Contents

1. Abstract
2. List of Abbreviations
3. Introduction
4. Literature Review
– 4.1 Stablecoin dollarisation and monetary sovereignty
– 4.2 Run risk and reserve transparency
– 4.3 Open banking and consumer data control
– 4.4 RegTech and differentiated supervision
– 4.5 The gap and the hypotheses
5. Analysis
– 5.1 Stablecoin dollarisation: inclusion versus sovereignty
– 5.2 Run risk and reserve transparency
– – 5.2.1 Mechanism
– – 5.2.2 Case A: TerraUSD
– – 5.2.3 Case B: USDC and Silicon Valley Bank
– – 5.2.4 Case C: Tether
– – 5.2.5 Synthesis
– 5.3 Open banking, data control and the regulatory challenge in emerging markets
– 5.4 RegTech and the regulatory response
– – 5.4.1 Core analysis results
– – 5.4.2 Assessing the case for imported frameworks
6. Discussion
7. Conclusion
8. Bibliography

1. Abstract

Digital financial services are changing how households in emerging markets hold money. Dollar-pegged stablecoins now work as a store of value in countries with weak currencies. Open banking frameworks let consumers share the transaction data that formal credit files leave out. Both expand access, and both move control over money and data outside the reach of domestic supervisors. This paper tests three propositions: (1) that higher adoption of digital financial services raises financial inclusion; (2) that it also moves monetary and liquidity risk from central banks to private firms outside their control; and (3) that stronger regulatory architecture weakens the second effect. The method is a qualitative synthesis of published research and institutional data across four areas: stablecoin dollarisation, run risk and reserve transparency, open banking and data control, and RegTech supervision. The first two propositions hold, but they turn out to describe one mechanism rather than two, because easy access to a foreign currency delivers the welfare gain and imposes the sovereignty cost at the same time. The third holds in a narrower form than stated. What moderates risk transfer is what regulation demands of reserve substance and consent, not disclosure or adoption on their own, and rules designed for advanced economies can raise costs for the users they are meant to protect. Digital finance in emerging markets works as a risk-transfer mechanism as much as an inclusion tool, and regulatory design decides which one dominates.

Keywords: stablecoins, financial inclusion, monetary sovereignty, open banking, RegTech, emerging markets

2. List of Abbreviations

3. Introduction

Tom Hillenbrand’s thriller Montecrypto (2021) turns on a discovery about a payment token. Juno, the company founded by the dead entrepreneur whose fortune drives the plot, issues a coin that people across the world treat as dollars. The reserves said to stand behind it are not there. What makes the book work as a thriller is that the danger lies in the finding out. The token works perfectly well as money for as long as nobody tests the claim, and the moment enough holders do, the collapse spreads into the wider financial system. Hillenbrand sets this in a near future where crypto has become everyday money. The question the plot rests on, whether anyone was checking the backing while the instrument grew into infrastructure, has since stopped being fictional.

Juno is invented. The migration it describes is real. Households in Argentina, Turkey and Nigeria have moved savings and payments into dollar stablecoins, and dollar-denominated tokens now make up more than 99% of a stablecoin market worth roughly $316 billion (BIS, 2025). Nigeria has become the largest stablecoin market in sub-Saharan Africa (IMF, 2026). Open banking regimes in India and Brazil have meanwhile put billions of financial accounts in a position to share transaction data with licensed third parties at the customer’s request (Government of India, 2026). Money and data are moving together, out of the institutions that central banks and supervisors were built to oversee.

That movement cuts two ways, and the literature tends to take one side at a time. Digital financial services reach households that branch networks never did. They lower the cost of payments, and they turn thin credit files into something a lender can price. The same services also move the unit of account, the savings pool and the data trail beyond the reach of domestic regulators. Two hypotheses follow: H1 holds that higher adoption of digital financial services raises financial inclusion; H2 holds that higher adoption also transfers monetary and liquidity risk from central banks to private actors outside their reach. If both hold, the policy lever is design and supervision, not permission. Our third hypothesis, H3, holds that the stronger the regulatory architecture, the weaker the transfer described in H2. The candidate architectures are the ones now being tested in practice: central bank digital currencies, open banking frameworks, stablecoin reserve and audit rules, and the supervisory technology needed to enforce any of them.

Our research question follows: To what extent can regulatory architecture preserve monetary sovereignty in emerging markets without limiting financial inclusion?

