Name: Ipushpull on the use of AI in capital markets
Uploaded: 2023-12-04T14:23:57.460Z
Duration: 1528.72
Description: At FinTech Futures recent AI Insights event in London, we had the chance to sit down with Matthew Cheung, CEO of ipushpull, to discuss how artificial intelligence is being put to work effectively within the capital markets industry.

Revised Cheung Interview_NO BG MUSIC_TL_1.mp4

Revised Cheung Interview_NO BG MUSIC_TL_1.vtt

ENGLISH

Hello everybody and welcome to
Fintech Futures AI Insights event

My name is Tyler Pathe, I'm a
reporter here at Fintech Futures

and today among our many guests who
have joined us here up in level 19

We're going to be getting a little
bit more into into the technology

But why don't you just give our, audience
a little bit of snapshot of who you are?

I'm CEO, one of the co
founders of Ipushpull.

I think the leading question
from that is, what is Ipushpull?

What is it's core services
and who are they for?

So we're a data sharing and
workflow automation platform.

Buyside, Brokers, Exchanges,
Trading Venues, Data Companies.

Anyone who has a problem in
capturing unstructured data

Typically customers will work with,
they'll use our platform, which is a no

code platform, to be able to get real
time data in from sources such as a

spreadsheet, or in a chat platform, or
maybe a third party platform via an API.

Get that into our service, you're able
to map and enrich it, and you can share

it in real time to one of your clients,
for example, who may want to consume it

So we sit in the middle and doing
all the heavy lifting in terms of the

integrations, and then providing what
we call this omni channel approach.

So if I'm a customer and I have some
data, I can connect them to us, we can

deliver it into the right application,
at the right time, at the right place.

We'll get along onto the topic of
data in just a sec, but in terms of

like the workflows that are based
on GenAI that you've built for the

capital markets industry can you
give us an example of one of those?

We're a technology company, so it keeps
out on on AI for a long time, but I

think a big Big change in adoption and
perspectives and people wanting to learn

This time last year when ChatGPT
came out and that has been fantastic

for our company because we've
always been building chatbots.

We've been building chatbots for
about five years now and customers are

now looking at how can they utilize
ChatGPT, which they probably played

How can they utilize it in their business?

And if their business is like
financial markets and capital

markets and sales and trade, it's not
always that accessible to go and use

So where we come in is we're able
to then through the previous kind

We've spent a long time building
this data integration platform.

We've built 20 odd integrations
into, I already mentioned, Excel,

Chan, API, but also things like
a blotter on a trader's desk.

We've got web apps, mobile apps, desktop
containers like OpenFin and Thinsumble,

a whole variety of places where people
in the front office live and breathe.

So you've got the data integration
platform, you've got the actual end

user integrations into these different
applications, we've got our own bot

framework, so in our chatbot framework
you can configure a bot once and it

will work across all these different
applications, and now you add a large

language model or AI onto it, and all of
a sudden the entire kind of stack that

we've built becomes 10x more than what it
was, which has been fascinating for us.

So customers We've been talking
to customers about generative

AI, probably since about
January, February of this year.

And obviously, ChatGPT came
out end of November last year.

So we, very much like I said,
just geeked out on AI and already

So we then started to bring some
of the tools that's available for,

Into our platform every single
conversation we had with customers.

So it in springtime, every single one
was touching on gen at Gen ai, which

I, which is no, no doubt you know,
why you've had this conference today.

And we, then started embarking
on a few different projects.

They have their own machine learning
component bolt on called Bedrock.

Within Bedrock, you can then select
different large language models.

So we've done a project using
Anthropic Cloud, which is a large

We've got a customer using it
where they're using it to capture

prices that they're seeing in chat
and receiving from their clients.

Taking that, adding structure onto it,
then using it to generate more data

There's another use case with a major
European exchange, where that's more

based on kind of NLP and natural language,
where we can connect to large data sets,

We've been doing that for many years
already, but now you use AI and large

language models, so you can have a
natural language input, rather than more

FinTech Futures

Expert Insight

At FinTech Futures recent AI Insights event in London, we had the chance to sit down with Matthew Cheung, CEO of ipushpull, to discuss how artificial intelligence is being put to work effectively within the capital markets industry.