April 20, 2024
A.I

From data to decisions: AI and monitoring

Article by Elizabeth McCaul, member of the ECB Supervisory Board, for Revue Banque

February 26, 2024

European banking supervision is committed to exploring the potential of AI to make the work of supervisors more efficient

In today’s digital age, new data is being generated at an exponential and unprecedented rate. The question is no longer about whether or not to use artificial intelligence, but rather how to use it more effectively and responsibly. AI offers enormous opportunities and promises to dramatically improve both the efficiency and quality of a wide variety of work-related processes. It can analyze large amounts of data quickly and accurately, improve risk identification by detecting patterns in the data, support decision making, and automate repetitive tasks, all of which can improve the work of banking supervisors. However, we also know that the use of AI carries risks that are not yet fully understood.

Banks also face the same dilemma. AI can improve the experience you offer your customers, increase your operational efficiency and strengthen your risk management processes. But challenges and risks abound when seeking to leverage AI capabilities, from data governance risks (related, for example, to the confidentiality and reliability of training data) to operational, model management and accountability risks. of emerging accounts. Banks are increasingly discovering that to remain competitive, they must embrace AI while meeting their risk management responsibilities.

So what does all this mean for banking supervisors?

The short answer is that we must take a future-proof approach to understanding and using AI. We should use it to improve our internal supervisory capabilities and gain a greater understanding of the risks faced by supervised banks as they, in turn, also implement AI. These risks are wide-ranging, affecting business models, governance frameworks, risk management processes and capital adequacy, as well as overall financial stability. Fundamentally, the role of ECB Banking Supervision is to ensure that banks remain safe and sound. It is not for us to dictate what business models banks adopt and what technologies they use. However, what we can do is harness the power of AI to decipher data, understand risks and speed up processes, freeing up more time for human analysis and judgment in an increasingly complex world.

From the beginning we recognized the need to embrace digital innovation and artificial intelligence to make European banking supervision more efficient and effective. We introduced an ambitious digital agenda to improve our analytical capabilities. We invest in a portfolio of supervisory technology (SupTech) applications to monitor a complex banking sector and manage an ever-expanding set of data and tasks. And we focus on the people who would use this technology: 14 applications and platforms have been developed in the last three years, serving more than 3,500 users across the ECB and national supervisors.

Today, our AI applications allow us to query supervisory data and employ chatbot functionality for regulatory and supervisory methodologies. In the area of ​​textual analysis, for example, our Athena application translates and analyzes the content of supervisory documents. You can combine this content with information from other sources, such as public media, allowing supervisors to increase their knowledge of banks and their risks.

In the field of big data analytics, GABI generates and optimizes large-scale regression models, allowing supervisors to base their analyzes on a much larger set of models and make more insightful comparisons than in the past. Of course, these models are still controlled by humans.

And in the field of network analysis, NAVI generates network diagrams to illustrate relationships in data. This allows users to visualize the often complex ownership structures of supervised banks and combines data from numerous sources to provide a comprehensive overview of bank owners and their interdependencies.

Other more specific SupTech tools include Heimdall, which supports experts in processing large amounts of incoming information to assess the suitability and ownership of members of the management body, and Medusa, which facilitates redaction and consistency checks. of reports following investigations of internal models.

Our investment in technology has allowed us to build a cutting-edge infrastructure to scale AI applications through the Virtual Lab, a cloud-based collaboration platform that offers machine learning capabilities and an easy-to-use environment for sharing and developing code. The Virtual Lab has not only improved collaboration within European banking supervision, but also enables the deployment of technology such as generative AI (a type of AI popularized by applications such as ChatGPT).

Generative AI has the potential to support the work of supervisors by making their daily tasks easier. In 2023, we collected more than 40 potential use cases from supervisors and developed several proofs of concept that demonstrate the potential of generative AI. The use cases we have tried to address include instantly retrieving answers to monitoring methodology questions, with clear references to internal methodologies, and automatically translating queries written in plain language into code to find specific data points.

The second of those use cases is particularly interesting. Agora, our only data lake for European banking supervision, currently requires users to have certain programming skills to access the database. But with the help of generative AI, which can automatically translate natural language queries into scripts, supervisors without programming experience can ask Agora where to find very specific data points. This is just one example of how generative AI, and AI in general, can make traditional technologies easier to use and put SupTech within the reach of supervisors.

Of course, it goes without saying that these tools are not intended to replace supervisors. Human judgment and experience are and always will be key to ensuring a reliable result.

Fostering a digital culture throughout our organization is crucial to our success. We regularly organize specific training courses for ECB and NCA staff with globally recognized providers, such as Coursera and INSEAD Business School. The aim is to improve the digital skills of our supervisors and raise awareness of recent technological developments and the latest relevant regulations (such as the new EU AI Law). We also host an annual conference that brings together leading digital experts from the supervisory community, academia and industry to strengthen our partnerships and facilitate the development of best practices.

When developing and implementing AI, we are obviously aware of the associated risks. For example, if we want to maintain trust in AI tools, it is essential that they are transparent and that we can explain how they work, given the potential “black box” nature of this technology. For this reason, we are working hard to provide strong organizational support and clear guidelines for the use of AI in banking supervision. At the same time, we continually strengthen our IT security to ensure we can securely host AI tools.

Looking ahead, we will continue to investigate the possibilities and challenges of using AI, in cooperation with supervisory authorities across Europe. Our goal is to harness the full potential of technology to make our supervisory work as efficient and effective as possible.

Leave a Reply

Your email address will not be published. Required fields are marked *