By 2030, Uzbekistan’s banks must learn to issue online microloans in an average of one hour, and the share of such loans should grow to 60% of total microcredit volume. The Central Bank of Uzbekistan set this goal in its Concept for Small and Medium Business Support for 2026–2030, as reported by UzDaily.uz on October 15, 2026, citing the regulator. The concept text is unavailable on the Central Bank’s website for direct verification at the time of publication, so figures and phrasing rely on the publication’s data.
What changes in online lending
Currently, issuing a microloan to an individual or entrepreneur through a bank branch takes significantly longer than an hour: applicants must gather documents, pass verification, and wait for a credit committee or scoring system decision. The Central Bank’s concept aims for a mass transition of this process to digital channels. Banks will rely on automated scoring and digital client identification, while document flow will be standardized for mobile apps and web platforms. Formally, the goal applies to all online microloans, but the description shows a primary focus on individuals and micro-entrepreneurs, who currently use bank loans the least.
The decision does not appear in a vacuum. On April 22, 2026, the Central Bank restricted online lending: a citizen can take out no more than one online credit or microloan per day. This measure targeted over-indebtedness and multiple-loan schemes across different apps. The new concept shows the regulator is simultaneously containing risks and clearing the path to accelerate legal digital lending. This is not a one-off liberalization, but part of a broader tuning of online lending rules.
Why Uzbekistan’s SMEs need this leap
Figures cited by the Central Bank from the World Bank explain why the target is an hour, not a day or a week. In 2025, only 10% of small and 16% of medium enterprises in the country used loans. Only 24% of SMEs have active credit accounts, yet 68% are registered with credit bureaus. This means banks either cannot access or do not use solvency data for a segment of businesses. According to World Bank estimates, about 30% of SME sales already occur electronically. Entrepreneurs are accumulating a digital footprint that could form the basis for scoring.
Against this backdrop, the sector’s scale looks disproportionate to its financing access. SMEs account for more than half the country’s GDP and about three-quarters of employment. As of July 1, 2026, the number of small businesses—including individual entrepreneurs, dehkan farms, and artisans—reached 1,236,100. In the first half of 2026, small business generated 50.5% of GDP, or 518.7 trillion soums in value added, and exported $7.48 billion, making up 47.2% of the country’s total exports. Yet SMEs account for only 36% of the aggregate bank loan portfolio, which stood at 642.8 trillion soums on July 1, 2026.
A concept broader than one metric
Cutting microloan issuance time to an hour, growing the online loan share to 60%, and doubling the SME portfolio from the current 218 trillion soums by 2030 are just part of the document’s 25 initiatives. The Central Bank groups the remaining measures into three blocks.
Seventeen institutional initiatives cover the transformation of the Business Development Bank, introducing a financial ombudsman for pre-trial disputes (including micro and small business complaints), granting banks the right to provide accounting, tax, and consulting services, and creating a methodological base for Islamic finance through pilot “Islamic windows.” This also includes a counter-guarantee system: following the president’s dialogue with entrepreneurs on August 18, 2026, a borrower seeking a loan up to 10 billion soums only needs to provide collateral for 25% of the amount, rather than the full loan amount often required today.
Five infrastructure initiatives aim to reduce information asymmetry: a centralized collateral realization platform with a unified online registry of movable property, a post-loan monitoring system, and the rollout of Open Banking and scoring based on alternative data—tax, payment, trade, and utility records. Borrowers are promised the right to receive an explanation for loan rejections, and entrepreneurs are promised a digital marketplace to compare credit products from banks and non-bank organizations.
Three product initiatives cover pre-export financing and international factoring. A guarantee organization is being created under the Trade Development Company JSC to cover factoring guarantees up to 10 billion soums, but no more than half its value. Until January 1, 2029, the company promises to reimburse part of the discount or interest on such deals.
The concept’s other targets also tie into financing access. The ratio of SME loans to GDP should grow from 12% to 20%, the share of non-bank credit organizations in total lending from 1.7% to 5%, and credit bureau coverage of SMEs from 68% to 80%. The share of state financial institutions in SME lending is planned to drop from 73% to 65%, and to 55% if a major state bank is privatized. The concept is established as a pilot document: it will be reviewed annually based on metric monitoring, initiative execution, and market participant discussions.
What this means for clients and banks
For the working population and entrepreneurs in regions with limited branch networks, one-hour microloan issuance via an app means access to small amounts no longer depends on the distance to the nearest bank. For banks, this requires rebuilding processes: replacing manual document checks with automated scoring tied to digital client identification and, judging by the infrastructure initiatives, data from tax, payment, and utility systems.
The concept links issuance speed with growing the online microloan share to 60%, effectively setting a benchmark for banks to shift retail microcredit to digital channels by default, rather than as an option for some clients. For now, these are targets on the horizon to 2030, not active regulations. The concept will use annual monitoring to check how quickly banks can back them up with real scoring models and credit bureau data.