapid credit expansion and increased interconnectedness with financial institutions.

### Funding trends for fintech in LAC
- Shift in funding sources: from angel investors and family and friends toward risk capital and accelerators/incubators.
- Average monthly venture capital and private equity funding for fintech: rose from $38 million in 2015 to $90 million in 2019.
- Surge in venture capital and private equity funding during the pandemic period (2020–21).
- External financing prevalence:
  - Among fintechs analyzed in the IDB 2022 study, about two-thirds reported receiving external support (compared with half in 2018).
  - About a quarter relied on local funds.
  - LAVCA 2022 report: $6.1 billion in external investments in Latin American fintech across 258 transactions in 2021.
- Investor size distribution (as reported): two-thirds of those investing in fintech invest less than $0.5 million, about a third invest between $0.5 and $5 million, and about 10 percent of investors invest more than $5 million.

### Causes fueling the fintech boom
- Three key factors identified:
  1. Limited access to finance from banks and insufficient competition among banks.
  2. Improvements in digital infrastructure.
  3. Access to venture capital.
- Financial development and access:
  - Between 2016 and 2019, LAC caught up with emerging market economies in financial development but remained behind emerging Asia.
  - High interest rate margins signaled limited access to finance; contributing factors include high operational costs, high perceived risk, and limited competition.
  - SMEs’ financing gap reached $1 trillion by 2020.
- Digital infrastructure:
  - Internet use: 74 percent of the population using the internet in 2019, compared with 34 percent in 2010.
- Tecnolatinas ecosystem (as described): 1,005 locally owned technology-based private companies by 2021, creating $221 billion of value, 245,000 jobs, and raising $28 billion in capital; fintech and e-commerce account for nearly three-quarters of the ecosystem value; one in five tecnolatinas works in fintech, collectively raising one-third of the $28 billion.

### Macro-critical impacts of fintech and inclusion effects
- Fintech addresses barriers to financial inclusion identified by World Bank and UNCTAD: insufficient income, use of a relative’s account, unaffordability, distance, documentation requirements, lack of trust, religious reasons; disproportionate effects on the poor, women, youth, rural populations, informal workers, and migrants.
- Fintech services to underserved markets:
  - More than one-third of all fintech companies in LAC serve those excluded from the formal financial system.
  - The three fintech segments most focused on previously unbanked clients: lenders to enterprises, lenders to consumers, and digital banking.
  - Two-thirds of digital banks’ loans go to under- and nonbanked consumers and SMEs.
  - The number of startups focused on financially underserved markets has been growing at an average annual rate of 19.3 percent since 2017.
- Financial education and gender progress:
  - In 2021, two-thirds of fintech companies reportedly offered tools for financial education, evaluation, and improvement to clients.
  - Share of fintech startups with female funders/cofounders has increased by a seventh.
  - Share of female fintech customers was up by approximately a third.
  - Share of fintech companies with equal gender parity in the labor force more than doubled from about 6 to 15 percent since 2018; share of fintech companies with no females among the labor force shrunk by 4 percentage points to 12 percent.
- Quantified impacts on market metrics:
  - An increase in the ratio between digital banks’ transactions and total banks’ loans by 1 percentage point in EMDEs and LAC is associated with a reduction in net interest margin by 0.2 to 1.9 percentage points.
  - Between 2017 and 2020, interest rate margins declined by about 13 percentage points in Brazil.
  - Using coefficients for the EMDEs sample, the model suggests that an increase in digital banks’ activity reduced interest rate margins in Brazil by 3 percentage points.
- Distributional and labor market associations:
  - Fintech adoption is associated with a lower income share of the top 10 percent and a lower Gini coefficient.
  - Fintech adoption is associated with a higher level of female employment.

### Regulatory responses and fintech during COVID-19
- Pandemic effects on sector dynamics:
  - While lending from traditional banks slowed in 2020, fintech lending continued exponential growth.
  - A funding glut in the second half of 2020–21 boosted fintech growth.
  - Fintech firms’ mobile technologies and new portfolios increased resilience during the pandemic.
- Regulatory prioritization and innovation:
  - World Bank-CCAF survey: COVID-19 generally increased the prioritization of fintech for regulators.
  - Around two-thirds of regulators in EMDEs consider that the priority of fintech has increased.
  - 60 percent in advanced economies indicated that fintech remains a high priority.
  - Regulators introduced or accelerated innovation offices, regulatory sandbox initiatives (including digital sandboxes), and digital infrastructure; regtech and suptech usage increased.
- AML/CFT and onboarding measures:
  - Half of regulators took measures to facilitate AML/CFT requirements using digital tools, including facilitating or permitting electronic KYC (eKYC).
  - Measures included facilitation of digital onboarding.
  - About one-third of regulators undertook at least one measure related to digital payments and remittances (examples: waiving transaction fees partially or wholly; increasing transaction limits/thresholds; increases in daily maximum account balance and wallet limits; increases in contactless payment and mobile money limits).
- Examples of fintech products introduced or updated in response to COVID-19 (from Table 3):
  - Digital lending: Credit or microcredit facility — a digital lending platform and a food delivery service collaborated to offer a loan facility to restaurants in Mexico.
  - Digital lending: New products and services — two Brazilian platforms joined the governments’ program to aid SMEs during the pandemic as intermediaries/facilitators to deliver loans.
  - Insurtech: New products and services — an insurtech from Chile introduced insurance per kilometer to address changing mobility habits.
  - Digital custody: Participation in COVID-19 relief measures — governments of Colombia and Paraguay partnered with digital wallets to distribute COVID-19–related stimulus.
  - Digital payments: New products and services — a digital payment firm greatly increased remote delivery of digital payment accounts linking to personal loans and money market savings funds (not permitted to take deposits or receive customers’ salaries or state benefits directly into the account).

