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Kuwait’s banking sector demonstrates resilience with record low NPL ratio

• Kuwaiti banks boast a historically low non-performing loan (NPL) ratio of 1.42%.

• Strong financial position indicators suggest the banking sector can withstand economic pressures.

• Central Bank of Kuwait (CBK) to maintain monetary and financial stability while promoting sustainable growth.

• CBK report explores both the advantages and challenges of Artificial Intelligence (AI) in central banking.

The Central Bank of Kuwait (CBK) has released a report stating that the non-performing loans (NPLs) ratio in Kuwait has remained at its lowest level in history, at 1.42%.

The CBK’s report on “Artificial Intelligence: Between Advantages and Challenges” states that the prudent and proactive policies it adopts are aimed at directing banks to strengthen their financial buffers and fortify the banking sector to increase its ability to withstand external shocks. The report emphasizes that the banking sector remains capable of efficiently serving the national economy even under pressure, as confirmed by the strong and sound financial position indicators of Kuwaiti banks as of the end of December 2023.

These indicators include the high capital adequacy ratio (19.9%), the liquidity coverage ratio (169.3%), and the net stable funding ratio (113.3%). These ratios exceed the minimum requirements set by the CBK’s regulations. The report also highlights that the NPL ratio has remained at its lowest level in history, at 1.42%.

The CBK affirms that it will continue to closely monitor developments and changes in economic, monetary, banking, and financial conditions, and that it is ready to take action when necessary to direct various monetary policy tools in order to consolidate the environment that supports sustainable economic growth and preserve the competitiveness and attractiveness of the national currency as a repository for local savings, within the framework of maintaining monetary and financial stability.

Domestic scene

The CBK’s decisions regarding the formulation and implementation of monetary policy came within the framework of a gradual and balanced approach aimed at consolidating monetary and financial stability for banking and financial sector units, preserving the competitiveness and attractiveness of the national currency as a rewarding and reliable repository for local savings, and promoting an environment that supports sustainable economic growth.

The CBK also highlighted that the spreads between interest rates on deposits for both the Kuwaiti dinar and the US dollar remain in favor of Kuwaiti dinar deposits. This enhances the CBK’s ability to maintain the stability of the dinar exchange rate and prevent any speculative operations that may occur to take advantage of the price differences between the US dollar and the Kuwaiti dinar.

In this context, the spread between the weighted averages of interest rates on customer deposits with local banks in both the Kuwaiti dinar and the US dollar for one-month deposits was about 0.6927 percentage points, compared to about 0.6696 percentage points in January of the previous year, and about 0.7202 percentage points for three-month deposits, compared to about 0.786 percentage points in January of the year.

Artificial Intelligence

The CBK stated that we are currently experiencing a tremendous technological revolution capable of stimulating productivity, promoting global growth, and increasing income around the world.

However, this technology can replace a range of jobs. Therefore, there are many questions about the potential impact on the global economy, and it is difficult to predict the net impact at this time, given the potential for AI to spread across economies in complex ways. It is therefore important to develop a set of policies to safely exploit the vast potential of AI for the benefit of humanity.

The CBK added that it is important to adopt a thoughtful and balanced approach when integrating AI programs into economic policies. This requires continuous cooperation and dialogue between stakeholders, including policymakers, experts, and technicians, to strike a balance between innovation and regulation.

Regulations should be flexible, allowing for the exploitation of recent developments in AI and harnessing all its potential on the one hand, and taking precautions and mitigating potential risks on the other. This will allow societies to benefit from AI to enhance human potential, achieve well-being and sustainable growth, and ensure a more equitable and secure digital future.

Application of AI in central banking

The CBK also discussed the potential for AI to be applied in the work of central banks. It stated that since the global financial crisis of 2008, central banks have faced additional emerging burdens that are not only related to maintaining price stability, the stability of the exchange rate of national currencies, and the financial sector, but have also focused on areas of measuring systemic risks, digital currencies, and climate change. These responsibilities rely heavily on all new data sources and access to them, which is known as big data, which is usually characterized by its large size, multiple dimensions, and irregular nature.

The CBK added that central banks have access to massive amounts of data to facilitate monetary policy decisions, and they can also extract data from different sources. However, the bulk of the data relies on small transactions between businesses and individuals (e-commerce, credit card transactions). Therefore, the importance of AI technologies in the field of decision-making by central banks lies in collecting, organizing, and analyzing data at the economic and financial level. These technologies can be used to:

1. Enhance the collection and analysis of macroeconomic data: AI can efficiently collect and analyze large amounts of data on macroeconomic indicators, which can help predict economic cycles by analyzing GDP components and inflation rates. It can also monitor commodity prices and labor market conditions.

2. Improve bank supervision and assess financial sector risks: AI can enhance bank supervision by automating the collection and analysis of large financial datasets. It can detect patterns that indicate potential risks or fraud, leading to more efficient and proactive risk supervision. It can also enhance compliance and provide instant access to bank data, making the financial system more resilient and secure.

3. Enhance anti-money laundering efforts: AI can enhance the effectiveness and efficiency of money laundering and financial crime investigations and risk management in financial and non-financial institutions by detecting suspicious activities and tracking financial flows.

4. Improve credit risk analysis: AI programs can collect and analyze customer credit score data and classify it while assessing default risk.

5. Improve operations: AI improves operations by speeding up reporting and analysis, leading to increased productivity and responsiveness.

Challenges and risks associated with the adoption of artificial intelligence

  • Data inadequacy: AI models may suffer from algorithmic bias due to incomplete data or human factors, such as decisions made by AI model engineers during development.
  • Privacy concerns: AI technology is vulnerable to unauthorized access to sensitive data of individuals, companies, or government entities. AI programs typically process massive amounts of data, making data privacy strategies crucial.
  • Cybersecurity threats: AI programs can be targeted by cyberattacks and manipulated to provide users with inaccurate data. For example, a third party could feed a new set of instructions to an AI model, deceiving it into generating false outputs for the end-user.
  • Interpretability challenges: AI relies on neural networks with numerous parameters, making it difficult to understand how output data is generated.
  • Reliability issues: AI programs may produce varying outputs for the same input commands, undermining the accuracy and reliability of results.
  • Regulatory complexity: As AI regulations evolve, companies may face an increasingly complex regulatory landscape, which could heighten their exposure to regulatory risks.
  • Non-financial risks for companies: Overreliance on AI without proper attention to training, capacity building, governance, and data protection can increase operational risks. These operational risks may eventually translate into financial risks.
  • Uneven access: Adoption of AI technologies remains uneven and unbalanced. Access to AI technologies is not uniform across countries, companies, and individuals. Parties with greater financial resources and infrastructure may benefit more from AI technologies, leading to a widening economic inequality gap between countries and companies in different economies. A wage inequality gap is also expected to follow, with individuals possessing the technical skills required for AI development, implementation, and management having better economic opportunities than those with lower-level skills.


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