Name: Impact of pandemic on data diversity
Uploaded: 2021-12-21T12:52:55.068Z
Duration: 180.3
Description: Diversity is vital when it comes to data. Non-representative data sets are less likely to produce useful insights than ones that cover all aspects of the market. Greg Palmer, Vice President of Strategy at Finovate, addresses how the pandemic has directly impacted data diversity and how this has improved the performance of machine learning (ML) and artificial intelligence (AI) platforms.

Impact of pandemic on data diversity.vtt

English

{{00:00:23}}
Whatever business you work
in, you've almost likely come

{{00:00:26}}
across the story about how
data is transforming our world.

{{00:00:30}}
A company's or management's ability
to make educated decisions and

{{00:00:34}}
analyze fresh insights is largely
dependent on data collecting.

{{00:00:38}}
The most critical goal of data
collecting is to obtain rich

{{00:00:41}}
information, diverse and reliable data.

{{00:00:45}}
Greg Palmer, Finovate's vice-president
of strategy describes how the

{{00:00:49}}
pandemic allowed the collection of
more diverse data, which could help

{{00:00:53}}
AI and machine learning systems
perform better in the future.

{{00:00:57}}
Talking about the importance of data.

{{00:01:00}}
It's no secret that you cannot
build good AI, good machine learning

{{00:01:04}}
solutions on top of bad data.

{{00:01:06}}
Well, where we've been for a while,
we've only had data that exists

{{00:01:10}}
when markets are going really well.

{{00:01:12}}
And this has really limited
the scope of what these AI

{{00:01:15}}
and ML solutions can do.

{{00:01:16}}
They're only as good as the
data that you feed into them.

{{00:01:19}}
Now, what we've gotten over the last
couple of months is a different type

{{00:01:23}}
of data to feed into these models.

{{00:01:25}}
This type of data only comes
in stressful situations.

{{00:01:28}}
If you look at the period between
2009 and 2019, these are boon times.

{{00:01:33}}
Everything is just always on the
up and up, the data that you get.

{{00:01:36}}
And that situation is really valuable.

{{00:01:37}}
You can build a solution on that
data, but ultimately that data

{{00:01:41}}
won't account for a shock to
the system like we saw in 2020.

{{00:01:46}}
What we saw in 2020, give us a
huge amount of new data points.

{{00:01:50}}
We got to see markets respond
to stress in a way that we

{{00:01:53}}
haven't for a really long time.

{{00:01:55}}
We're able to capture more
data now than ever before.

{{00:01:58}}
And so what you'll see is more and
more of this data being incorporated

{{00:02:02}}
into machine learning and AI.

{{00:02:04}}
Those platforms will get
stronger because of it.

{{00:02:07}}
So while there've been obviously a
huge number of pain points in the

{{00:02:10}}
pandemic, the data nerd in me loves
seeing this kind of robust data come

{{00:02:15}}
through because I know ultimately
it makes these systems stronger.

{{00:02:18}}
The more data we have, the more
diverse data we have, the better

{{00:02:22}}
all of these platforms will be.

{{00:02:24}}
And we're so good at
capturing that data.

{{00:02:26}}
The developers have a lot of
really fun stuff to play with.

{{00:02:29}}
It's never been a better time to
be in the AI or ML space because

{{00:02:33}}
you simply have so many cool
pieces of data to work with.

{{00:02:37}}
It's going to be something we're going
to continue to see more data, more

{{00:02:40}}
better as we continue to recover from
the pandemic, we'll get data on that.

{{00:02:44}}
We'll continue to get all of this
financial data and all of these systems

{{00:02:47}}
are going to get more robust and a lot
more usable and quite frankly, a lot

{{00:02:50}}
better at predicting what will happen
with the next shock to the system.

Whatever business you work
in, you've almost likely come

across the story about how
data is transforming our world.

A company's or management's ability
to make educated decisions and

analyze fresh insights is largely
dependent on data collecting.

The most critical goal of data
collecting is to obtain rich

Greg Palmer, Finovate's vice-president
of strategy describes how the

pandemic allowed the collection of
more diverse data, which could help

AI and machine learning systems
perform better in the future.

It's no secret that you cannot
build good AI, good machine learning

Well, where we've been for a while,
we've only had data that exists

And this has really limited
the scope of what these AI

They're only as good as the
data that you feed into them.

Now, what we've gotten over the last
couple of months is a different type

This type of data only comes
in stressful situations.

If you look at the period between
2009 and 2019, these are boon times.

Everything is just always on the
up and up, the data that you get.

You can build a solution on that
data, but ultimately that data

won't account for a shock to
the system like we saw in 2020.

What we saw in 2020, give us a
huge amount of new data points.

We got to see markets respond
to stress in a way that we

We're able to capture more
data now than ever before.

And so what you'll see is more and
more of this data being incorporated

Those platforms will get
stronger because of it.

So while there've been obviously a
huge number of pain points in the

pandemic, the data nerd in me loves
seeing this kind of robust data come

through because I know ultimately
it makes these systems stronger.

The more data we have, the more
diverse data we have, the better

And we're so good at
capturing that data.

The developers have a lot of
really fun stuff to play with.

It's never been a better time to
be in the AI or ML space because

you simply have so many cool
pieces of data to work with.

It's going to be something we're going
to continue to see more data, more

better as we continue to recover from
the pandemic, we'll get data on that.

We'll continue to get all of this
financial data and all of these systems

are going to get more robust and a lot
more usable and quite frankly, a lot

better at predicting what will happen
with the next shock to the system.

Trend

Diversity is vital when it comes to data. Non-representative data sets are less likely to produce useful insights than ones that cover all aspects of the market. 
Greg Palmer, Vice President of Strategy at Finovate, addresses how the pandemic has directly impacted data diversity and how this has improved the performance of machine learning (ML) and artificial intelligence (AI) platforms.

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Greg Palmer

Vice President

The epidemic has had major ramifications for the global financial industry and is influencing finance research.
In the face of uncertainty, the data analytics industry has another problem: how to use past models to forecast future behaviour.
Because reliable data regarding the future is difficult to obtain, the researchers must rely on data from the past. However, as Palmer underlines, if the past is no longer a good predictor of the future, the researchers will have difficulty undertaking any predictive analytics.