*Source: FINTECH NOTES — The Rise and Impact of Fintech in Latin America (selected excerpts).*

### 1. In billions of dollars 2. Year-on-year percent change

### ftnea2023003 - 1. In billions of dollars 2. Year-on-year percent change

### Fintech’s Access to Funding
- After a short slowdown at the outset of the COVID-19 pandemic, funding to fintech startups accelerated sharply between the second quarter of 2020 and the end of 2021.
- Three-month moving average of total monthly funding (selected values reported in the source):
  - $104 million in December 2019
  - $77 million in May 2020
  - $257 million in January 2022 (peak)
  - $152 million in May 2022
  - $222 million in October 2022
- Machine learning analysis (Annex III) finding: young fintech startups benefited more from the financing boom than mature ones.

### Pandemic Effects and Risk Perceptions
- The acceleration of digital financial services during the COVID-19 pandemic heightened risks.
- World Bank and Cambridge Centre for Alternative Finance Survey results on perceived risk increases during the pandemic:
  - Cybersecurity: 78 percent
  - Operational risks: 54 percent
  - Consumer protection: 27 percent
  - Fraud and scams: 18 percent
- Fintech expansion increased systemic risks and amplified operational, data, and consumer protection risks similar to those in the traditional financial system.

### Policymaker Roles and Risk Areas
- Policymakers play two major roles:
  - Setting regulation for digital sandboxes, digital ID, open banking, and innovation facilitators.
  - Addressing risks stemming from fintech in six areas: (1) financial stability, (2) financial integrity, (3) cybersecurity, (4) consumer and data protection, (5) data provision, and (6) market integrity.

### Approaches to Fintech Regulation
- Four regulatory options for authorities:
  - Wait and see
  - Test and learn (innovation hubs and sandboxes)
  - Expanding the perimeter (adapting existing rules)
  - Bespoke regulation (entity- or innovation-specific rules)
- In Latin America:
  - Most jurisdictions apply activity-based regulation.
  - Mexico applies entity-based (entity) regulation, granting licenses to financial technology institutions.
  - Argentina, Brazil, and Colombia have acts or amendments specific to credit, payments, and crowdfunding.

### Nonbank Payment Service Providers (NBPSP)
- Rapid growth of NBPSP increases risks in fund protection, digital exclusion, and market concentration.
- Regulatory tools applied (differentiated or across the board): licensing, minimum capital, safeguards, interoperability, AML/CFT, risk management and cyber security, data protection, consumer protection.
- Country examples:
  - Brazil: general license framework; requires interoperability for e-money issuance, acquiring, and payment initiation services.
  - Mexico: limited (payment) license; nonbank institutions can issue e-money, including in foreign currency.
  - Colombia: capital requirement for e-money issuance is 2 percent of total payments or transfers in the past 12 months.

### Open Banking and Open Finance
- Open banking: consumers share transaction and account data from bank accounts to regulated third parties for specific purposes.
- Open finance: consumer-permissioned data from a broader set of financial accounts (investment accounts, small business accounts, crypto wallets, fintech apps).
- Regulation principles required: data access and data sharing, data portability, data interoperability.
- Regional status:
  - Brazil and Mexico: have open finance regulation with mandatory models for sharing information with client consent.
    - Mexico: open finance included in the Fintech Law; subsequent regulation by the Central Bank and CNBV in 2020 (interoperability, authentication mechanisms for APIs).
    - Brazil: staged development; Central Bank regulates and supervises open finance; 2020 regulation issued covering mandatory participants, scope of data and services, requirements, governance; included as a priority in the first cycle of the Central Bank regulatory sandbox.
  - Chile and Colombia: finalizing regulations for open finance.
    - Colombia plans a voluntary system (contrasting with mandatory models in Brazil and Mexico).

### Crowdfunding
- Regulation for crowdfunding (debt and equity) exists in 16 out of 37 jurisdictions in the region.
- Typical regulatory requirements: minimum capital, maximum investment, maximum subscription; additional requirements on information disclosure, minimum liquidity, insurance.
- Reported ranges and limits:
  - Minimum capital: $179,000 in Brazil to $234,000 in Chile; Colombia imposes no minimum capital requirement but has strong asset management and operational/infrastructure risk requirements.
  - Maximum investment for nonqualified investors: $200 in Argentina to $2,700 in Brazil; Colombia: limit established as 20 percent of the annual revenue or capital.

### Bigtech Expansion and Risks
- Existing fintech regulation has enabled bigtech expansion in the region; examples of enabling measures include faster payments systems and open banking initiatives.
- Pandemic-era regulatory response example: Central Bank of the Republic of Argentina published guidelines for cyber-incident response and recovery in April 2021.
- Risks from bigtech activity:
  - Excessive debt from rapid lending expansion to individuals and small businesses.
  - Data gaps due to activities not captured by existing reporting requirements.
  - Concentration risks: four bigtechs provide around two-thirds of global cloud services.
  - Cross-border complexity and the need for tailored regulatory responses.
- Recommended approach (Bali Fintech Agenda principles):
  - Short term: bigtech codes of conduct to manage spillover risks.
  - Long term: hybrid regulation—home supervisors establish entity-based regulation for bigtech groups; host supervisors apply activity-based regulation.

### Making Regulation Work: Regtech and Suptech
- Regtech (by firms) and suptech (by supervisors) improve compliance and supervisory effectiveness.
- Common features: cloud-based, use application programming interfaces, facilitate data management, reporting, AML/CFT, and customer due diligence.
- Regional adoption examples:
  - Mexico: leader in regtech; National Strategy for Financial Inclusion adjusted KYC to facilitate account opening; CNBV partnered with Regtech for Regulators Accelerator in 2017; uses tools to detect suspicious patterns and experiments with NLP tools for name-flagging related to money-laundering.
  - Bank of Mexico: uses web-scraping and text mining for AML and anti-fraud auditing of promotional materials and prospectuses.
  - Colombia: Financial Superintendency launched an initiative to promote local regtech development within its Fintech division.
- Regtech firm examples:
  - Brazilian OriginalMy and Idwall (fraud and identity verification)
  - Chilean Ceptinel (fraud prevention and regulatory compliance)
  - Colombian Pronus (risk and compliance management for financial, legal, mining, and infrastructure sectors)
- Suptech tools in Brazil:
  - ADAM (machine learning tool): can analyze 3 million exposures to customers in just 24 hours; a team of 10 experienced inspectors would take 30 years to do the same.
  - EVE (automated end-to-end inspection tool): automates working paper creation and drafting of communications; simulations showed the tool can do the job 200 times faster than inspection teams; piloted in 2020 and made available to other supervisors.
- Implementation challenges: limited data science skills among supervisors; need for improved IT infrastructure and data collection practices.

