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The three barriers stopping AI agents from executing trades
AI agents are already moving into financial-market workflows, but when will they actually be trusted to execute trades?
In this conversation, David Rickard, Global Head of Fixed Income at LSEG, explains why AI-powered trade execution is closer than many people think, but still faces significant challenges.
We explore the three major barriers: the difficulty of processing real-time, low-latency data; governance and trust around automated execution; and the fragmented, deeply entrenched legacy systems that underpin many trading workflows.
David also explains why fixed income is particularly difficult to electronify, how AI is already being embedded into trading workflows, and what needs to change before AI agents can move from assisting traders to actually executing trades.
David Rickard
Global Head of Fixed Income, LSEG
David Rickard is Global Head of Fixed Income at LSEG. He joined Refinitiv, then the Financial & Risk business of Thomson Reuters and now part of LSEG, in 2015 as a fixed income and derivatives market specialist for buy-side and sell-side clients in the Pacific region. He moved to Hong Kong in 2019 to lead market development for the Refinitiv trading desktop, later becoming Global Director of Trading Desktop for FX, money markets and derivatives. Before Refinitiv he spent more than a decade as an Associate Director in financial markets at Westpac Institutional Bank and St. George, working across fixed income sales, derivatives and short-term money markets and on funding programmes for securitised products including ABS and MBS.