A market vendor in Indonesia can spend an entire day receiving QR payments and still struggle to obtain a bank loan. Her customers and sales are real, but her business may have no formal credit history or collateral. On 26 October 2026, Bank Indonesia said it plans to use transaction histories from QRIS, the national QR payment standard, as one reference for assessing creditworthiness among micro, small, and medium-sized enterprises (MSMEs). By the third quarter of 2026, QRIS had reached 49.4 million merchants, about 97 percent of them MSMEs.
The idea arrives at a difficult moment for the politics of economic opportunity. In August 2025, protests in Indonesia over lawmakers’ allowances escalated following the death of a motorcycle-taxi driver struck by a police vehicle. In Nepal, a social media ban ignited demonstrations also shaped by anger over corruption and limited opportunities. Young Moroccans protested inadequate public services and prospects for work, while demonstrations in Madagascar over water and electricity shortages developed into a national political crisis. These movements had different causes; none was simply a revolt against inequality. Together they exposed how precarious public trust can become when economic progress seems disconnected from daily life.
The UN World Social Report 2025 warned that economic insecurity and persistent inequality were eroding social cohesion. Credit cannot repair failures of governance or public services. It does, however, speak to a question beneath much of the frustration: whether working hard today still offers a plausible route to living better tomorrow.
When Financial Invisibility Limits Opportunity
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A productive small enterprise can be difficult for a lender to assess. Without audited accounts, collateral or previous loans, a manufacturer may be unable to buy equipment needed for a larger order; a market vendor may miss the chance to purchase stock at lower prices. Transaction histories offer evidence of turnover and business continuity that conventional credit records can overlook, although they cannot reveal every expense or liability.
A 2022 Bank for International Settlements study of roughly half a million Chinese firms found that QR payment records helped merchants obtain credit from the technology platform processing their transactions, with positive spillovers to bank credit. Access to platform credit also improved business sales, including during the COVID-19 shock. China’s platform-controlled model differs from a potential Indonesian arrangement built around a national payment standard. In the Philippines, Maya’s Paleng-Kita program uses merchant QR histories alongside alternative data to assess loans for vendors and drivers. Both cases establish the value of payment data, not an inevitable development outcome.
Consider a tailor who borrows to purchase a machine and wins larger orders, alongside a shopkeeper who borrows to keep buying stock as sales decline. Both gain access to credit, but only one may build wealth. A 2015 synthesis of six randomized microcredit evaluations found generally modest rather than transformative welfare gains. Those studies examined microcredit, not QR-based scoring for established merchants. Their relevance is the distinction between getting a loan and benefiting from it.
Credit access, wealth creation, and wealth distribution are three different outcomes. An innovation may expand the first without necessarily improving the other two. That distinction should guide the evaluation of financial inclusion, particularly when access to new technology is itself unequal.
The AI Divide Adds Another Constraint
A March 2026 ILO working paper by Paweł Gmyrek, Mariana Viollaz, and Hernan Winkler examined GenAI exposure across 135 countries. It found lower aggregate automation exposure in developing economies than in advanced ones and warned that conventional exposure measures often overstate likely impacts in poorer countries. Yet connectivity gaps mean that some workers could face disruption before others can capture productivity benefits. The paper analyses jobs and workers, not merchant financing.
A further possibility follows from this evidence, rather than being established by it. A small business with a thin digital payment history may struggle to obtain financing; without affordable capital, it may also struggle to invest in software, equipment, or training that would make AI useful. A better-resourced competitor can move sooner. Credit innovation could ease one barrier to technological adaptation but would not solve inadequate connectivity, skills, or market demand. The distribution of these capabilities will influence whether AI helps close economic gaps or compounds them.
The Danger of Digitizing Debt
Indonesia already has subsidized MSME lending through Kredit Usaha Rakyat and the Financial Services Authority’s credit information system, SLIK. QRIS histories could complement them, particularly for businesses with limited formal borrowing records. The uneven pace of lending is evident in OJK’s September 2026 report: bank credit to MSMEs grew only 2.32 per cent year on year in August, compared with 13.65 per cent for total bank credit. This suggests sluggish MSME credit growth, although the figures alone cannot distinguish weak demand from restricted supply.