### Data Collection, Privacy, and Regulatory Balance
- Financial sector collects personal data for business and regulatory purposes (customer ID, suspicious activity detection, due diligence, monitoring).
- Data frameworks should balance privacy, innovation, competition, consumer protection, financial integrity, and financial stability and require inter-agency cooperation.
- Data sharing for regulatory purposes must balance privacy protection with public policy objectives like criminal law enforcement.

### Innovation Hubs and Regulatory Sandboxes
- Definitions:
  - Innovation hub: dedicated space inside the regulator to promote open, informal dialogue with innovators.
  - Sandbox: experimental space allowing temporary operation under supervision to test products.
- Trade-offs:
  - Innovation hubs: lower resource intensity than sandboxes; useful for rapidly growing ecosystems; require feasibility studies, clear objectives, organizational buy-in; can be costly and divert resources.
  - Sandboxes: resource-intensive, hypothesis-led, allow live testing with real consumers; expensive and require significant resources for a small number of firms; reputational risk if regulatory standards are lowered.
- Regional counts reported in the source:
  - Eight innovation hubs
  - Nine sandboxes
- Examples and experiences:
  - Brazil: Laboratório de Inovação Financeira e Tecnológica (LIFT) with LIFT Labs (annual since 2018), LIFT Learning (partnerships with universities), and LIFT Challenge (MVP-focused challenges).
  - Mexico: CNBV Sandbox Challenge—6 (out of 166) projects approved in areas including fiduciary, capital markets, and crypto assets.
  - Colombia: Supervisor Sandbox started in 2019; had a total of 18 pilot projects, of which 8 were in tryout in early stages.

*Source: FINTECH NOTES — The Rise and Impact of Fintech in Latin America, INTERNATIONAL MONETARY FUND.*

### 2022. The second one (Regulatory Sandbox) was expanded to nonsupervised companies and has 9 pilot

### ftnea2023003 - 2022. The second one (Regulatory Sandbox) was expanded to nonsupervised companies and has 9 pilot

### Regulatory Sandboxes and Uptake
- The Regulatory Sandbox was expanded to nonsupervised companies and has 9 pilot projects.
- According to the IDB-Finnovista survey, fintech companies perceive sandboxes as a useful and needed tool for regulation in both countries that already have them (such as Brazil and Colombia) and those that do not (such as Panama and Honduras).
- Fintech companies in credit scoring, payments and remittances, asset management, digital banking, and corporate lending give a high relevance to regulatory sandboxes.
- Participating in a sandbox can help firms attract financing.
- A BIS paper finds that firms entering the United Kingdom's regulatory sandbox have a higher probability of raising funding and an increase of about 15 percent in the average amount of funding raised relative to firms that do not enter.
- Results suggest that sandboxes improve access to funding through two channels: reducing information asymmetries and lowering regulatory costs.

### Innovation Hubs and Sandboxes (Selected country promoters and years)
- Innovation Hubs (selected entries):
  - Argentina: National Securities Commission, 2022
  - The Bahamas: Securities Commission of the Bahamas, 2019
  - Brazil: Securities and Exchange Commission, 2016
  - Colombia: Financial Superintendency, 2020
  - Costa Rica: CONASSIF, SUGESE, SUGEVAL, SUPEN, SUGEF, Central Bank, 2022
  - El Salvador: Financial Superintendency, 2021
  - Guatemala: Banks Superintendency, 2019
  - Dominican Republic: Central Bank, Bank Superintendency, Capital Markets Superintendency, Pensions Superintendency, and Insurance Superintendency, 2022
- Sandboxes (selected entries):
  - Barbados: Central Bank of Barbados and Financial Service Commission, 2018
  - Brazil: Central Bank of Brazil, 2020
  - Brazil: Private Insurance Superintendency, 2020
  - Brazil: Securities and Exchange Commission, 2020
  - Colombia: Financial Superintendency, 2020
  - Jamaica: Bank of Jamaica, 2020
  - Mexico: National Commission of Banking and Securities, 2018
  - Peru: Banks and Insurance Superintendency, 2021
  - Trinidad and Tobago: Central Bank, Financial Intelligence Unit, and Securities Exchange Commission, 2021

