• KGS/USD = 0.01144 0%
  • KZT/USD = 0.00200 0%
  • TJS/USD = 0.10468 -0.1%
  • UZS/USD = 0.00008 0%
  • TMT/USD = 0.28571 0%
  • KGS/USD = 0.01144 0%
  • KZT/USD = 0.00200 0%
  • TJS/USD = 0.10468 -0.1%
  • UZS/USD = 0.00008 0%
  • TMT/USD = 0.28571 0%
  • KGS/USD = 0.01144 0%
  • KZT/USD = 0.00200 0%
  • TJS/USD = 0.10468 -0.1%
  • UZS/USD = 0.00008 0%
  • TMT/USD = 0.28571 0%
  • KGS/USD = 0.01144 0%
  • KZT/USD = 0.00200 0%
  • TJS/USD = 0.10468 -0.1%
  • UZS/USD = 0.00008 0%
  • TMT/USD = 0.28571 0%
  • KGS/USD = 0.01144 0%
  • KZT/USD = 0.00200 0%
  • TJS/USD = 0.10468 -0.1%
  • UZS/USD = 0.00008 0%
  • TMT/USD = 0.28571 0%
  • KGS/USD = 0.01144 0%
  • KZT/USD = 0.00200 0%
  • TJS/USD = 0.10468 -0.1%
  • UZS/USD = 0.00008 0%
  • TMT/USD = 0.28571 0%
  • KGS/USD = 0.01144 0%
  • KZT/USD = 0.00200 0%
  • TJS/USD = 0.10468 -0.1%
  • UZS/USD = 0.00008 0%
  • TMT/USD = 0.28571 0%
  • KGS/USD = 0.01144 0%
  • KZT/USD = 0.00200 0%
  • TJS/USD = 0.10468 -0.1%
  • UZS/USD = 0.00008 0%
  • TMT/USD = 0.28571 0%

Viewing results 1 - 6 of 9

Kazakhstan Adopts Pragmatic AI Regulation in Financial Sector

As of early 2026, the global financial market faces a strategic choice: impose tighter restrictions on artificial intelligence or allow the technology to evolve within existing regulatory frameworks. While the European Union has opted for comprehensive regulation, Kazakhstan has adopted a more pragmatic approach. According to the National Bank of Kazakhstan, approximately 75% of the country’s banks already use AI technologies— a share that has risen steadily over the past year — and 88% plan to expand their use. This indicates that AI integration is no longer experimental but systemic within the financial sector. Banks are increasingly deploying AI in credit underwriting, fraud detection, and anti-money-laundering transaction screening Madina Abylkasymova, Chair of the Agency for Regulation and Development of the Financial Market, articulated the principle of technological neutrality as early as 2025: the regulator does not intend to introduce artificial constraints until uniform global standards for AI are established. In her view, existing regulatory frameworks remain sufficient. Cybersecurity requirements, data protection standards, and risk management rules continue to apply regardless of whether decisions are made by humans or algorithms. Accountability and oversight remain unchanged. Infrastructure Before Regulation At the same time, the market faces significant structural barriers. These include a shortage of specialists at the intersection of finance and data science, the absence of unified data standards, and the high cost of computing infrastructure. The introduction of additional “European-style” restrictions could disproportionately burden smaller market participants and potentially force them out of the sector. Over the past twelve months, discussions have shifted from pilot experimentation to operational scaling across core banking functions. Some market participants have privately expressed concern that regulatory lag could eventually create supervisory blind spots as AI models grow more complex. Recognizing the high cost of entering the AI ecosystem, the state is assuming an infrastructural role. Timur Suleimenov, Governor of the National Bank of Kazakhstan, operating within the broader digital modernization agenda supported by President Kassym-Jomart Tokayev has outlined a strategic objective: to establish secure and scalable infrastructure to support AI development in the financial sector. This includes the launch of domestic data centers and the expansion of partnerships with global technology companies. The stated goal is to strengthen technological sovereignty and ensure the protection of citizens’ personal data. In practical terms, the regulator aims to create a sovereign “sandbox” in which fintech companies can test algorithms without transferring sensitive information to foreign servers. Supervisory Modernization The rapid expansion of AI also requires a transformation of supervisory practices. Currently, 39% of financial organizations in Kazakhstan use neural networks in some capacity. Over the past year, the number of companies that have progressed from pilot projects to partial implementation has nearly doubled. International institutions, including the Bank for International Settlements and the International Monetary Fund, argue that AI does not generate fundamentally new categories of risk. Rather, it accelerates and amplifies existing risks, credit, market, and operational. This suggests that regulators do not need to rewrite foundational rules but must enhance the speed, scale, and depth of...

