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
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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
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