### Fintech and Competition Among Banks — Key Findings
- Fintech companies address limited access to finance in Latin America by competing with banks and providing incentives for banks to acquire new technologies.
- Bank responses:
  - Smaller banks tend to compete by price and reduce interest margins.
  - Larger banks tend to be more reluctant to reduce interest margins and instead increase investment in technologies.
- Historical net interest margin context:
  - Average net interest margin in advanced economies between 2000 and 2012: 3 percent.
  - Average net interest margin in EMDEs between 2000 and 2012: almost 7 percent.
  - Average net interest margin in Latin America and the Caribbean between 2000 and 2012: 9 percent.
- Fintech sector scale:
  - Transaction volume of fully online digital banks in LA6 reached $123 billion in 2021.
  - Digital banks had more than 30 million users, mostly concentrated in Brazil and Mexico.
  - Alternative finance industry expanded to $6 billion in 2020.
- Empirical model (specified):
  - NIM_{ict} = α_i + β_t + δ X_{ict} + θ Z_{ct} + γ FT_{ct} + ε_{ict}
  - NIM = net interest margin; FT_{ct} uses digital banks’ transactions (Statista) in main specification.
- Estimated effect of digital banks’ transactions:
  - An increase in digital banks’ transactions by one standard deviation is associated with a reduction in net interest margin in EMDEs and Latin America and the Caribbean by 0.2 to 2.7 percentage points.
  - Results robust across samples and specifications (fintech variable in levels, growth rates, and lag).
- Annex Table 1.1 (selected data medians and std. dev.):
  - NetiInterest income/average earning assets: Obs. 244584, Median 3.13, Std. dev. 2.59
  - Net fees and commissions/average earning assets: Obs. 244584, Median 0.87, Std. dev. 3.53
  - Personnel expenses/average earning assets: Obs. 244584, Median 1.76, Std. dev. 2.49
  - Other operating expenses/average earning assets: Obs. 244584, Median 2.19, Std. dev. 5.30
  - Liquid assets/total assets: Obs. 244530, Median 18.15, Std. dev. 26.05
  - Equity/total assets: Obs. 244582, Median 12.03, Std. dev. 29.95
  - Impaired loans (NPLs)/gross loans: Obs. 185473, Median 4.60, Std. dev. 52.05
  - Gross domestic product, constant prices, percent change: Obs. 243295, Median 1.98, Std. dev. 3.20
  - Consumer prices, period average, percent change: Obs. 243109, Median 3.86, Std. dev. 240.21
  - Digital banks' transactions to total banks' loans: Obs. 55445, Median 1.18, Std. dev. 1.43
- Annex Table 1.2 (coefficient on digital banks' transactions):
  - Advanced economies: –0.057***
  - Emerging market and developing economies: –0.162***
  - Latin America and Caribbean: –1.862***
  - Year fixed effect: Yes; Bank fixed effect: Yes
  - N: 298805 (Advanced economies), 7041 (EMDEs), 322 (Latin America and Caribbean)

### Fintech and Inclusion: Evidence from Latin America — Key Results
- Research question: Effect of fintech adoption on gender inequality and income inequality in Latin America using 2010–2019 cross-country data.
- Specification: Inequality_{i,t} = β0 + β1 Fintech_{i,t−1} + β2 X_{i,t−1} + μ_t + ε_{i,t}, where Fintech measured by volume of alternative finance; controls include ln GDP per capita, inflation, trade openness, debt level, institutional quality; explanatory variables lagged by one year.
- Main findings:
  - Fintech development is associated with lower income inequality (negative correlation with Gini coefficient).
  - Fintech adoption associated with reduction in top income shares and increase in bottom 50 percent income share.
  - Relationship between fintech development and income inequality is nonlinear (coefficient on fintech squared statistically significant).
  - Fintech adoption associated with higher female employment:
    - A 1 percent increase in the scale of fintech usage is associated with a 1.1 percentage point increase in the number of female workers during the sample period.
    - Sample average percentage of female employees: 51 percent.
  - Coefficient on male employment is significant but smaller in magnitude than female employment.
- Annex Table 2.1 (selected coefficients and significance):
  - Fintech on Gini coefficient: –2.100*** (standard error 0.688)
  - Fintech squared on Gini: 0.083*** (0.025)
  - Fintech on Top 1% income share: –0.021*** (0.005)
  - Fintech on Top 10% income share: -0.033*** (0.007)
  - Fintech on Bottom 50% income share: 0.009*** (0.003)
  - Fintech on Female employment: 1.049*** (0.400)
  - Observations: 150 (Gini), 155 (Top 1%), 155 (Top 10%), 155 (Bottom 50%), 154 (Female employment)
  - R-squared: 0.239 (Gini), 0.351 (Top 1%), 0.345 (Top 10%), 0.238 (Bottom 50%), 0.269 (Female employment)
- Robustness and consistency:
  - Findings consistent with literature cited (Asongu and Nwachukwu (2018); Chinoda and Mashamba (2021); Loko and Yang (2022)).

### Venture Capital and Private Equity Funding of Fintech during COVID-19 — Firm-Level Evidence
- Data source: Crunchbase (firm-level venture capital and private equity funding for fintech startups).
- Overall pattern:
  - Venture capital and private equity funding of fintech companies surged in the second half of 2020 and 2021 and peaked in the first half of 2022.
  - The total amount of funding increased, as did funding for Series A, Series B, and Series C.
- Temporal funding details:
  - Average monthly funding (sum of Series A, B, and C) increased from $38 million in 2015 to $90 million in 2019.
  - Early pandemic decline: total monthly funding declined from $104 million in December 2019 to $77 million in May 2020.
  - Subsequent surge with a peak of $257 million in January 2022.
  - Funding eased to $152 million in May 2022, then rebounded to $236 million in September 2022.
  - Analysis stops in September 2022 (Crunchbase snapshot taken in October 2022).
- Deal-stage details:
  - Surge occurred for Series A, B, and C; strongest for Series A.
  - Average deal size increased, most strongly for Series A.
  - Total funding for Series A increased by 344 percent from 2019 to 2021 and by 495 percent from 2019 to 2022 (up to September) for fintech, compared with 304 percent and 245 percent, respectively, for nonfintech.
- Interpretation:
  - Machine learning analysis indicates fintech firms had a higher probability of receiving financing in 2021 and 2022 even after controlling for proxies of financial conditions.
  - Higher probability likely reflected optimism about fintech sector prospects rather than only global funding conditions.

*International Monetary Fund*

### Annex Figure 3.3. LAC: Total Amount Raised for Fintech in Series A (USD million)

### ftnea2023003 - Annex Figure 3.3. LAC: Total Amount Raised for Fintech in Series A (USD million)

### Machine learning analysis: purpose and scope
- Objective: use machine learning (ML) tools to reveal nonlinear patterns in the financing boom during the COVID-19 pandemic and predict whether a firm receives financing.
- Data source: Crunchbase (firm-level characteristics and funding timelines); country-level variables from World Bank Development Indicators.
- Sample: fintech companies with self-identified industries including fintech, big data, peer to peer, virtual currency, crowdfunding, payments, insurtech, bitcoin, blockchain, cybersecurity, machine learning.
- Geographic/sample period: countries in Latin America and the Caribbean; sample period between 2010 and 2022.
- Features used: 55 indicators including firm-level characteristics (age, industry dummies, total financing raised), country-level indicators (GDP growth, inflation, change in currency value, changes of the Federal Reserve System and the European Central Bank balance sheets based on their period averages, policy rate, domestic credit in US dollars), and multiple financial condition indicators.

