Listing 1 - 3 of 3 |
Sort by
|
Choose an application
Using the 2010, 2015, and 2020/2021 datasets of the IMF’s Central Bank Legislation Database (CBLD), we explore artificial intelligence (AI) and machine learning (ML) approaches to analyzing patterns in central bank legislation. Our findings highlight that: (i) a simple Naïve Bayes algorithm can link CBLD search categories with a significant and increasing level of accuracy to specific articles and phrases in articles in laws (i.e., predict search classification); (ii) specific patterns or themes emerge across central bank legislation (most notably, on central bank governance, central bank policy and operations, and central bank stakeholders and transparency); and (iii) other AI/ML approaches yield interesting results, meriting further research.
Artificial intelligence --- Banking --- Banks and Banking --- Central bank autonomy --- Central bank governance --- Central bank legislation --- Central bank transparency --- Central Banks and Their Policies --- Central banks --- Currency crises --- Diffusion Processes --- Economic & financial crises & disasters --- Economics of specific sectors --- Economics --- Economics: General --- Forecasting and Other Model Applications --- Informal sector --- Intelligence (AI) & Semantics --- Large Data Sets: Modeling and Analysis --- Macroeconomics --- Technological Change: Choices and Consequences --- Technology
Choose an application
This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.
Artificial intelligence --- Banks --- Capital and Ownership Structure --- Computer security --- Cyber risk --- Depository Institutions --- Diffusion Processes --- Econometric and Statistical Methods: Special Topics: General --- Economic sectors --- Finance --- Finance: General --- Financial Institutions and Services: General --- Financial Institutions and Services: Government Policy and Regulation --- Financial Instruments --- Financial Risk and Risk Management --- Financial sector policy and analysis --- Financial sector stability --- Financial sector --- Financial services industry --- Financial services --- Financing Policy --- General Aggregative Models: Forecasting and Simulation --- General Financial Markets: Government Policy and Regulation --- Goodwill --- Industries: Financial Services --- Industries: Information Technololgy --- Information technology industries --- Information technology --- Innovation --- Institutional Investors --- Intellectual Property Rights: General --- Intelligence (AI) & Semantics --- Large Data Sets: Modeling and Analysis --- Machine learning --- Micro Finance Institutions --- Model Construction and Estimation --- Mortgages --- Non-bank Financial Institutions --- Online Safety & Privacy --- Pension Funds --- Research and Development --- Security measures --- Technological Change --- Technological Change: Choices and Consequences --- Technological innovations --- Technology --- Value of Firms --- Hong Kong Special Administrative Region, People's Republic of China
Choose an application
This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies.
Listing 1 - 3 of 3 |
Sort by
|