Conference Dailys TRADETech Daily 2019 - Wrap-Up Issue - Page 16

THETRADETECH DA I LY in-depth THE OFFICIAL NEWSPAPER OF TRADETECH 2019 ‘We can’t do what we did 20 years ago’: AXA’s trading head sees need for AI and predictive analytics due to information overload THETRADETECH DAILY in-depth THE OFFICIAL NEWSPAPER OF TRADETECH 2019 Global asset managers require ‘global backbone’ to address organisational complexity STREAMLINING TRADING TECHNOLOGIES IS A VITAL ELEMENT TO SUSTAINING SCALABILITY AND GROWTH FOR GLOBAL AS- SET MANAGERS SAYS BNP PARBIAS ASSET MANAGEMENT’S COO. AXA’S GLOBAL HEAD OF TRADING AND SECURITIES FINANCING SAYS THE ASSET MANAGER WILL HAVE TO RELY ON AI AND PREDICTIVE ANALYTICS TO GIVE TRADERS CONDENSED INFORMATION. T he sheer magnitude of trades and markets that buy-side desks are participating in is forcing the need for artificial intelligence (AI) and predictive analytics, according to AXA Investment Managers’ global head of trading. Daniel Leon, who also heads up securities financing for the French asset manager, said the firm has to invest in new technologies because traders simply cannot keep up with the amount of information required across its ever-increas- ing volumes of trades. “We are not able to do what we used to do 20 years ago,” said Leon. “Yes, you can have a specialist on leverage loan, you can have that, but on the big credit market or medium and small-cap you cannot have all that information in one guy. “We are trying as well to solve problems that we used to do a long time ago. For the more vintage traders – I started on FX options desk in charge of research – it used to be that the trader would know the market and what’s traded for one month, what happened last week, they had information and that’s what typical trading used to be. “But now we have to gain efficiency, we have to trade so many bonds that you can’t ask one trader to remember everything to know that this sector last week had this event. We have to reconstitute the experience that the trader used to have. What has traded, what was the liquidity and what was the market impact. You can’t do that on a comprehensive basis.” It’s been widely accepted that AI and machine learning technologies have the potential to fundamentally improve trader performance, whether it’s now or in the future. A poll during Leon’s panel however, showed that 62% of traders are currently not engaged directly in the use of AI tools. On a recent webinar with The TRADE, Ashwin Venkatraman, global head of equity trading automation and execution at JP Morgan Asset Management said the use of AI on trading desks should ultimately be geared towards providing as much relevant and condensed information as possible to the trader. During a buy-side keynote interview at this year’s TradeTech conference, Supurna VedBrat, the global head of trading at BlackRock, also 16 THETRADETECH DAILY “We have to reconstitute the experience that the trader used to have… You can’t do that on a comprehensive basis.” DANIEL LEON, AXA INVESTMENT MANAGERS said that while gaps in liquidity present issues for all market participants, artificial intelligence and data science are key tools for BlackRock in going forward with these trading challenges. Research from TABB Group recently showed that the majority of buy-side firms anticipate an A sset managers are continuing to consolidate their technology provider lists and systems stack to support global growth and scalability as part of their operational objectives, according to buy-side executives. During a keynote buy-side interview, BNP Pa- ribas Asset Management’s COO, Fabrice Silber- zan, outlined how for buy-side firms with scale and volumes of trading channels on a global level, there is a vital requirement for common understanding when it comes to front-office technologies for trading strategies. Speaking to Allianz’s global head of trading, Eric Boess, Silberzan said that the firm had re- cently moved from using several disparate sys- tems to a single provider: “Systems can be very effective in doing specific things but at some stage you will need a backbone, something that you can share across the organisation and that goes above and beyond a given functionality.” “We have moved from a world where we had six or seven portfolio management systems, dif- ferent OMS, resulting in a complexity in dealing with data management and analytics that were useful for portfolio managements and clients, hence our decision to go for one large system,” he explained. BNP Paribas Asset Management currently manages around $400 billion in AuM across its global strategies, and Silberzan acknowledged that the counterpoint to adopting a holistic technology approach to manage such operations is that single systems can, in some cases, be inflexible in the face of such complexity. One way to address this is to ensure tight integration between the trading system and that firm’s wider technology architecture, which, according to Silberzan can provide scale and provide the tools necessary for users to handle various regional frameworks regardless of their location or what strategy they are working under. Allianz’s Boess noted the importance of standardisation for firms operating to such scale, particularly to manage costs, pointing out that asset managers face a problematic decision between opting for one large-scale system that can handle most challenges or smaller, nimbler systems that can provide specific solutions to specific challenges. “Think of MiFID II research payments, where Europe has pretty much gone totally unbundled, Asia is still pretty much bundled in many areas and the US is largely bundled but somewhere in between - you have to cater for all of these different frameworks,” Boess said. As Silberzan acknowledged, there will never be “one system doing everything for you”, so firms must instead “cluster their needs” around a central data hub, where firm-wide data can be consolidated and managed, from which appli- cation program interfaces (APIs) and additional services can be plugged in. Ultimately, he said, many firms are now at a turning point, and new technology oppor- tunities, such as those borne out of artificial intelligence and machine learning adoption, can be the difference for asset managers that are aiming to, or seeking to manage, operating at global scale. “I believe that what we see today will be very different from what we are going to see in only two years, while this will be more common and portfolio managers will have to adapt to that; some will do incredibly well and some will keep on doing some form of magic out of technology, which sometimes works well and sometimes works less,” Silberzan concluded. increased spend on AI technology over the next 12 months. The research group also surveyed 160 buy-side, sell-side and exchanges on their use of the technology and found that current internal budgets are modest, with 75% of re- spondents revealing they either have no budget in place, or a budget of up to $500,000. However, 61% of asset managers said that they expect spend on AI technology to increase over the next 12 months, while 39% expect it to remain the same. At the same time, 80% of sell-side firms and 55% of exchanges, or trading venues, anticipate increased spend. “If you’re in trading you have no choice but to invest into a serious amount of data analytics – advanced data analytics,” added Leon. “You have to somehow be able to turn the market into something you understand. If you are not rebuilding liquidity at your level then you’re just not able to see what you need to do.” Issue 2 17