Section 5 tests these hypotheses across four analyses, each built around one variable. Section 5.1 takes the demand side, asking why households substitute into dollar tokens and uses Nigeria’s eNaira to show that a public digital alternative fails when the underlying currency lacks trust. Section 5.2 turns to the supply side. It asks whether the private claim those households hold deserves their trust, using three run episodes to separate the effects of reserve quality and reserve transparency. Section 5.3 moves from money to data, testing whether open banking gives consumers control or shifts risk onto them, with India and Brazil as the cases. Section 5.4 asks what can actually be enforced, examining RegTech supervision through Nubank’s operations in Brazil. A discussion and conclusion follow. Hillenbrand’s investigator works out what the reserves consist of only after the run has started, which has often been the regulator’s position too. Whether that sequence is inevitable is the question this paper takes up.

4. Literature Review

Four literatures bear on this paper’s question, and they have developed largely apart. One studies what happens to a currency when households leave it; a second asks whether the instrument they leave for is sound; the remaining two concern control over financial data instead of money, and whether any of this can be supervised in practice.

4.1 Stablecoin dollarisation and monetary sovereignty

Currency substitution was studied long before stablecoins existed. Ize and Levy-Yeyati (2003) treat financial dollarisation as a portfolio decision, deriving the choice to hold foreign-denominated claims from the relative volatility of domestic inflation and the real exchange rate. Reinhart, Rogoff and Savastano (2003) establish how persistent it is, showing that dollarisation survives the macroeconomic stabilisation that might have been expected to reverse it. Together they explain the motive and its durability, but they predate the technology that now carries it.

Recent scholarship extends this to digital assets and divides on what follows. Murakami and Viswanath-Natraj (2025) build a welfare model of a small open economy and conclude that the shift can leave households better off, most of all where shocks are severe, which makes accommodation the sensible policy. The Bank for International Settlements (2025) starts from the same evidence and reaches the opposite conclusion, holding that private tokens damage the singleness of money and that the remedy is a publicly issued digital alternative. Two empirical studies sit between these positions. Aldasoro, Beltrán and Grinberg (2026) estimate the exchange-rate spillovers of stablecoin flows, while Ree (2023) assesses take-up of Nigeria’s central bank digital currency. Whether a state can win demand back once it has moved offshore, and on what condition, is still unsettled.

4.2 Run risk and reserve transparency

The theoretical starting point is Diamond and Dybvig (1983), who show that an intermediary funding illiquid assets with claims redeemable on demand is exposed to a self-fulfilling run, because sequential service hands early redeemers a claim on the most liquid assets. Goldstein and Pauzner (2005) establish a unique run threshold, which makes run probability tractable as a variable.

Ma, Zeng and Zhang (2025) apply that structure to stablecoins. In their model, issuers remain open to panic runs because illiquid reserves must be sold at a discount under stress, which reproduces the first-mover advantage.

Ahmed, Aldasoro and Duley (2024) separate two variables that the earlier literature treats as one. Reserve quality is the true variance of reserve asset values, while reserve transparency is the precision of public information about them. Li et al. (2026) model the policy response and argue for mandated safe backing. Two questions remain open: the first is whether disclosure raises or lowers run risk, which appears to depend on what holders already believe; the second is which of the two variables dominates when both move at once.

4.3 Open banking and consumer data control

The literature has largely presented open banking as a tool that empowers consumers, through data portability, financial inclusion and competition (Plaitakis and Staschen, 2020; World Bank, 2022). Eroglu et al. (2026) argue that letting consumers share financial data with licensed providers reduces information gaps and improves access to credit. Most of this research examines advanced economies with established regulatory frameworks and high digital literacy.

The emerging-market picture is less settled. Open banking may expand financial access, but whether consumers benefit where privacy protection, digital literacy and enforcement are uneven remains contested (Medine and Plaitakis, 2023; World Bank, n.d.). He, Huang and Zhou (2023) show formally that data sharing can leave all borrowers worse off even when they choose whether to share, because lenders draw inferences from the decision to sign up. Practitioner work adds the risks of data misuse and algorithmic exclusion (Medine and Plaitakis, 2023). Less attention has gone to how open banking frameworks are designed and whether they give consumers real control or shift risk from institutions onto individuals. That question matters because emerging markets are adopting open banking without the institutional safeguards developed economies already have.

4.4 RegTech and differentiated supervision

Gurung and Perlman (2018) provide the foundational account of RegTech in developing-country central banks. They find that automated reporting and granular data collection can extend supervisory reach where capacity is thin, but that legacy processes and skills shortages often block adoption. Sharma (2026) documents the problem this capacity is meant to solve, reporting overregulation across seven developing countries in the form of rigid licensing, high capital thresholds and overlapping oversight.

