also fixed income, commodity, and currency markets. herd behaviour has always been a characteristic of financial markets. but herds of robots have proven to be far more deadly than herds of humans. the international organisation of securities commissions ( iosco ) has since mandated that exchanges have in place mechanisms to manage extreme volatility. and securities regulators have themselves started to use ai – to provide early warning of potentially disruptive ai - based trading patterns and trigger appropriate circuit - breakers. but more generally, the increased use of ai by financial institutions has created the risk of “ black boxes ” in decision - making. boards and senior management of financial institutions are struggling to validate ai - based models which use continuous learning and adaptation as distinct from fixed parameters and 6 / 9 bis central bankers'speeches historical back - testing. the application of ai in financial services has also created issues of financial exclusion which regulators cannot ignore. regulators have begun to detect cases where ai - based decision - making has led to systematic exclusion of certain demographics. when an ai tool finds an empirical basis for discriminating by a combination of variables such as gender, ethnicity, religion, and nationality, say for a loan or insurance decision, how much of that empiricism is grounded in reality and how much of it is due to unobserved biases in society that the ai is learning from? and even if such discrimination is backed by empirical unbiased data, is that a socially acceptable outcome? regulators in many jurisdictions have been engaging the industry as well as the broader society on developing guidance on the responsible and ethical use of ai and data analytics by financial institutions. defending against systemic cyber risk the third theme that stands out in the history of financial regulation over the last two decades is cyber security. but it was only after the global cyber crisis of 2023 that cyber risk management has moved to front and centre of the international regulatory agenda. the global cyber crisis laid bare our cyber vulnerabilities. a highly skilled and well - resourced group of hackers used ai - enabled malware to infiltrate banks across the world, subvert detection, and siphon monies. over a span of just 6 weeks, a total of us $ 45 billion was stolen from over 500 banks, leading to loss of public confidence and bank runs in several jurisdictions. only 8 % of the stolen funds has ever been recovered. the failure of algor bank at the height of the global cyber crisis demonstrated both the high points and low points in financial regulation.

more transparent, less risky, less costly. the three areas that saw the biggest transformations were in compliance, trade finance verification, and cross - border payments. as dlt systems became more pervasive, they began to assume properties of critical infrastructure with systemic implications. there were information security - related risks as well as operational risks associated with interoperability across multiple platforms. while strong cryptography is a feature of dlt systems, they are not immune to cyberattacks through the widely distributed network of participants. 4 / 9 bis central bankers'speeches and old - fashioned risks like not having enough liquidity to settle transactions can potentially lead to gridlocks in dlt systems which could, in turn, cause systemic risks. the trigger for a co - ordinated regulatory response to dlt came in the cross - border payments space. in 2020, the bank of canada and monetary authority of singapore successfully piloted a cross - border dlt - based system that achieved almost real - time fixed income securities trading and settlement. under the global payments accord of 2024, central banks agreed to upgrade their real - time gross settlement systems to a dlt - inspired infrastructure with a view to connect these systems for safer, faster, and more efficient cross - border payments and settlements. this called for internationally accepted standards for dlt - based payment systems. the fsb and standard - setting bodies worked closely with the newly - formed international organisation for distributed ledger standards to design a supervisory framework for dlt. dlt networks that performed key market functions like clearing and trade reporting were required to meet specified standards for settlement finality and the security of digital asset custody. making cloud computing services safer from about 2015, financial institutions increasingly began to use the cloud. with cloud computing, financial institutions could efficiently integrate customer data across platforms to enable sharper consumer insights. the cloud provided scalable storage solutions to meet the real - time demands of trading and analytics processes. some banks have even moved their core banking systems into the cloud to reap the benefits of its scalability and resilience. cloud computing has considerably enhanced risk management. risk assessments are now more comprehensive, more granular, and more real - time. but the cloud has also introduced new risks. the risks are not so much in the technology of cloud computing per se but in the business and operating models of cloud services. cloud services are essentially a utility provided by specialist third - party providers. and as with any third - party service provider, there are outs