Kazakhstan to Launch AI Fund Backed by National Bank

Kazakhstan will establish a dedicated Artificial Intelligence Fund to finance digital and educational initiatives, Deputy Prime Minister and Minister of Artificial Intelligence and Digital Development Zhaslan Madiev announced at an expanded government meeting. According to Madiev, the fund will be capitalized using resources from the National Bank, with the government currently finalizing its financial and organizational structure. The fund is expected to serve as the main vehicle for identifying and supporting priority AI and digitalization projects, as well as educational programs. Madiev cited international precedents, noting that leading technological nations allocate between 4% and 6% of GDP to digital development and artificial intelligence over three years. Based on ministry projections, such investments could yield a multiplier effect of 5 to 1, with the potential to contribute up to 1.5% of GDP annually in additional economic growth. One of the fund’s key focuses will be integrating AI solutions into Kazakhstan’s public and quasi-public sectors. Simultaneously, the country is pursuing international tech partnerships. With presidential backing, Kazakhstan has approved the creation of a joint venture with Chinese artificial intelligence firm 01.AI. Scheduled to launch in March, the venture will operate the National Artificial Intelligence Platform and focus on developing AI agents to enhance public sector decision-making. 01.AI is a startup founded by former Google China CEO Kai-Fu Lee. The company is best known for its open-source language model Yi-34B, positioned as an alternative to ChatGPT. At the meeting, President Kassym-Jomart Tokayev emphasized that AI is a foundational pillar of Kazakhstan’s emerging economic model. Anticipated benefits include increased labor productivity, growth in export-oriented industries, higher production of high value-added goods, and deeper integration into global digital networks. However, Tokayev also cautioned against using insufficient digitalization as a scapegoat for systemic inefficiencies. “Technology should not serve as an excuse for management shortcomings,” he noted. As previously reported by The Times of Central Asia, Kazakhstan joined OpenAI’s “Education for Countries” initiative, aimed at integrating AI tools into national education systems.

Household Debt Persists Despite Lending Slowdown in Kazakhstan

At the start of 2026, Kazakhstan’s financial indicators appear promising: the population is borrowing less, and banks are increasing financing to businesses. Yet behind this macroeconomic optimism lies a more complex picture. The debt burden on citizens has not disappeared; it has simply changed form. While less visible in financial reports, household debt is becoming increasingly evident in everyday family budgets. Two Realities, One Economy Madina Abylkasymova, chair of the Agency for Regulation and Development of the Financial Market, reported to President Kassym-Jomart Tokayev that consumer lending has slowed, while business lending has begun to grow steadily for the first time in three years. Data from the National Bank confirm this trend. In 2024, lending to individuals increased by 23.5%. By the end of 2025, growth had slowed to 17.7%. Business lending, meanwhile, accelerated from 17.9% to 19%. From a macroeconomic perspective, the regulator has met its interim objective: banks are channeling more resources into the productive economy. However, an analysis of second-tier banks’ portfolios suggests that a fundamental imbalance persists. Excluding development institutions and the quasi-public sector, end-of-year data show household debt to commercial banks at $55.1 billion, compared with business debt of 15.4 trillion tenge, or approximately $34.2 billion. The resulting $22.2 billion gap points to a structural issue: individuals remain the primary source of income for major private banks, including Halyk Bank, Kaspi Bank, and Bank CenterCredit (BCC), while the real sector continues to be underfinanced by market-based institutions. Shift to Installment Plans In 2025, under pressure from regulators, banks tightened lending standards for consumer loans. Traditional cash loan issuance slowed significantly. Despite this, total household debt continued to grow. According to the National Bank, the consumer loan portfolio expanded by KZT 2 trillion in the first half of 2025, reaching $55.1 billion by year’s end. This growth was driven not by large loans but by installment plans and Buy Now, Pay Later (BNPL) services. The number of loan contracts is rising much faster than the number of borrowers, a classic sign of demand fragmentation. Instead of a single large loan, citizens are taking out multiple small loans for food, clothing, and everyday necessities. This reflects declining purchasing power. Inflation reached 12.3% by the end of the year, with food prices rising 13.5%. At the same time, official data shows real incomes fell by 2%. Installment plans, once used primarily to purchase durable goods, are increasingly being used to “make ends meet.” Statistically, this appears as a reduction in average loan size and risk exposure. In reality, it points to growing debt dependency among households. Why the Bankruptcy Law Has Fallen Short The 2023 law on restoring personal solvency and bankruptcy was designed to address over-indebtedness structurally. But by early 2026, it was clear the system was functioning unevenly. Data from 2025 reveals the scale of rejections. Of more than 270,000 submitted applications, only about 34,000, just 12%, were approved. Approximately 87% of applicants received official denials. The main reason lies in strict eligibility criteria. For out-of-court...