### Empirical methodology and training details
- ML model: XGBoost (gradient boosting trees ensemble).
- Treatment of sample:
  - 80 percent of the sample used for a training set and the remaining 20 percent for a testing set.
  - Observations randomly assigned to two groups.
  - Because only 20 percent of firm-year pairs had a financing deal, the training set is adjusted to be more balanced; the testing set is left as is.
- Hyperparameter tuning:
  - Fivefold cross validation and Bayesian optimization were used to tune hyperparameters.
  - Tuned hyperparameters listed in Annex Table 3.1:
    - Alpha (L1 regularization term): 0
    - Lambda (L2 regularization term): 0.79
    - Eta (Learning rate): 0.066
    - Gamma (minimum loss reduction required to make a further partition on a leaf node of the tree): 0.83
    - Max depth: 6
    - Number of estimators: 100
- Model interpretation: SHAP values (SHapley Additive exPlanations) used to attribute the change in expected model prediction to each feature; higher SHAP values imply a higher likelihood the model predicts the firm would receive funding.

### Quantitative results and substantive findings
- Temporal effects:
  - The ML analysis suggests firms had a higher probability of receiving financing in 2021 and 2022 than in other years, after controlling for firm characteristics and macroconditions.
  - Annex Figure 3.4 shows SHAP values for year dummies; SHAP values of 2021 and 2022 are larger than those of other years. Low values for 2010 and 2011 likely reflect the impact of the global financial crisis.
- Age effects:
  - Young firms benefited disproportionately from the financing boom in 2021 and 2022.
  - Annex Figure 3.5: for the 2021 dummy, firms of lower ages (those below 8) have more dispersed SHAP values, and this pattern continues for 2022; in both years, firms with the highest probability of receiving financing are young firms (age < 8 vs age ≥8).
- Fintech-specific effects and robustness:
  - Fintech firms had a higher probability of receiving financing in 2021 and 2022 than in other years, after controlling for proxies of financial condition.
  - Annex Figure 3.6 shows distributions of SHAP values for fintech firms for 2021 and 2022 year dummies; the positive SHAP values of 2021 and 2022 shown in Annex Figure 3.4 are not driven by nonfintech firms.
  - The stronger surge of venture capital/private equity financing for fintech firms in 2021–22 compared with nonfintech firms supports the argument that fintech-specific factors played a role in the 2021–22 fintech financing surge, in addition to a global funding boom.
- Caveat on Crunchbase nonfintech financing:
  - Total financing of nonfintech firms reported by Crunchbase is shown with the caveat that their main financing source should not be venture capital or private equity; selection bias could create an upward bias for reported VC/PE financing for nonfintech firms.

### Regulatory views and survey evidence (Annex IV)
- Overall perception of regulatory adequacy and dialogue:
  - Surveys (IDB 2022) find regulation still has room to improve across the region, even in countries with a high presence of fintech.
  - Two-thirds of Brazilian companies consider that regulation is adequate; perception in Argentina and Mexico is close to the region’s average; Colombia and Chile are below average.
  - In less mature fintech markets the proportion that perceive regulation as adequate is lower, except Uruguay.
  - Regulation perceived as better by companies in personal finance, insurance, consumer lending, crowdfunding, and digital banking; less favorable for trading, asset management, wealth management, and corporate lending businesses.
  - More than half of companies think regulators have a weak openness to dialogue.
- Annex Table 4.1 — Perception of the Quality of the Dialogue with Regulators of the Fintech Ecosystem (percentages preserved exactly):
  - All: Strong openness to dialogue 41.5; Weak openness to dialogue 53.3; No openness to dialogue 5.3
  - Argentina: 22.6; 71.0; 6.5
  - Brazil: 61.9; 32.0; 6.2
  - Chile: 13.7; 78.4; 7.8
  - Colombia: 51.2; 46.3; 2.4
  - Mexico: 45.2; 52.3; 2.8
  - Dominican Republic: 79.0; 15.8; 5.3
  - Peru: 26.0; 70.0; 4.0
  - Costa Rica: 28.6; 57.1; 14.3
  - Ecuador: 14.3; 64.3; 21.4
  - Uruguay: 20.0; 70.0; 10.0

### Recent regulatory changes and policy developments (Annex V)
- Brazil:
  - March 2022: Central Bank announced financial conglomerates led by payment institutions (such as Nubank) will need to comply with the same capital requirements of traditional banks.
  - New regulation (first issued in 2013 updated) will take effect in January 2023 and be gradually implemented over the next eighteen months until January 2025; it extends regulatory requirements used for conglomerates led by financial institutions to conglomerates led by payment institutions (IPs), varying according to size and complexity.
  - Under the new approach, IPs should gradually increase their amount of capital and exclude assets with a low capacity to absorb capital losses in times of stress, as is already the case with banks.
  - The new regulation mainly affects payment institutions with strong growth (example cited: Nubank); simplified rules will be kept for new fintech entrants.
  - Open banking / open finance timeline and phases (Brazil):
    - Open finance project entered into operation in February 2021.
    - Phase 1 (February 2021): participating institutions provide standardized information about service channels and characteristics of traditional banking products (deposits, savings accounts, credit).
    - Phase 2 (August 2021): sharing of customer registry and transactional data for the same traditional banking services (account, credit card, credit operations).
    - Phase 3 (October 2021): institutions could initiate payments (starting with Pix) and make personalized credit proposals to clients who voluntarily shared their information.
    - Phase 4 (December 2021): participants must provide standardized information on non-traditional banking services (insurance, open pension funds, investment and foreign exchange) and evolve to allow sharing of transaction data on those services.
- Colombia:
  - 2021: government launched a regulatory sandbox for fintech companies with trial periods of up to two years; goals include promoting innovation, protecting financial consumers, encouraging compliance, and preventing regulatory arbitrage; sandbox available to supervised and new companies.
  - Open finance regulation at an early stage; model will be voluntary and contemplates inclusion of data from other financial institutions beyond banks.
  - End of 2021: government issued two foundational documents for open finance:
    - A technical document from the Financial Regulation Unit (URF) describing general rules to implement open finance and suggesting regulatory intervention.
    - A draft decree from the Ministry of Finance and Public Credit on open finance (approved in July 2022) specifying rules around transfer of consumer data between financial entities, emphasizing that supervised entities may commercialize the use, storage, and circulation of personal data with express authorization from the data owner, and may offer third-party products and services in their channels with previous authorization in their connection operations.

