Prospects and Legal Aspects of Using Artificial Intelligence in the Research and Statistics of the Central Bank of the Republic of Uzbekistan

By Ulug’bek Khamidjonov, Head of Statistics and Research Department, Central Bank of the Republic of Uzbekistan

Artificial Intelligence (AI) has become a transformative tool for central banks around the world. Increasingly, it is used for analyzing statistical data, building economic forecasts, assessing risks, and ensuring financial stability. The Central Bank of the Republic of Uzbekistan is also making significant progress in this area. Leveraging AI to collect, process, and analyze statistical information not only improves data accuracy but also enables more efficient policy-making. However, while the benefits of AI are clear, its use also raises important legal, ethical, and regulatory questions that must be addressed.

Recent data highlights the rapid pace of digitalization in Uzbekistan’s banking sector. For example, in 2023 the number of users of remote banking services grew by 56.3 percent, increasing from 20.8 million to 32.6 million in a single year. This growth demonstrates both the expanding role of financial services beyond physical branches and the increasing volume of data that central banks must process and analyze.

Moreover, interbank payment transactions processed through the Central Bank’s systems grew 1.5 times in 2022 compared to 2021, reflecting the wider adoption of digital technologies, including contactless payments. Another promising initiative is the Central Bank’s project “Forecasting Banking System Liquidity Using Payment System Data in Uzbekistan.” This project applies neural networks and machine learning models to payment system data in order to develop liquidity forecasts. Such innovations highlight how AI could enhance the Central Bank’s ability to issue early warnings about liquidity shortages or excess reserves, thereby safeguarding financial stability.

Prospects of AI in Central Bank Research and Statistics

The prospects for AI in the Central Bank’s research and statistical functions are significant:

1. Improved forecasting and analysis. Machine learning models can analyze vast datasets and detect patterns that are not always apparent through traditional statistical methods. For instance, AI-driven liquidity forecasting provides policymakers with quicker and more accurate signals, reducing systemic risks.

2. Optimized data collection. Technologies such as Computer-Assisted Telephone Interviewing (CATI) streamline the process of gathering survey data, reducing costs while improving speed and accuracy.

3. Enhanced data integration. AI can facilitate greater information exchange between government agencies such as the tax authority, customs, and commercial banks. This integration reduces errors, enhances monitoring of financial risks, and speeds up decision-making.

4. Real-time monitoring. With AI, it becomes possible to track payment flows, inflation indicators, and financial stability metrics in real time, offering a more dynamic picture of the economy.

These prospects show that AI has the potential to make statistical research faster, more accurate, and more actionable in shaping monetary policy.

Challenges and Legal Considerations

Despite its potential, the adoption of AI in the Central Bank’s research and statistics also brings challenges that cannot be ignored:

1. Data privacy and protection. Statistical research often involves sensitive financial and personal information. Laws must clearly regulate how data is collected, stored, and shared when processed by AI.

2. Algorithmic bias. AI systems trained on historical datasets may replicate existing inequalities across regions, genders, or social groups. Without careful monitoring, this could lead to distorted forecasts and unfair policy outcomes.

3. Transparency and explainability. AI models are often perceived as “black boxes.” For policymakers, courts, and the public, it is critical to understand why and how an AI model produces its forecasts. Lack of explainability undermines trust.

4. Legal accountability. If AI-based forecasts or analyses are flawed and lead to poor policy decisions, who is responsible—the developer, the data provider, or the Central Bank itself? This question remains unresolved in most jurisdictions.

5. Weak regulatory framework. Uzbekistan currently lacks a comprehensive legal framework governing AI and big data technologies. While strategies and policy documents exist, they do not fully address the specific standards, transparency requirements, and citizens’ rights issues that arise when AI is used in statistical analysis.

6. Institutional preparedness. The effective application of AI requires infrastructure such as powerful servers, reliable data centers, and high-quality datasets, as well as a skilled workforce trained in data science, machine learning, and statistical modeling.

These challenges demonstrate that successful adoption of AI depends not only on technological readiness but also on strong legal and ethical safeguards.

Proposals for the Effective and Responsible Use of AI

To fully realize the benefits of AI while addressing these challenges, the following proposals are recommended:

1. Strengthening the legal framework. Uzbekistan should adopt dedicated laws and regulations on AI use in statistics and financial research. These should define liability rules, establish supervisory authorities, and introduce certification systems for AI models used in official statistics.

2. Independent oversight and audit. AI models should be regularly evaluated not only by internal experts but also by independent auditors and international organizations. This would ensure accountability, improve model quality, and enhance public trust.

3. Data integration and unified ecosystems. A national data ecosystem should be created by integrating datasets from tax authorities, customs, financial institutions, and government agencies. Real-time access to this ecosystem would significantly improve the reliability of economic forecasting.

4. Capacity building and research centers. The Central Bank should establish a specialized research center on AI and statistics, possibly in cooperation with universities. This center could train young researchers, support doctoral programs, and produce cutting-edge AI-based models for central banking.

5. Transparency and public engagement. Forecasts and analyses produced with AI should be presented in an understandable format for the public, researchers, and policymakers. The Central Bank could publish regular reports explaining the logic and methodology behind AI-driven models, following international “explainable AI” standards.

6. International cooperation. The Central Bank should strengthen ties with international institutions such as the European Central Bank, Bank for International Settlements, and the IMF. Joint projects would allow Uzbekistan to import best practices, benefit from global expertise, and avoid costly mistakes.

7. Technical infrastructure and cybersecurity. Investment in secure data centers, encrypted communication channels, and strong cybersecurity protocols is essential. AI-based models must operate in an environment that ensures both reliability and protection of sensitive data.

8. Clarifying legal accountability. A clear distribution of responsibility should be established: the developer of the AI system, the institution applying it, and the supervisory body should all have defined obligations. This clarity would help avoid legal disputes in cases of flawed outputs.

9. Ethical standards. A code of ethics should be introduced to prevent discriminatory or biased outcomes when AI processes statistical data. These standards would reinforce public trust in AI-driven policymaking.

10. Phased implementation. AI should be introduced gradually. The first stage could focus on liquidity forecasting, followed by inflation modeling, and later broader financial stability indicators. Each stage should be accompanied by monitoring, evaluation, and public reporting.

Conclusion

Artificial intelligence represents a new frontier for the Central Bank of the Republic of Uzbekistan in its research and statistical work. If properly implemented, AI will allow the Central Bank to deliver faster, more reliable, and more transparent analyses that strengthen monetary policy and financial stability. Yet technology alone is not enough. Legal frameworks, ethical standards, accountability mechanisms, and public engagement are equally important to ensure that AI-driven statistics are trustworthy, responsible, and aligned with the principles of good governance.

By combining innovation with responsibility, the Central Bank of Uzbekistan can position itself at the forefront of AI adoption in financial research—not only regionally, but also globally.