Conference program

The presentation explores the opportunities and research areas in AI for enhancing central bank operations, from economic analysis to real-time data insight, with a focus on the innovative solutions implemented by the MNB. There will be 2 projects presented: the first part delves into NLP-driven sentiment analysis of the Hungarian economy, showcasing a method to extract timely signals from online news text and to use them for macroeconomic nowcasting. The second part discusses and analysis of the online cash register data using NLP and deep learning techniques.

This presentation showcases the Central Bank of Nigeria's venture into AI, spotlighting the progress made, promising prospects, potential gains, and obstacles faced. It uncovers the impact of AI applications, emphasizing achievements and outlining future opportunities. Also, it addresses challenges, including regulatory and ethical considerations, while underscoring the Bank's dedication to responsible AI integration. The presentation concludes with a forward-looking perspective on how AI can enhance the Bank's operations and contribute to economic development.

Over several decades, banks have continually adapted the latest technologyinnovations to redefine how customers interact with them. Banks introduced ATMs inthe 1960s and electronic, card-based payments in the ’70s. The 2000s saw broadadoption of 24/7 online banking, followed by the spread of mobile-based “banking onthe go” in the 2010s.Few would disagree that we’re now in the AI-powered digital age, facilitated by fallingcosts for data storage and processing, increasing access and connectivity for all, andrapid advances in AI technologies. These technologies can lead to higher automationand, when deployed after controlling for risks, can often improve upon human decisionmaking in terms of both speed and accuracy.In this speech, I will cover what the Future of AI in Central Banking and Financial Services is.

Drawing from nearly a quarter-century of collaboration with global lending, fintech, and insurance leaders, this presentation illuminates the art and science of building machine learning and AI models. It showcases successful applications and cautionary tales, revealing the keys to effective algorithmic implementations. By exploring the realms of promise and peril, the talk offers valuable insights into understanding algorithms while simultaneously ensuring they are fair, robust, and successfully implemented.

The last few months has increased awareness of the advances in Large Language Models with the release of ChatGPT. This talk will discuss the potential risks and opportunities of using large language models like ChatGPT in financial services. These models have the potential to revolutionize the industry by processing vast amounts of data and providing sophisticated insights. However, the risks associated with these models include bias, lack of transparency, and overreliance on the technology. The talk will explore ways to mitigate these risks and maximize the opportunities presented by ChatGPT and other large language models.

This panel will examine various scenarios for the future role of AI in central banking. The most important trends and possible paths to a future with AI will be highlighted. The opportunities and risks will also be discussed.