The technical literature has since moved towards automating the supervisory function itself. Srivastava (2026) tests machine-learning models for automated compliance monitoring, while Atkinson and Potvin (2024) examine machine-readable rulebooks through FINRA’s pilot. Both are developed-market studies. Suryanarayana and Oman (2023) supply the emerging-market counterpart, identifying fragmented regulatory procedures across India’s fintech sector, and Prihandini and Safaria (2025) argue that digital regulatory capacity is what allows oversight and stability to be balanced at all. What this literature does not settle is whether that capacity can substitute for rules designed elsewhere.

4.5 The gap and the hypotheses

Each literature stops where the next begins. Dollarisation research establishes that households move into private dollar tokens, but takes the soundness of those tokens as given. That is where the run-risk literature starts, though it in turn abstracts from the emerging-market conditions in which the tokens are held. Open banking research finds outcomes turning on regulatory design without asking whether money behaves the same way. The RegTech literature asks what can be enforced instead of what should be.

Two limits cut across all four. The empirical work draws disproportionately on advanced economies, where the institutional conditions that make these questions urgent are largely absent. The field also disagrees on basic effects, as Section 4.1 sets out, and neither side can settle the disagreement alone, because each describes a different regulatory environment.

This paper treats the four as one problem and tests three hypotheses across them:

• H1: Higher digital-finance adoption raises financial inclusion.
• H2: Higher digital-finance adoption transfers monetary and liquidity risk from central banks to private actors outside their regulatory perimeter.
• H3: Stronger regulatory architecture weakens the H2 effect, with the substance of what is mandated mattering more than disclosure or adoption alone.

5. Analysis

Four analyses test the hypotheses. Each isolates a single variable, and the four follow the sequence in which control moves. Separating money, data and supervisory capacity follows the literature, which has studied them apart. Bringing them back together is what allows the four analyses to qualify one another in Section 6.

The method is qualitative synthesis, not original estimation. Evidence comes from central bank and multilateral sources, from peer-reviewed research and from the statutory instruments themselves. We excluded market commentary and industry press. Quantitative findings come from published empirical work and are cited to their source.

We selected cases to isolate a variable, not to represent a population.

Nigeria’s eNaira works as a natural experiment for Section 5.1. It holds access, technology and population constant while changing only the unit of account, which separates public provision from regulation. The three episodes in Section 5.2 do the same job. TerraUSD, USDC and Tether shared a label and a promise to redeem at par. What differed was the quality and transparency of their reserves, which is why the difference in outcomes can be attributed to reserves and not to token design.

India and Brazil are the two largest consent-based data-sharing regimes in emerging markets, which makes them the strongest available test for Section 5.3. Nubank operates at scale in a market that combines a progressive regulatory framework with a large unbanked population, the conditions Section 5.4’s enforcement question requires.

Two limits follow from this design. Choosing instructive episodes over representative ones means the findings describe how these mechanisms work, not how often they occur. Several of the regimes examined are also too recent for their effects to be observable, which limits what the analysis can claim about H3.

5.1 Stablecoin dollarisation: inclusion versus sovereignty

Stablecoin dollarisation describes the growing use of dollar-pegged tokens, mainly USDT and USDC, as a store of value and a medium of exchange in economies with weak domestic currencies. The scale is no longer small. Dollar-denominated tokens make up more than 99% of the roughly $316 billion stablecoin market, and cross-border volumes rise measurably after episodes of high inflation and exchange-rate volatility (BIS, 2025). What looks at household level like a sensible decision looks from the central bank’s chair like a slow transfer of monetary authority, and both readings are correct at once. The risk identified here is therefore a sovereignty risk borne by the country. The section tests two propositions: that the more unstable the local currency, the greater the shift into dollar tokens, and that this shift moves monetary risk from the central bank to actors outside its regulatory perimeter.

The strongest theoretical case comes from Murakami and Viswanath-Natraj (2025), who model cryptocurrency adoption in a small open economy. They find that stablecoins raise welfare by smoothing consumption and by protecting households against macroeconomic shocks. Those gains grow with the size of the shock. Volatile assets fail where stable ones succeed. Bitcoin’s adoption as legal tender in El Salvador in 2021 increased volatility instead of reducing it, and uptake stayed low. The impulse itself is old. Households have long moved into a foreign currency when domestic inflation is volatile relative to the real exchange rate (Ize and Levy-Yeyati, 2003). Stablecoins digitise that choice for the same countries, Argentina and Turkey among them, that dollarised through banks a generation earlier. Payment costs add to the pull. Sending $200 to sub-Saharan Africa still costs close to 9% of the transfer against a global average nearer 6%. Adoption has followed. Nigeria alone drew roughly $59 billion in crypto-asset inflows between mid-2023 and mid-2024 and now accounts for around 60% of sub-Saharan Africa’s stablecoin inflows (IMF, 2026).