*Source: ftnea2023003 - Annex Figure 3.3. LAC: Total Amount Raised for Fintech in Series A (USD million); IMF staff calculations; Crunchbase; World Bank Development Indicators; IDB (2022).*

### References

### ftnea2023003 - References

### IMF and Working Papers
- Appendino, M., O. Bespalova, R. Bhattacharya, JF. Clevy, N. Geng, T. Komatsuzaki, J. Lesniak, W. Lian, S. Marcelino, M. Villafuerte, Y. Yakhshilikov. 2023. “Crypto Assets and CBDCs in Latin America and the Caribbean.” IMF Working Paper 23/37, International Monetary Fund, Washington, DC.
- Berkmen, Pelin, Kimberly Beaton, Dmitry Gershenson, Javier Arze del Granado, Kotaro Ishi, Marie S. Kim, Emmanuel Kopp, and Marina Rousset. 2019. “Fintech in Latin America and the Caribbean: Stocktaking.” IMF Working Paper 19/71, International Monetary Fund, Washington, DC. https://www.imf.org/en/Publications/WP/Issues/2019/03/26/Fintech-in-Latin-America-and-the-Caribbean-Stocktaking-46677.
- Bersch, Julia, Jean Francois Clevy, Naseem Muhammad, Esther Perez Ruiz, and Yorbol Yakhshilikov. 2021. “Fintech Potential for Remittance Transfers: A Central America Perspective.” IMF Working Paper 21/175, International Monetary Fund, Washington, DC. https://www.imf.org/en/Publications/WP/Issues/2021/06/25/Fintech-Potential-for-Remittance-Transfers-A-Central-America-Perspective-461266.
- Carare, Alina, Lavinia Franco, Metodij Hadzi-Vaskov, Justin Lesniak, Dmitry Vasilyev, and Yorbol Yakhshilikov. 2022. “Digital Money and Remittances Costs in Central America, Panama, and the Dominican Republic.” IMF Working Paper 22/238, International Monetary Fund, Washington, DC. https://www.imf.org/en/Publications/WP/Issues/2022/12/02/Digital-Money-and-Remittances-Costs-in-Central-America-Panama-and-the-Dominican-Republic-526289.
- Haksar, Vikram, Yan Carriere-Swallow, Emanuel Kopp, Gabriel Quiros, Emran Islam, Andrew Giddings, and Kathleen Kao. 2021. “Toward a Global Approach to Data in the Digital Age.” IMF Staff Discussion Note 2021/005, International Monetary Fund, Washington, DC. https://www.imf.org/en/Publications/Staff-Discussion-Notes/Issues/2021/10/06/Towards-a-Global-Approach-to-Data-in-the-Digital-Age-466264.
- Khera, Purva, Sumiko Ogawa, Ratna Sahay, and Mahima Vasishth. 2022. “Women in Fintech: As Leaders and Users.” IMF Working Paper 22/140, International Monetary Fund, Washington, DC. https://www.imf.org/en/Publications/WP/Issues/2022/07/15/Women-in-Fintech-As-Leaders-and-Users-520862.
- Loko, Boileau, and Yuanchen Yang. 2022. “Fintech, Female Employment, and Gender Inequality.” IMF Working Paper 22/108, International Monetary Fund, Washington, DC. https://www.imf.org/en/Publications/WP/Issues/2022/06/03/Fintech-Female-Employment-and-Gender-Inequality-518871.
- International Monetary Fund (IMF). 2018. “The Bali Fintech Agenda: A Blueprint for Successfully Harnessing Fintech’s Opportunities.” https://www.imf.org/en/News/Articles/2018/10/11/pr18388-the-bali-fintech-agenda.
- International Monetary Fund (IMF). 2022. “Financial Access Survey.” https://data.imf.org/?sk=E5DCAB7E-A5CA-4892-A6EA-598B5463A34C.

### BIS, FSB, and Other Multilateral Reports
- Duarte, Angelo, Jon Frost, Leonardo Gambacorta, Priscilla Koo Wilkens, and Hyun Song Shin. 2022. “Central Banks, the Monetary System and Public Payment Infrastructures: Lessons from Brazil’s Pix.” BIS Bulletin, no. 52. https://www.bis.org/publ/bisbull52.htm.
- Cantú, Carlos, and Barbara Ulloa. 2020. “The Dawn of Fintech in Latin America: Landscape, Prospects and Challenges.” BIS Paper No. 112. Bank for International Settlements. https://www.bis.org/publ/bppdf/bispap112.htm.
- Cornelli, Giulio, Sebastian Doerr, Leonardo Gambacorta, and Ouarda Merrouche. 2020. “Inside the Regulatory Sandbox: Effects on Fintech Funding.” BIS Working Paper 901, International Monetary Fund, Washington, DC. https://www.bis.org/publ/work901.htm.
- Ehrentraud, Johannes, Jermy Prenio, Codruta Boar, Mathilde Janfils, and Aidan Lawson. 2021. “Fintech and Payments: Regulating Digital Payment Services and E-Money.” FSI Insight on Policy Implementation No. 33. https://www.bis.org/fsi/publ/insights33.htm.
- Ehrentraud, Johannes, Denise Garcia Ocampo, Lorena Garzoni and Mateo Piccolo. 2020. “Policy Responses to Fintech”. FSI Insights No. 23. https://www.bis.org/fsi/publ/insights23.htm
- Financial Stability Board. 2017. “Artificial Intelligence and Machine Learning in Financial Services.” Press Release. https://www.fsb.org/2017/11/artificial-intelligence-and-machine-learning-in-financial-service/.
- Financial Stability Board. 2020. “Bigtech Firms in Finance in Emerging Market and Developing Economies Market developments and potential financial stability implications”