The same report showed Rp106.94 trillion in outstanding regulated online peer-to-peer lending, up 22.07 per cent year on year. Its 90-day delinquency measure, TWP90, rose from 4.32 per cent in July to 4.73 per cent in August. Gross non-performing loans in banking stood at 2.11 percent, although the measures and borrower populations are different and should not be treated as directly comparable. None of these figures describes QRIS-based credit. They show why more lending cannot automatically be counted as better economic outcomes.
A January 2026 IMF working paper found that rapid growth in borrower numbers becomes a stronger warning signal for instability when it coincides with a wider credit boom. There is a distributional risk too: cash-heavy or seasonal enterprises can appear less creditworthy simply because their histories are harder for an algorithm to read. Financial inclusion can become another sorting mechanism if visibility replaces a fuller assessment of business viability.
Who Controls the Right to Be Seen?
The political dimension also lies in who controls merchant data and credit decisions. Can a payment provider use transaction histories for purposes beyond processing payments? Can a business correct inaccurate records, take them to another lender, or contest a rejection? These choices determine who benefits from financial visibility and who remains dependent on a single institution.
Indonesia’s Personal Data Protection Law recognizes individual rights to data portability and to object to certain significant decisions based solely on automated processing. Crucially, Article 15 also permits exceptions to those very rights for specified purposes, including financial-sector and payment-system supervision conducted as a state function; Article 15(2) confines such exceptions to the implementation of statutory provisions. Their application to any future QRIS scoring arrangement therefore requires careful legal assessment, rather than an assumption that the rights apply without qualification. Article 34 requires impact assessments for high-risk personal-data processing, including systematic scoring. These protections concern identifiable individuals; an incorporated business does not automatically hold the same personal-data rights.
Government Regulation No. 33/2026 was promulgated on 16 July 2026 and is scheduled to take effect on 16 January 2027. Enforcement capacity remains another concern: Bisnis.com reported in September 2026 that Indonesia’s dedicated data-protection supervisory body had not yet been fully established. Its absence could complicate complaints and oversight, even where rights exist on paper. The proposed QRIS scoring model itself has not been specified publicly in enough detail to settle these questions.
A Geoeconomic Asset, with a Local Test
QRIS cross-border arrangements already connect Indonesia with regional payment partners and support local-currency transactions for commerce and tourism. Bank Indonesia has also targeted US$55 billion in local-currency transactions in 2026, against approximately US$25 billion in 2025. That target covers the broader local-currency transaction framework, not cross-border QRIS alone.
Regional payment autonomy and domestic MSME financing are different achievements. Their shared significance lies in whether nationally coordinated infrastructure improves economic choices for people and enterprises. Credit may help a small producer buy equipment or reach a larger market, but it cannot replace reliable energy, skills, or customers. The geoeconomic test is whether more domestic firms develop the productive capacity to compete and withstand shocks, rather than simply generate additional digital transactions.
What Good Design Would Look Like
Indonesia should specify lawful, transparent access to merchant data, with practical portability where appropriate and safeguards suited to individuals and incorporated businesses alike. Lenders should consider supplier transactions, utility payments, or other relevant evidence so cash-dependent businesses are not rejected for lacking QR records. Decisions shaped by automated scoring need meaningful correction and review channels, within the applicable legal framework, while impact assessments should test discriminatory outcomes and misuse risks.
Most importantly, BI, OJK, and participating lenders should evaluate what happens after disbursement: changes in net earnings, productive assets, business survival, and repayment stress, including for merchants previously excluded from formal credit. Such evidence would distinguish productive inclusion from the expansion of debt.
For the vendor receiving QR payments each morning, a loan approval may make a new piece of equipment affordable. Whether that investment improves her circumstances will depend on markets, costs, and choices no algorithm can fully predict. The promise of digital finance lies in democratizing the opportunity to build wealth, not merely expanding access to debt.