Added up across a population, that mechanism is what the BIS (2025) calls stealth dollarisation: a quiet migration of transactions and contracts onto the dollar with no formal policy decision behind it. Monetary sovereignty, defined as a jurisdiction’s capacity to control the monetary system within its borders, erodes through several channels. As demand for the local currency falls, monetary policy transmission weakens, and the IMF (2026) describes Nigeria’s uptake in exactly these terms. Savings moving out of bank deposits into privately issued tokens also reduce bank funding and the credit it supports. Recent empirical work attaches numbers to the channel. Using daily data for four stablecoins across 27 currencies, Aldasoro, Beltrán and Grinberg (2026) find that a one-percent rise in net stablecoin inflows measurably depreciates the local currency and widens covered interest parity deviations, with the sharpest effects where capital controls operate. This is the risk transfer in motion, though it is often described imprecisely. What matters for an emerging-market central bank is not whether issuers are regulated somewhere, but that they sit outside its own regulatory perimeter. A rule binding only licensed domestic intermediaries therefore governs the smaller half of a permissionless market.

How to respond is where the literature divides. Murakami and Viswanath-Natraj (2025) read the migration as welfare-improving, especially under severe shocks, and so as something policy should accommodate. The BIS (2025) reads the same movement as a threat to the singleness of money and argues instead for a tokenised public alternative anchored in central bank money. Prohibition was never promising, since currency substitution persists long after macroeconomic conditions improve (Reinhart, Rogoff and Savastano, 2003) and permissionless settlement leaves a ban little to grip. Nigeria supplies the closest available test of the BIS position. In October 2021, it issued the eNaira, Africa’s first central bank digital currency (CBDC), promoted partly as a financial inclusion measure and expected to offer a domestic alternative to foreign tokens. A CBDC is not a regulatory framework but a payment system the state issues, so what the case tests is public provision and not regulation. The eNaira delivered neither inclusion nor substitution. Ree (2023) found roughly 98.5% of eNaira wallets unused in any given week, with cumulative transactions numbering fewer than the wallets issued. Most holders never returned after opening one. The same population, on the same phones, meanwhile became the largest stablecoin market in sub-Saharan Africa. The contrast isolates the variable, which is the unit of account and not access or technology. A CBDC is a claim on the very currency households are trying to escape, and digitising the naira did not make it a more trustworthy store of value.

Both propositions hold on this evidence, and the trade-off is uneven. The household gains, the central bank carries the sovereignty cost, and the seigniorage goes to the United States and to the offshore issuer. A third proposition, that stronger regulatory architecture weakens the transfer, is beyond what a demand-side section can test, although the eNaira sets one condition on it. Where people do not trust the domestic currency, offering a public digital version of it does not separate inclusion from risk. The IMF (2026) comes to a similar view and treats a credible domestic currency, rather than prohibition, as the real defence against digital dollarisation. Whether the private claim households hold instead deserves their trust is the question Section 5.2 must answer.

5.2 Run risk and reserve transparency

A fiat-backed stablecoin is a private liability that promises redemption at par, funded by reserve assets that may be less liquid than the claim itself. Structurally, it is a bank without deposit insurance and without access to a lender of last resort (Aldasoro, Mehrling and Neilson, 2023). Three propositions follow:

• P1: the promise of par convertibility is only as sound as the liquidity and transparency of the reserves behind it.
• P2: higher reserve opacity raises run risk and the potential for fire sales.
• P3: audit and reserve-quality requirements moderate that risk.

5.2.1 MECHANISM

Redemption is sequential. A holder who redeems early receives par while reserves remain liquid, while a holder who waits receives whatever survives forced liquidation. This is the Diamond and Dybvig (1983) first-mover advantage transposed onto a token. Ma, Zeng and Zhang (2025) formalise it: reserves that must be sold at a discount under stress generate exactly this incentive, and the resulting sales pass stress outward into the markets for the reserve assets themselves. The Bank of England (2026) treats that second channel as a financial stability concern, noting that concentration of backing assets among systemic issuers could produce fire sales if several issuers had to liquidate holdings at the same time.

Three episodes isolate the reserve variable across its range: absent reserves, high-quality disclosed reserves and opaque reserves of contested quality.

