This presentation will provide a technical basis for what AI is and situate many of the terms that can be associated with artificial intelligence for a better understanding of the following program.

Recent developments in AI technology have captured the world's attention, including in the central banking community. While the long term potential of AI remains to be seen, the rapid pace of innovation in AI technology and the new capabilities this has introduced are genuinely remarkable. These developments present exciting opportunities for central banks but also new types of risk that need to be managed, both in their own operations and in the financial sector more generally. This talk will provide a broad overview of the latest developments in generative AI, the key opportunities and risks these present for central banks, and how the industry is responding.

Every bank in Switzerland must operate an IT-based transaction monitoring system that enables it to identify conspicuous transactions. This is the only way that the due diligence obligations under money laundering law in connection with transactions with increased risks, such as clarification or reporting obligations, can be fulfilled at all. Based on a sound risk analysis, transaction monitoring systems must be tailored to the specific business model and customer structure of the bank in question and vary accordingly from bank to bank. In order to reduce the manual effort involved in transaction monitoring and to focus the resources of compliance staff as far as possible on relevant problem cases, banks are examining the use of systems based on so-called "artificial intelligence" (AI applications).

Implementing AI is a fairly new concept in many regulated spaces. Experimenting in this domain is necessary but comes with many things to consider. In this session, I will walk through the journey of implementing RPA and AI in the Bank of Canada's critical banking operations and share the lessons learned that will help future endeavors implement successfully and avoid un-known risks.

Artificial intelligence (AI) has the potential to revolutionize the financial industry, especially in developing economies. AI-powered financial services can help to improve financial inclusion, reduce costs, and increase efficiency. AI can also help to reduce the costs of financial services through AI-powered chatbots can automate customer service tasks, and AI-powered fraud detection systems can help to reduce fraud losses. Developing economies like Zambia is well-positioned to benefit from the promise of AI in finance because of the increasing populations of underserved individuals and businesses, and they are also often early adopters of new technologies

Artificial intelligence presents new challenges for organizations as the technology is implemented faster than the supporting processes, tools, and knowledge are created. Additionally, it can be hard to understand where the reality is with wild reporting and over-the-top claims. Covering the basics is necessary to solve safety, security, and privacy challenges and comply with regulatory guidelines. This presentation looks at the landscape of AI technologies with a particular eye toward risk and privacy concerns. We’ll look at some trends and provide guidance on where to start.

This panel discussion will explore the question of whether AI is friend or foe - or both? What does one mean and what does the other mean, and what needs to be done to use AI sensibly or to protect against it?

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.