Straight Talk Special Issue: Financial Services - 20

Emerging Technology
Our latest innovation is the
creation of the Emerging
Technology Group. It's a team of
approximately ten staﬀ members
globally, run by our CTO, whose
mission is to explore new
technology by testing it's
application to a variety of business
problems and opportunities. The
idea is to run "strategic
experiments" through
partnerships with some of our key
suppliers in new areas of
opportunity. Right now, the group
is focusing on analytics,
distributed ledger technology, AI,
and large-scale data manipulation.

skin in the game, ensuring that
there is true commitment. The
logistics are typically a
six-to-eight weeks experiment
that teaches us something about
an important technology, and
that may or may not lead to a
business opportunity for us
collectively in the future.
This team has helped us make
some important advances. We
are implementing a truly
distributed database that should
prove to be highly scalable and
reliable. Very few companies
have done that. A distributed
database is hard to come by: the
architecture has to be foolproof,

Those contributing to the tests/ experiments
in the form of POCs often are happy to have
skin in the game.
Most of the ideas we're
evaluating through testing begin
with a business idea or with a
problem that a client, business
area, or a key supplier brings to
our attention. We're fortunate
enough to have trusted
relationships with clients and a
great brand in the market. This
makes it easier to move from
ideas into agile experiments-
proofs of concept-not only with
clients but also with existing and
potential suppliers of technology,
who are often knocking on our
door to sell us things. Those
contributing to the
tests/experiments in the form of
POCs often are happy to have

20

especially when you're running
data businesses, stock
exchanges, and securities
clearing businesses.
We've recently run a
proof-of-concept data lake to
bolster the LSE's stock market
surveillance capability. It's built
out of open source technology
and includes some algorithms
that we've developed as well as
purchased, and it makes it
easier to detect unusual activity
anywhere in the system. It
enables our surveillance
analysts to be more productive,
making them smarter and their
jobs easier.

There are probably a dozen
other areas where we could
also be experimenting with AI
and sooner or later we will. I
can't think of a way we work
where AI won't beneﬁt us at
some point down the road.
Of course we're doing work with
blockchain technology, focused
on the Hyperledger open source
implementation of distributed
ledger functionality. We've
selected Hyperledger due to the
fact that it is open source and it's
not clear yet which of the
proprietary solutions will
become more standardized.
We've done a few proofs of
concept which include trade
reconciliation, and digitized stock
certiﬁcates, to name a few.
Overall, it's a very immature area
and there's a lot of development
and experimentation that's still
going to take place, where one
can see broad applicability over
time. As with any speculative
investment, there will be
numerous winners and losers.
We don't see ourselves making a
series of relatively small
investments in tech or ﬁntech
companies that are part of the
blockchain/DLT ecosystem.
Rather, we want to implement
solutions in regulated entities as
a way of proving the technology
Straight Talk Special Issue: Financial Services

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