5.2.2 CASE A: TERRAUSD

TerraUSD was the largest algorithmic stablecoin and the third largest stablecoin overall at its peak. Its peg rested on Luna, a self-issued and highly volatile cryptoasset that served as reserve backing only in the loosest sense (Ahmed, Aldasoro and Duley, 2024). Ahmed et al. find that peg deviations widened as Luna’s return volatility rose, and that the relationship strengthened as Terra’s equity value, defined as Luna’s market capitalisation minus that of TerraUSD, approached zero. Terra sits at the endpoint of the opacity axis, since there was little in the way of reserves to disclose in the first place. On 12th May 2022, TerraUSD broke its peg and fell to roughly $0.78. By 14th May, it traded near $0.12 and Luna’s estimated daily volatility exceeded 400% (Ahmed et al., 2024).

5.2.3 CASE B: USDC AND SILICON VALLEY BANK

On 10th March 2023, Circle disclosed that $3.3 billion of the cash reserves backing USDC was held at the failing Silicon Valley Bank. Ahmed et al. (2024) treat the disclosure as an exogenous public information shock and estimate its effect using a synthetic control built from minute-frequency data. Average absolute peg deviations rose to $0.03 in the post-disclosure window against a counterfactual of effectively zero, a difference significant at the 1% level. The peg recovered after the US authorities announced a backstop for SVB.

The case complicates P3. USDC held high-quality reserves and disclosed them, yet the disclosure amplified the run instead of damping it. Ahmed et al. account for this: greater transparency raises run risk when holders’ beliefs about reserve quality are already weak and lowers it when those beliefs are strong. Transparency stabilises the peg only where holders already have some reason to trust the reserves.

5.2.4 CASE C: TETHER

Tether occupies the opaque middle of the range. The CFTC (2021) found that between June 2016 and February 2019, Tether misrepresented that it held enough dollar reserves to back every token in circulation, failed to disclose that its reserves included unsecured receivables and non-fiat assets, and falsely claimed to undergo routine professional audits. Tether paid a $41 million civil penalty. The gap between attestation and independent audit carried a measurable cost. Ahmed et al. (2024) find that during the period of heightened doubt beginning in late 2018, Tether’s realised peg deviations averaged $0.009 against a counterfactual of $0.001, roughly nine times larger. When Tether resumed attestations in February 2021 after a gap of two and a half years, peg deviations fell significantly relative to the counterfactual. Opacity did not bring Tether down, but it did keep a standing discount on its promise to redeem at par.

5.2.5 SYNTHESIS

Across the three cases, the label held constant while the reserves varied, and the outcomes tracked the reserves. P1 and P2 hold. P3 holds in a narrower form than stated. Transparency and reserve quality operate through distinct channels (Ahmed et al., 2024), and disclosure imposed without a quality mandate can raise run risk in the short term. Ahmed et al. also identify the matching moral hazard: opacity can stabilise the peg in the short run by dulling holders’ reaction to weak signals, which frees the issuer to reach for yield and raises true fragility. Li et al. (2026) arrive at the same place from theory, finding that unregulated issuers hold risky assets to maximise profit and that mandated safe backing improves the equilibrium.

The finding in Section 5.1 bears directly on this. Growth has been concentrated in the two largest coins, Tether and USDC (BIS, 2025), and the one that Section 5.1 identifies as the household default in emerging markets is the coin with the disclosure history set out above. Those households exchange the currency risk of a sovereign that has a central bank for the counterparty risk of an issuer that has neither a supervisor with jurisdiction over them nor access to a public liquidity backstop.

The statutory responses treat this as a structural problem. The GENIUS Act requires backing at one-to-one in high-quality liquid assets, segregation of reserves, monthly published reserve reports examined by a registered public accounting firm, and certification of those reports by the issuer’s chief executive and chief financial officer (United States Congress, 2025). MiCA imposes an obligation to hold a reserve of assets, rules on custody and on how the reserve may be invested, a right of redemption at par and publication of audit reports on the reserve (European Union, 2023). The Bank of England (2026) adds a further layer, pairing backing-asset quality requirements with a Central Bank Liquidity Facility intended as a backstop for systemic issuers. In each case the safeguard is built into how the instrument is constructed and supervised, which is the level at which Section 5.3 takes up control over data.

5.3 Open banking and data control in emerging markets

Control over financial data is becoming as significant as control over money itself. As digital payments, mobile wallets and online credit expand across emerging markets, people generate valuable financial data through everyday transactions. For populations with limited formal credit histories, such as informal workers, small merchants and rural households, this data offers a possible bridge to financial visibility. Whether it does depends on regulatory design. Without clear consent protocols, data protection, cybersecurity standards and public supervision, data-sharing systems may expose vulnerable consumers to new risks instead of reducing exclusion (Plaitakis and Staschen, 2020; World Bank, 2022).

