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to its full potential , employing it to analyse sentiment , ideas , and conversations . It ' s in these areas that Gen-AI will truly stand out , providing a valuable enhancement to the conventional quantitative analyses focused on pricing and financial data ,” confirms Consigny .
Play by the rules James Hilton , head of multi-asset agency solutions at RBC Capital Markets , previously told The TRADE that though AI can be massively helpful in some areas going forward , those in the industry must “ make sure that we ’ re delivering these things in a responsible and ethical way and that you ’ ve got really strong governance around implementation .”
In this vein , comes the inevitable regulation factor . As regards AI , regulation is still largely in its infancy with watchdogs around the world not only at different stages in terms of rules , but also taking distinct approaches to the technology .
While financial sector regulation around AI in the EU is the most advanced when it comes to developing a regulatory framework , a federal AI legislation in the US appears less likely . The UK by comparison has opted for a principles-based approach without a great deal of detail and other regions currently differ between official rules and soft guidelines . Addressing market reaction , Strange says : “ Our clients are flagging the lack of direction and the bit of confusion across each of the jurisdictions . I work with global asset managers based in the US […] and there still seems to be a lack of priority when it comes to what is important .”
Though some watchdogs continue to put more and more regulatory proposals in place , clearly things are still relatively vague in terms of empirical guidance .
Speaking to the disconnect between the actual nature of this technology and how regulation essentially works , Cheung explains : “[ GenAI ] is probabilistic rather than deterministic , so it ' s essentially serving up its best estimate , regulators will never appreciate that .”
The tortoise not the hare When it comes to AI “ you could either be the fastest
“ Given how fragmented fixed income markets are and how illiquid some bonds are ( for example , high yield , convertible bonds , securitised , structured loans ), I suspect we still won ’ t be able to fully outsource trading to machines in the near future .”
KHURSHEDA FAZYLOVA , FIXED INCOME TRADER , ASSISTANT VICE PRESIDENT AT SSGA
or you can be best , and we all want to do both but there ’ s a lot of factors to consider ,” asserts Flanagan .
In essence , despite the rapid surge of AI innovation , it ’ s clear that slow and steady wins the race , especially when the stakes are so high . The most reliable proof of this is the fact that human intervention is still fundamental in these processes . We are far from the no touch stage .
As Cheung asserts : “ The nature of how AI systems work things out means they can ' t give you a definitive answer , so in most cases you need to retain a human in the loop . That might change in the future but for now that is the case .”
The evolution of AI is not a straight line and importantly what is essential to remember is that existing tools , honed over a long period of time and continually adapted in line with changing markets , have succeeded for a reason . Throwing advanced technology at a problem is not only risky , but not necessarily even the best answer . Balance is key .
In this turbulent period of intense innovation , weighing risk and reward has never been more important . AI is intriguing , but the market should continue to exercise patience , or face the – potentially catastrophic – consequences .
76 // TheTRADE // Q3 2024