Why Generative AI Is Becoming Essential to Financial Services

A recent survey from Clearwater Analytics reveals Gen AI in finance is shifting from an algorithm challenge to a data governance challenge.

Now the study identified a 23% point gap in how fund managers review their data.

And meanwhile, 79% of firms believe that their data is complete.

And only 56% considered accurate.

So joining me to discuss this very interesting topic and more is Sam Deepson Hai, CEO of Clearwater Analytics.

Thanks for joining us.

Thank you so much for being here.

Thank you.

Thank you, Johnny, for having me.

Very interesting conversation that we're having because I think this is top of mind for everyone.

So take us through the key points of your survey and what do the numbers say to you about whether this Gen AI is here to stay.

So Gen AI firstly is here to stay.

Why is that?

95% of our clients are using Generative AI today.

The other interesting fact is 16% of all humans, including anyone who's alive on the Earth today, is training these models.

It's not 16% of people who have computers, it is 16% of all humans.

That's why it will make a difference.

People are spending double what they spent on this technology last year, and so yes, it is here to stay.

It's hard to believe that it won't play a big role in our future.

All right, so I want to hone in a little bit more on the investment management industry.

How is this technology going to shake up that part of the industry?

Yeah, so firstly, we should really agree that everything will change.

I think I'm old enough, you may not be, but I'm old enough to remember that when the internet came along, people said only the books will change and how you buy your flight will change, and look where we are, changed everything.

So we've got to start from there.

So what generative AI does, Johnny, is it allows you to take huge amounts of data.

And consume it.

So let's take two examples.

Suppose you're a cotton futures trader.

You want to know how much cotton is being produced in the next year.

You would make some phone calls.

You try and figure out what's going on, but generally what you can do is take 1000 agents and they would swarm out into the world, into every zip code that produces cotton, and it would take the soil temperature, it would take the temperature of the region, the rainfall, and persistently watch for how much cotton is being produced.

That makes you a massively better trader.

That was simply not possible earlier.

Think about you personally.

You have a savings account.

What's the return on that?

You you've checked when you did deposit it, and now you don't know.

But the point is you can now have 100 agents persistently watch every bank and come back to you and tell you what the best savings account is, so the ability to consume large amounts of data.

And then act on it as foundationally changes how investments are done.

So let me ask you this.

So with, with all this change, because we see that AI is just rapidly changing, it's evolving everything, how will businesses succeed in your point of view?

Yeah, so it's a little controversial because so much is being said about the foundation models.

I think the foundation models just simply normalize.

Remember one year back it was all open AI.

Right now it's all anthropic.

It's going to be something else tomorrow, Grok, and then you'll have Kimmy and you'll have Deepeek.

So the point is I think foundation models normalize.

The second thing is really compute and Vidia is great.

Guess what?

We're spending tens of billions of dollars to invest in producing chips.

You have an iPhone.

Do you know what the chip on that is?

You have no idea.

Now 20 years back it was all about 286 and 386.

The point is if foundation models normalize and chips normalize, what is left?

Truly believable, accurate data.

That example I gave you about savings bank return, you need to believe your data, and that's why when you led off and you said 79% of the people believe they have the data, but only 56% believe it's accurate.

And if you don't believe your data, will you act on it?

And the answer is no, and that's what makes a difference here.

So I want to talk about the specific challenges that you are tracking across the business landscape because we see that there are different challenges.

So what are some that in your point of view, uh, warrant some concerns at this point?

Yeah, you know, when it comes to the stock exchange here, it's easy to see you you want the price of a security.

You look at it and you have the price.

What about an opaque instrument?

So what about private credit which you've invested in?

What about CLOs?

What about mortgage backed securities?

And the point of that is that when you think about getting access to that data and you don't have the data, you're taking unnecessary risk.

So insurance companies, for example, they used to have only 5% in private credit.

Now they have 9%.

You've got private wealth managers who had 0 and now they have 5, so getting access to believable comprehensive data of opportunities around the world is what it's about.

You should know what opportunities exist in India, what opportunities exist in Tokyo.

What opportunities exist in Europe, and then you'll make a better decision.

So access to truly believable and accurate data is really what makes a difference.

And if you don't have that, I think you're taking risks you don't even understand.

And that's what somebody like Clearwater helps companies do.

All right, so I want to talk a little bit more about AI because obviously it's top of mind for everyone.

It's changing, it's evolving.

So what's your outlook for the rest of the year when it comes to generative AI adoption and what do you expect to see next year too, because again this is changing, this is moving and grooving.

Like it's very much one of those things that it, it's evolving very quickly.

So let's get your output.

So I'll give you a view about 2020, um, and then sorry, 202,000 when the internet came along.

There used to be all of these companies, they got destroyed.

Johnny, you think about Ceil.

It was the leader in CRM.

It got destroyed by Salesforce.

You think about PeopleSoft, they got destroyed by Workday.

The point is you will see in the next year and a half completely new companies come along or companies completely reinventing themselves.

I do want to say one thing really quick though is generative AI.

Was born a few years back and that's it.

I think in the next 6 months you'll see massive change.

In the next 12 months and 18 months you'll have brand new companies owning much of the software landscape.

So I think the $43 billion software industry will be completely remade by generative AI.

A Sanda, thank you so much for joining us.

It's a pleasure to have you on and talk about this because again this is changing at a rapid pace.

So it's thank you so much.

It's gonna be interesting to see what happens.

Appreciate your time.

Thank you.