Open banking is a regulatory system that allows consumers to authorise banks to share their financial data with licensed third-party providers through standardised application programming interfaces, or APIs. The World Bank (2022) emphasises that open banking can expand consumer choice and access to new financial products, while also stressing that strong consumer consent protocols are essential to its legitimacy. The Bank for International Settlements argues along similar lines that open finance can break down data silos, reduce information gaps and improve access to financial services when built on standardised protocols and effective regulation (Eroglu et al., 2026). Open banking should therefore be understood as both a fintech innovation and a form of financial governance.

If consumers can safely share their data, fintech firms may offer budgeting tools, personalised savings products, cash-flow-based lending and more accurate affordability assessments. A small merchant without formal collateral may demonstrate regular revenue through digital payment records. A gig worker with irregular income may use account data to show repayment capacity more fairly than a traditional credit score allows. Plaitakis and Staschen (2020) argue that open banking can support financial inclusion by enabling cheaper and more tailored products for underserved consumers. Recent evidence also suggests that open banking adoption can increase digital payment participation, although the effect is not uniform across all measures of digital banking use (Ryan and Mukherjee, 2026). Open banking can therefore deepen inclusion without being automatically transformative.

In many developing economies, consumers and micro-enterprises rely on cash income, informal employment, mobile money or fragmented financial relationships. These patterns often mean they have limited credit histories or are treated as high-risk by formal banks, even when they have genuine repayment capacity. The World Bank’s Global Findex data shows that gaps in account ownership, formal saving, borrowing and digital payments remain uneven across income, gender and geography (Klapper et al., 2025). Open banking may reduce this information gap by allowing consumers to share transaction histories and savings behaviour that reflect their financial lives more accurately.

India’s Account Aggregator framework offers a consent-based data-sharing system where customer information cannot be retrieved, shared or transferred without explicit authorisation. The Reserve Bank of India’s master directions require clear rules on consent architecture, auditability, data storage restrictions, customer grievance systems and secure data flows (RBI, 2024). The Indian Department of Financial Services reports that, as of March 2026, more than 2.88 billion financial accounts had been enabled to share data through this framework (Government of India, 2026). Brazil provides another important case. The Banco Central do Brasil defines open finance as the sharing of data, products and services between regulated entities at the customer’s discretion, with objectives including innovation, competition, credit-market efficiency and financial citizenship (Banco Central do Brasil, n.d.). In both countries, the framework does more than move data from banks to platforms because it also sets conditions on how that data may be used.

The risks are substantial, and they concentrate in the same place. Open banking relies on consent, but consent may not be meaningful if users do not understand what data is shared, who receives it, or how it affects future credit decisions. This matters most in emerging markets where digital literacy, legal understanding and regulatory enforcement are uneven. The World Bank warns that users may lack a clear understanding of how their data is collected or shared, while data misuse and fraud are among the fastest-growing consumer risks (World Bank, n.d.). Medine and Plaitakis (2023) argue that weak regulatory checks can expose low-income consumers to data abuse and privacy harms. He, Huang and Zhou (2023) show that the problem is not only one of enforcement. In their model, lenders infer credit quality from who chooses to share, so borrowers can end up worse off even when sharing is voluntary and understood. Consumers with unstable income or informal employment are the most likely to be misclassified by such systems.

This produces a result that parallels Section 5.2. Portability of data, like disclosure of reserves, is a mechanism for moving information rather than a guarantee about what happens to it. What determines whether consumers gain control is the substance of the consent architecture: what a provider may do with the data, for how long and with what recourse. India and Brazil impose those conditions, which is why they are the stronger cases; a portability mandate without them would shift responsibility onto consumers while leaving power where it was. How to supervise these systems in practice is the question Section 5.4 addresses.

5.4 RegTech and the regulatory response

Emerging economies face a persistent contradiction while developing open banking. Authorities struggle to balance expanding financial inclusion against safeguarding users’ personal financial data, and copying mature Western regulatory frameworks rarely matches local market realities. This section examines the supervision risks that dollar stablecoins create, uses Nubank’s Brazilian operation as its case and considers locally adapted RegTech solutions to reconcile the competing objectives.

Regulatory gaps between advanced economies and emerging markets remain stark. Western rules are designed around mature banking systems, low inflation and established consumer credit infrastructure. Transplanted directly to developing countries with weaker financial foundations, those standards create persistent operational problems for regulators. Policymakers across emerging markets nonetheless tend to adopt European and North American systems refined over decades. Overregulation in developing countries takes the form of rigid licensing regimes, high capital thresholds and overlapping oversight, which restricts innovation and access without a matching gain in systemic safety (Sharma, 2026). Locally built RegTech infrastructure offers supervisors a workable middle position.