### Academic Articles and Methodological References
- Asongu, Simplice, and Jacinta Nwachukwu. 2018. “Mobile Phones, Institutional Quality and Entrepreneurship in Sub-Saharan Africa.” Technological Forecasting and Social Change 1, no.C: 183–203. https://econpapers.repec.org/article/eeetefoso/v_3a131_3ay_3a2018_3ai_3ac_3ap_3a183-203.htm.
- Asongu, Simplice A., and Nicholas M. Odhiambo. 2019. “How Enhancing Information and Communication Technology Has Affected Inequality in Africa for Sustainable Development: An Empirical Investigation.” Sustainable Development 1: 1–10. https://onlinelibrary.wiley.com/doi/abs/10.1002/sd.1929.
- Athey, Susan, and Guido W. Imbens. 2017. "The State of Applied Econometrics: Causality and Policy Evaluation." Journal of Economic Perspectives 31, no. 2: 3–32. https://www.aeaweb.org/articles?id=10.1257/jep.31.2.3.
- Athey, Susan, and Guido W. Imbens. 2019. "Machine Learning Methods that Economists Should Know About." Annual Review of Economics 11: 685–725. https://www.annualreviews.org/doi/abs/10.1146/annurev-economics-080217-053433.
- Mullainathan, Sendhil, and Jann Spiess. 2017. "Machine Learning: An Applied Econometric Approach." Journal of Economic Perspectives 31 (2): 87–106. https://www.aeaweb.org/articles?id=10.1257/jep.31.2.87.
- Kohavi, Ron. 1995. “A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection.” International Joint Conference on Artificial Intelligence. https://www.ijcai.org/Proceedings/95-2/Papers/016.pdf.
- Lundberg, Scott, and Su-In Lee. 2017. "A Unified Approach to Interpreting Model Predictions." In Proceedings of the Advances in Neural Information Processing Systems, Long Beach, CA, USA, 4–9 December 2017; pp. 4765–4774.
- Chen, Tianqi, and Carlos Guestrin. 2016. "XGBoost: A Scalable Tree Boosting System." In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 785–94. https://dl.acm.org/doi/10.1145/2939672.2939785.
- Snoek, Jasper, Hugo Larochelle, and Ryan P. Adams. 2012. “Practical Bayesian Optimization of Machine Learning Algorithms.” Advances in Neural Information Processing Systems 25: 2960-2968 https://arxiv.org/abs/1206.2944.
- Kohavi, Ron. 1995. “A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection.” International Joint Conference on Artificial Intelligence. https://www.ijcai.org/Proceedings/95-2/Papers/016.pdf.

### Industry Analyses, Databases, and Trade Associations
- Association for Private Capital Investment in Latin America (LAVCA). 2022. “LAVCA Trends in Tech.” LAVCA Venture Investors. Accessed May 6, 2022, at https://lavca.org/industry-data/2022-lavca-trends-in-tech/#MAPPING-THE-MAJOR-MARKETS.
- Fintech Technology Partners (FT Partners). 2020–2022. “Fintech Almanac 2020, 2021 and Quarterly Fintech Insights.” https://www.ftpartners.com/fintech-research.
- “The Global Fintech Index.” N.d. Findexable. https://gfi.findexable.com/.
- “Global Fintech-Enabling Regulations Database.” The World Bank. November 16, 2021. https://www.worldbank.org/en/topic/fintech/brief/global-fintech-enabling-regulations-database.
- Statista. 2022. “Number of Fintech Users in Latin America in 2022, by Segment.” Statista Research Department. https://www.statista.com/forecasts/1241612/latin-american-caribbean-fintech-users-segment.
- Crunchbase. N.d. Wikipedia. https://en.wikipedia.org/wiki/Crunchbase.
- Finicity. 2022. “Open Banking vs. Open Finance.” https://tinyurl.com/5n994r4z.

