July 6, 2026 • 36 mins
AI can read every earnings report, filing and research note in seconds — but can it ever replace the instincts of a seasoned investor? Merryn Somerset Webb sits down with Causeway Capital Management chief executive Sarah Ketterer to explore where AI is genuinely changing fund management and why human judgment still matters. Ketterer also shares where she is finding value in today's markets, highlighting opportunities in healthcare, enterprise software, UK equities and overlooked Chinese companies while warning investors about the risks of chasing the AI semiconductor boom.
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Speaker 1 (00:02):
Bloomberg Audio Studios, Podcasts, Radio News.
Speaker 2 (00:18):
Welcome to Marin Talks Money. In the podcast in which
people who know the markets explain the markets. I am
Maren Somerset Web and this week I am speaking with
Sarah Catterer. Sarah is the CEO of Causeway Capital Management
affirm and she co founded in two thousand and one.
Today we speak about how AI is going to impact
and is impacting the fund management industry. We talk about
(00:38):
bargains in the UK and whether anyone is ever going
to pick them up, what's going on in biotech and pharma,
and why you may need more medical devices than you think. Sarah,
Welcome to Marin Talks Money.
Speaker 3 (00:50):
Thank you for inviting me right now. Why don't we start?
Speaker 2 (00:53):
Can I just ask you to tell me what it
is the Causeway actually does. You've been on the podcast before.
We've got piles and you listen, it'll rundown of what
is your business actually do.
Speaker 3 (01:03):
Cosway is a fund manager. We manage approximately eighty billion
dollars of client assets and our clients are largely institutional
and our business is global equity. So we have both
fundamental research and quantitative research, and we have strategies that
deploy primarily fundamental with quantitative risk control and then primarily
(01:26):
quantitative with fundamental risk control. So that's what distinguishes us.
It's the it's the convergence of both fundamental quant.
Speaker 2 (01:35):
Yeah, the combination of the two, which is not something
you find that often. Okay, So following directly on from that,
I wanted to ask you about AI because I know
you've been thinking about a lot. I know you've been
talking about it, but the key question is how are
you using it in your own business. You know, hearing
a lot about the businesses that are being disrupted by
AI and how they're being disrupted, and I'm beginning to
hear a lot from people saying, well, what do we
(01:57):
need fund managers for because AI can do this?
Speaker 3 (01:59):
Yes, if only I know. Well, I believe that the
initial applications of AI for us at Causeway has been
that we've had a similar experience to other enterprises and
that we've got tremendous efficiency gains from coding so that
our software engineers could do so much more in the
(02:21):
same amount of time. And I've noticed this based on
our head of investment, technology has been able to do
much more for our quant effort and the people who
work for him that the quant software infrastructure has become
much more developed more quickly. That means that our quant
researchers can test more ideas more and do so not
(02:46):
just more quickly with more accuracy. The head of our
digital services just our whole it effort. He's been able
to help us produce tax optimizer. He did in about
two weeks and normally would have taken months. This was all,
I guess in part. Vibe coded using AI models to
(03:08):
accelerate the software development. But the output has been really good,
and the interaction with our team to make sure that
it does what it's supposed to do for our mutual
funds has been great. But I'm going to just step
back and say that from a coding perspective fantastic. From
an investment perspective, the answer is mixed, and it's that
(03:33):
AI has been made us, each of us as research
analysts able to read everything. We have an assistant now
our AI agents who read everything, every company transcript, earning transcript,
every government agency filing, every every trade journal, every bit
(03:55):
of news.
Speaker 2 (03:56):
Every actually the annual report. Someone's reading the report.
Speaker 3 (03:59):
Finally, it reads them all it can do all of that,
but what it can't do is make decisions with the information.
I don't know how AI will replicate the fundamental portfolio
manager who relies on his or her experience, has a
level of intuition that's probably thirty to forty percent of
the investment decision comes from something that you can't even quantify.
(04:23):
It's this instinct honed after decades of doing this, and
from a quanm perspective, with AI, the ability to find
signals that aren't actually explainable to clients as quite a temptation.
We'd be really careful not to go and use the tool,
(04:45):
i'd say ineffectively. So in short, AI is an accelerant
to productivity improvement, but it hasn't yet developed where it
can replace that human judgment. And I think that's true
across many of the companies that we research. They have
some of the similar experiences. So it doesn't confine to finding.
Speaker 2 (05:07):
When we're talking about it reading everything, every research report,
every every company announcement, every everything, and that'll be done
and summarized and presumably produced for enos. That's I mean,
if you're looking at thousands of companies, which I know
you are, that's a massive time saving. But back to
the intuition bit. It is the reading of those reports,
the reading of the company announcements, followed by the reading
(05:30):
of the transcripts of earning calls, et cetera, et cetera,
where a good analysts might pick up the bits and
bobs and make the connections that create the intuition. So
without the without the hard graft bit, yes, can you
have the bay.
