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part of traders ’ day to day where accurate calculations based on the best data is paramount .
AI , for all its merits , has arguably just not been developed with the financial industry in mind and thus is often not in tune with its intricacies and structures .
As Charlie Flanagan , head of applied AI at Balyasny Asset Management , asserts , “ a lot of the wariness also comes because AI models are known not to be good at certain tasks and this taints opinion when it comes to others . For example , AI models are not good at maths - that ' s just not what they ' re trained to do .”
However , he adds that though concerns are not just expected , but valid , this should not dissuade firms .
“ The key is to educate [ our ] internal users and explain that they shouldn ’ t get spooked because when it comes to the analytical path the potential is there .”
Evidently , across asset classes , and in fixed income specifically , the future is set to be more electronified thanks to both AI and big data , however it ’ s important to consider the minutiae of each asset class .
“[..] 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 ,” said Khursheda Fazylova , fixed income trader , assistant vice president at SSGA , speaking to The TRADE earlier this year .
The task at hand When it comes to AI , it ’ s easy to understand the market ’ s caution considering this unprecedented challenge . As a result , a wealth
“[…] At the end of the day , before trust comes education . It ' s about helping folks understand where these models can add value right now and where they can ’ t .”
CHARLIE FLANAGAN , HEAD OF APPLIED AI AT BALYASNY
ASSET MANAGEMENT
of structural changes and AI-focused hires are being made across the industry to offer the best possible support .
As firms seek to evade potential snags , a large degree of the focus is on education - both internally and externally . Flanagan himself joined Balyasny from Google last year as the firm sought to strengthen the data science side .
He tells The TRADE : “ A lot of my role and the role of my team is connecting the dots and finding commonalities across teams . If something is working really well in one team or one vertical within the firm it then becomes about translating that . It ' s never a direct translation but taking the lessons about the AI technology that ' s working well somewhere and then
74 // TheTRADE // Q3 2024