### Regional and Thematic Studies on Fintech, Payments, and Inclusion
- Berkman et al. (see above) — Fintech in Latin America and the Caribbean: Stocktaking. IMF Working Paper 19/71.
- Bains, Parma, Nobuyasu Sugimoto, and Christopher Wilson. 2022. “Bigtech in Financial Services: Regulatory Approaches and Architecture.” IMF Fintech Note 2022/002, International Monetary Fund, Washington, DC. https://www.imf.org/en/Publications/fintech-notes/Issues/2022/01/22/BigTech-in-Financial-Services-498089.
- Bains, Parma, and C. Wu. Forthcoming. “Institutional Arrangements for Fintech Regulation: Supervisory Monitoring.” IMF Fintech Note, International Monetary Fund, Washington, DC.
- Cantú, Carlos, and Barbara Ulloa. 2020. “The Dawn of Fintech in Latin America: Landscape, Prospects and Challenges.” BIS Paper No. 112.
- Cambridge Centre for Alternative Finance (CCAF), World Bank, and World Economic Forum. 2020. “The Global Covid-19 FinTech Market Rapid Assessment.” University of Cambridge, World Bank Group, and the World Economic Forum.
- Inter-American Development Bank (IDB). April 2022. Fintech in Latin America and the Caribbean: A Consolidated Ecosystem for Recovery. IDB Report. https://publications.iadb.org/en/fintech-latin-america-and-caribbean-consolidated-ecosystem-recovery.
- World Bank and Cambridge Centre for Alternative Finance (CCAF). 2020. The Global Covid-19 FinTech Regulatory Rapid Assessment Report. World Bank Group and the University of Cambridge. https://www.jbs.cam.ac.uk/wp-content/uploads/2020/10/2020-ccaf-report-fintech-regulatory-rapid-assessment.pdf.
- Ziegler, Tania, Felipe Ferri de Camargo Paes, Cecilia López Closs, Erika Soki, Diego Herrera, and Jaime Sarmiento. 2022. “The SME Access to Digital Finance Study: A Deep Dive into the Latin American Fintech Ecosystem.” Judge Business School, University of Cambridge, UK. https://www.jbs.cam.ac.uk/faculty-research/centres/alternative-finance/publications/sme-access-to-digital-finance-study-latam/.
- Ziegler, Tania, Rotem Shneor, Karsten Wenzlaff, Krishnamurthy Suresh, Felipe Ferri de Camargo Paes, Leyla Mammadova, Charles Wanga, Neha Kekre, Stanley Mutinda, Britney Wanxin Wang, et al. 2021. The 2nd Global Alternative Finance Market Benchmarking Report. Cambridge Centre for Alternative Finance (CCAF), University of Cambridge, UK. https://www.jbs.cam.ac.uk/wp-content/uploads/2021/06/ccaf-2021-06-report-2nd-global-alternative-finance-benchmarking-study-report.pdf.
- Carare et al. (see above) — Digital Money and Remittances Costs in Central America, Panama, and the Dominican Republic. IMF Working Paper 22/238.

### Payments, Digital Wallets, and National Systems
- “Pix Frequently Asked Questions.” 2020. https://www.bcb.gov.br/en/financialstability/pixfaqen.
- Duarte et al. 2022. “Central Banks, the Monetary System and Public Payment Infrastructures: Lessons from Brazil’s Pix.” BIS Bulletin, no. 52.
- Kagan, Julia. 2022. “Digital Wallet Explained: Types with Examples and How It Works.” Investopedia. https://www.investopedia.com/terms/d/digital-wallet.asp.
- Khaitan, Piyush, and Armaan Joshi. 2022. “What Is a Digital Payment and How Does It Work?” Forbes Advisor. https://www.forbes.com/advisor/in/banking/what-is-a-digital-payment-and-how-does-it-work/
- “CoDi es Para Todos.” N.d. CoDi. https://www.codi.org.mx/.
- Blakely-Gray, Rachel. 2021. “Digital Payments Are a Staple in Friendships, but What About Business?” Patriot. https://www.patriotsoftware.com/blog/accounting/digital-payments/.

### Insurtech, Alternative Finance, and SME Finance
- Catlin, Tanguy, Johannes-Tobias Lorenz, Björn Münstermann, and Valentino Ricciardi. 2017. Insurtech—the Threat That Inspires. McKinsey & Company. https://www.mckinsey.com/industries/financial-services/our-insights/insurtech-the-threat-that-inspires.
- Digital Insurance Latam. 2021. “LatAm Insurtech Journey.” Latam. https://www.sincor.org.br/wp-content/uploads/2022/02/latam_insurtech_journey_eng.pdf.
- Hargrave, Marshall. 2022. “Overview of Insurtech and Its Impact on the Insurance Industry.” Investopedia. https://www.investopedia.com/terms/i/insurtech.asp.
- “What Is Alternative Lending?” 2020. Funding Circle. https://www.fundingcircle.com/us/resources/alternative-lending/#:~:text=Alternative%20lending%20refers%20to%20any,investors%20willing%20to%20provide%20it.
- World Bank. 2020. “Promoting Digital and Innovative SME Financing.” Global Partnership for Financial Inclusion. World Bank, Washington, DC. https://www.gpfi.org/news/promoting-digital-and-innovative-sme-financing.
- Ziegler et al. 2022. “The SME Access to Digital Finance Study: A Deep Dive into the Latin American Fintech Ecosystem.” Judge Business School, University of Cambridge, UK.

### Data Sources, Databases, and Statistical Series
- World Bank. 2022. “Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19.” World Bank, Washington, DC. https://www.worldbank.org/en/publication/globalfindex.
- World Bank. 2023. “Bank’s Net Interest Margin for Brazil.” Federal Reserve Bank of St. Louis. https://fred.stlouisfed.org/series/DDEI01BRA156NWDB.
- Statista. 2022. “Number of Fintech Users in Latin America in 2022, by Segment.” Statista Research Department. https://www.statista.com/forecasts/1241612/latin-american-caribbean-fintech-users-segment.
- “The Global Fintech Index.” N.d. Findexable. https://gfi.findexable.com/.

### Additional Policy, Practice, and Media Coverage
- Johansson, Eric. 2022. “How COVID-19 Created a Massive Fintech Boom.” Private Banker International. https://www.privatebankerinternational.com/news/how-covid-19-created-a-massive-fintech-boom/.
- Majbour, Bilal. 2021. “Taking a Look at the Digital Investing Landscape.” Forbes. https://www.forbes.com/sites/forbesbusinesscouncil/2021/09/16/taking-a-look-at-the-digital-investing-landscape/?sh=65861cee6892.
- Stafford, Christian. 2016. “Regtech.” TechTarget. https://www.techtarget.com/searchcio/definition/RegTech.
- World Bank. 2014. “Global Financial Development Report 2014: Financial Inclusion.” World Bank, Washington, DC. https://openknowledge.worldbank.org/handle/10986/16238.
- United Nations Conference on Trade and Development. 2021. “Financial Inclusion for Development: Better Access to Financial Services for Women, the Poor, and Migrant Work.” United Nations Conference on Trade and Development, New York.

*References list for: The Rise and Impact of Fintech in Latin America — NOTE/2023/003*

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_Source: https://www.imf.org/-/media/files/publications/ftn063/2023/english/ftnea2023003.pdf_