5.4.1 CORE ANALYSIS RESULTS

Replicating Western stablecoin reserve frameworks may weaken the cost advantages that support digital financial inclusion in emerging markets. Regulators in the EU and elsewhere set strict reserve liquidity requirements suited to stable inflation and well-established banking systems. Imposed on fintech platforms such as Nubank, those rules raise daily compliance costs substantially.

Nubank’s core users are low- and middle-income households who rely on cheap stablecoin transfers and basic digital bank accounts. Additional compliance costs reach end consumers as higher transaction fees or stricter identity verification. Such changes erode the low-cost access that originally brought unbanked residents into formal digital finance. Large parts of Latin America still lack physical bank branches, so any additional threshold to affordable fintech services slows regional economic development. The mechanism is documented across developing-country fintech regimes: high capital thresholds and prolonged licensing bureaucracy delay operations and put financial services beyond the reach of many potential providers, which in turn constrains innovation and financial inclusion (Sharma, 2026).

Even without rigid Western-style regulation, emerging economies can build robust risk defences through customised RegTech monitoring. Static reserve requirements rely on costly periodic manual audits, whereas automated systems allow continuous monitoring. Srivastava (2026) tests machine-learning models for automated compliance monitoring and finds them effective at identifying anomalous transactions in imbalanced data, a technical logic that transfers to stablecoin supervision. Applied to Nubank’s payment network, such platforms would let regulators verify circulating stablecoin reserve assets on an ongoing basis, while automated alerts flag the large capital outflows that can precede a run on an issuer. Section 5.2 identifies precisely these two exposures: opaque reserve information and the threat of mass redemption. Automated monitoring addresses both while reducing unnecessary operational burden on fintech firms.

This flexible supervisory model suits developing economies better than uniformly applied frameworks. Excessively strict imported rules suppress financial inclusion, while wholly unregulated fintech accumulates systemic risk. RegTech allows central banks to balance the two priorities (Gurung and Perlman, 2018). The efficiency gains are measurable. Institutions adopting RegTech report an average reduction in compliance costs of 25%, rising to between 30% and 40% in some cases (Sharma, 2026). Rwanda’s integration of RegTech for anti-money-laundering supervision between 2015 and 2019 produced a 50% increase in financial crime detection and a 20% decrease in high-risk transactions (Sharma, 2026). Brazil’s own RegTech sector has been growing at roughly 35.3% annually, supported by a progressive regulatory framework (Sharma, 2026).

Beyond real-time risk monitoring, integrated RegTech platforms unify supervision across stablecoin circulation and open banking data systems, addressing the fragmented governance raised in Sections 5.1 and 5.3. Most emerging markets face a structural problem: monetary supervision and personal data protection sit in separate government departments. Split supervision creates loopholes that firms may exploit, and conventional supervisory tools cannot connect the two policy fields. Supervisory capacity is therefore a component of monetary sovereignty and not a technical adjunct to it, since a jurisdiction that cannot observe the flows crossing its borders cannot govern the monetary system inside them.

Drawing on the logic of regulatory digitalisation examined by Atkinson and Potvin (2024), unified RegTech platforms can aggregate scattered transaction histories and consent logs within a single monitoring framework. Their study concerns mature financial markets, but the integrated design adapts to the fragmented supervision found across emerging economies. For platforms such as Nubank, unified oversight prevents firms from shifting high-risk activity between payment services and data-sharing functions to evade inspection. Regulators can trace the full lifecycle of user funds, from cross-border stablecoin transfers to domestic loan data shared under open banking rules, without interfering with everyday consumer activity. Suryanarayana and Oman (2023) identify the same fragmentation across India’s fintech sector, and their findings offer a reference for Latin American markets including Brazil. The Indian experience indicates that RegTech standardises scattered regulatory procedures, improves the consistency of supervision, and reduces long-term compliance costs.

5.4.2 ASSESSING THE CASE FOR IMPORTED FRAMEWORKS

The argument for importing mature Western regulation directly deserves a fair hearing. Its supporters hold that internationally unified rules strengthen foreign investor confidence in local fintech sectors, and that common legal standards close off the cross-border regulatory arbitrage available between neighbouring developing countries. On this reading, locally customised supervision risks fragmenting regional rules and obstructing financial cooperation across Latin America.

The position understates how far financial infrastructure differs between developed economies and countries such as Brazil. Where financial inclusion is the policy priority, uniformity carries a social cost that the gain in investor confidence does not obviously offset. Tailored RegTech supervision offers a middle position, retaining baseline legal standards while adjusting how intensively they are enforced.

