Central banks around the world are starting to use a new type of artificial intelligence (AI) called generative AI to improve their cybersecurity. This means they are using advanced computer programs to help protect their systems from hackers and other cyber threats. The Bank for International Settlements (BIS), an organization that supports central banks, has shared this information. Let’s explore what generative AI is, why central banks are interested in it, and how it can help enhance cybersecurity.

Generative AI is a type of artificial intelligence that can create new content, such as text, images, or even software code, based on the data it has learned from. Unlike traditional AI, which follows specific instructions, generative AI can generate new, original outputs by learning patterns from existing data. This makes it very powerful and flexible, capable of performing complex tasks.

Central banks manage the money supply and oversee the banking system in their countries. They handle a lot of sensitive information and must protect it from cyber attacks. Cybersecurity is crucial for central banks because any breach can lead to serious financial and economic consequences. As cyber threats become more sophisticated, traditional methods of cybersecurity are not always enough. This is where generative AI comes in.

Generative AI can help central banks in several ways. First, it can detect unusual patterns and activities that might indicate a cyber attack. For example, if someone tries to access a system in an unusual way, generative AI can recognize this as suspicious and alert the cybersecurity team. It can do this by learning what normal behavior looks like and identifying anything that doesn't fit this pattern.

Second, generative AI can simulate cyber attacks to help central banks prepare for real threats. By creating realistic scenarios, it allows cybersecurity teams to practice their responses and improve their defenses. This is like having a virtual training ground where they can test different strategies and see what works best.

Third, generative AI can help in developing stronger security systems. It can analyze existing security measures and suggest improvements. For example, it might find weak points in a system and recommend ways to strengthen them. It can also help in creating new encryption methods to protect data, making it harder for hackers to break in.

Another benefit of generative AI is its ability to respond quickly to threats. When a cyber attack happens, every second counts. Generative AI can act faster than human responders, identifying the threat and taking initial steps to contain it. This can significantly reduce the damage caused by an attack.

The use of generative AI by central banks is still relatively new, but it is growing. The BIS is encouraging central banks to explore this technology and share their experiences. By working together, central banks can learn from each other and develop better cybersecurity practices.