The Nubank case indicates what that looks like in practice. Regulators can hold minimum standards constant while varying supervisory intensity through automated tools according to local conditions. In high-inflation regions with large unbanked populations, targeted oversight of RegTech-compliant platforms protects low-cost access. When capital outflow risks appear, the same systems allow monitoring to be tightened quickly. RegTech does not replace primary legislation, and treating it as a substitute would misread what it does. It makes existing law cheaper to enforce and more responsive to local conditions, which is why building digital regulatory capacity matters for emerging markets balancing oversight against stability (Prihandini and Safaria, 2025). Whether that capacity can compensate for rules calibrated elsewhere is taken up in Section 6.

6. Discussion

The four analyses track one movement. Control over an asset passes from a public or incumbent holder to a private one: the unit of account from the central bank to an offshore issuer, the savings pool from the domestic banking system to that issuer’s balance sheet, the transaction record from the bank to the platform, and supervisory capacity from the statute book to the monitoring system. Each transfer gives households something they wanted and takes away something the public authority relied on.

Placed side by side, the sections qualify one another. Section 5.1 finds the flight into dollar tokens welfare-improving for households facing severe shocks. Section 5.2 shows what they arrive at, which is a private liability whose promise to redeem at par rests on reserves that, in the dominant case, have never been independently audited. The issuer has no lender of last resort behind it and no supervisor with jurisdiction over the households concerned. Measured against a collapsing local currency, the safe haven is real; measured against anything else, it is conditional. Section 5.3 finds the same conditionality in data, where the inclusion gain from consumer-permissioned sharing turns on consent architecture and enforcement and not on adoption itself.

H1 and H2 both hold, but they describe one mechanism seen from two positions. Easy access to a foreign currency is what delivers the household’s welfare gain and what imposes the cost on the monetary order. The transaction history that makes an informal trader legible to a lender is the history that makes her legible to anyone else with access. As inclusion and risk transfer share a mechanism, a policy that suppressed one would suppress the other, which is why the trade-off cannot be settled at the margin.

H3 needs more care than the other two. Section 5.2 found that transparency and reserve quality work through separate channels, and that disclosure by itself can raise run risk in the short term when holders already doubt an issuer. What moderates risk transfer is the mandate on reserve substance. Section 5.4 pushes from the other side, finding that frameworks calibrated for low-inflation economies with mature banking sectors impose compliance costs that reach consumers as higher charges and stricter identity checks. Both findings survive once the substance of a rule is separated from its calibration. A token backed by unsecured receivables is fragile in Lagos as in Frankfurt, so reserve quality mandates travel across jurisdictions. The supervisory apparatus built around them does not, which is the case for adaptive monitoring over transplanted compliance regimes.

That separation also settles the disagreement identified in the literature review. The BIS (2025) and Murakami and Viswanath-Natraj (2025) reach opposite conclusions from similar evidence because each answers the question under different implicit regulatory conditions. Where reserve quality is mandated and supervised, the household’s position approximates what Murakami and Viswanath-Natraj model. Where it is not, the sovereignty and stability costs the BIS identifies dominate, and the household additionally holds an unaudited claim. Both can be correct. Which one dominates is an empirical question about regulatory architecture and not a theoretical dispute about stablecoins.

One problem outlasts this synthesis: MiCA and the GENIUS Act bind issuers serving European and United States users, and neither gives an emerging-market central bank authority over the token its residents actually hold. Domestic rules reach the licensed portion of a permissionless market, so the supervisory capacity examined in Section 5.4 does its most useful work exactly where formal jurisdiction is weakest. Regulatory architecture preserves monetary sovereignty only so far as some authority can reach the issuer.

The analysis is a qualitative synthesis of published literature and institutional data, not an original dataset, and several regimes examined here are too recent for their effects to be observable. Whether reserve mandates suppress adoption among low-income users, and whether consent frameworks hold under stress, are questions this paper frames and does not settle.

7. Conclusion

Digital finance in emerging markets expands access for unbanked populations and moves currency and liquidity risk from central banks to private actors, and these are two effects of one mechanism. Sovereignty is therefore only partly preservable under current conditions. States cannot fully recover monetary authority without first making the domestic currency credible, and the failure of the eNaira shows that a public digital alternative does not substitute for that credibility.

What states can do is limit further erosion through the substance of what they require. The stablecoin evidence shows that high-quality backing verified by independent audit is what stabilises a private claim, and that disclosure on its own does not; the open banking evidence shows the same pattern, where consent architecture rather than portability determines whether consumers gain control. The priority is therefore structural safeguards matched to each instrument: mandatory reserve audits for stablecoins, enforceable data protection for open banking and adaptable RegTech supervision that enforces both without pricing providers out. The benefits of these innovations are real, but they depend on the governance framework that decides how they are used and who carries the risk.

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