Speaker 3 (05:42):
I can make some connections. You can find in the
footnotes where there might be counting anomalies. What it can't
do is what we're doing. It can't have a meeting
with management and observe the body language. You can't say,
you know, this doesn't feel right. I don't even know
how to put it into words. But I think they're
becoming the measure a little more caution, and I'm going
to take that back and assimilate that information. We don't
(06:05):
record meetings we I think management would find that a
little off putting and probably we wouldn't get any meetings.
But we're taking notes. But what we're it's what we're
hearing and the way we're observing how the message is
being delivered. That's so incredibly important. And this is not.
(06:27):
Someday when robots are doing the job and it's all visual,
I think the other side of the table will be
a robot too. It's going to be a pretty grim world.
Speaker 2 (06:38):
How And I don't normally get into young people early on.
We normally save that for the end. But the way
you're talking about the fund management business now the fundamental
part of it. Yes, what is the young person who
wants to be in fund management these days do because
all that grunt work that was the training ground.
Speaker 3 (06:52):
Yeah, yes, the grunt work initially is probably a good idea.
We encourage analysts to do everything from scratch to understand
what the meaning is of all these documents, where where
to go? When you in a prompt, one has to
ask the AI to search certain areas, or we have
(07:14):
agent builders that link into systems. It links into databases
and you have to know which database is to plumb.
But once an analysis has done this a few times,
they don't necessarily want to do the gruntwork because it
displaces in a zero sum day any something more higher
(07:35):
level thinking oriented. So I'm okay with the AI doing
the grunt work. It's just that if people stop thinking,
that's when we're in trouble. It's it's using that time
freedom where you're not entering the entering in the quarter's
earnings into your spreadsheet, but the AI is doing it
your clawed ad in or whatever the tool is. What
(07:57):
how else is the analyst using that freedom time? Is
he or she thinking about more about the assumptions, really
testing the model, going back to the notes and thinking
again about where they might have been wrong, taking a
step back and thinking more about structural change and how
this company what come out of left field being one's
(08:18):
own devil's advocate, and the AI can help with that too, interestingly,
But that's the higher level thinking that we want and
we are promoting.
Speaker 2 (08:27):
Okay, I'm convinced we still need you. Thanks. When you
look at how working in your own company, and then
you look at the businesses in which you invest, what
are you looking for in the companies you're investing in?
Speaker 3 (08:41):
Well, I'm glad you asked, because we for every sector globally,
have done a deep dive into how we believe they
will be impacted by AI. This is quite an endeavor.
We did this fundamentally in our quant colleagues observed the
process and the output. But what we found is for
many there are some structural changes that are going to
be quite significant, and then others there's a lot of upside.
(09:03):
Let's go to healthcare to start. We have a number
of pharmaceutical companies in the portfolio and now we're adding
more medical technology because they've been left out in the
cold in this huge AI driven rally. But their ability
to innovate, their ability to in the case of pharmaceuticals,
discovered new molecules advance them through the clinical trial process
(09:25):
more quickly, efficiency, lower cost is that could be given
that patent lifes remain the same. That means more years
out in the marketplace and less in development. That's a
profit booster. It's more hard pressed to see how there'll
be some sort of mysterious AI entity that will develop drugs.
(09:49):
Pharmaceutical business is very laborious and involves a lot of
interaction with the health authorities and clinical trials are carefully
scripted and then being able to target patients with AI
in advance of a doing trials so they are they
are the right individuals for that particular drug. That's another
(10:10):
way to accelerate the process and get output that can
be get that drug into the market more quickly. So
for healthcare, we think this is going to be fantastic.
Healthcare companies they gather lots and lots of data and
their ability to use it in ways they never could
before with AI is not that dissimilar from other industries.
(10:31):
It's just they have so much intellectual property and their
ability to innovate now is improved. And innovation equals pricing power,
and pricing power is margin, and margin is profitability, and
profitability leads to cash flow, and cash flow gets returned
to shareholders.
Speaker 2 (10:48):
Okay, that makes sense. How does that then interact? I
mean one of the one of things about healthcare sector
is how regulated. It hugely regulated across the board, regulated
in different ways in every country, but the layers of
regulation massive.
Speaker 4 (11:01):
Is that a barrier, It's part of the moat, and
regulation and compliance and on the need for audible outcomes
are one of the reasons why some industries they will
they just won't have this sort of AI competition.
Speaker 3 (11:17):
The market might be inferring they're going to incur. So
a mote is a plus and a minus. A mote
can protect the business from competition, but it can also
mean that there will be it conhibit growth. You need competition, yes,
yes you do. But the working their way for the
(11:39):
regulatory maze is what healthcare companies do very well, and
the large ones have whole teams for this, and the
teams may be able to harness AI to be more
efficient doing that, which could be also a cost savings
as well as time saving.
Speaker 2 (11:53):
Interesting, and we've all talked on this podcast about how
big companies love regulation because nothing, nothing holds competition back
more and a good bit of regulation. And one of
the thought was about AI was that it might be
one way for new entrance to circumvent We'll find easier
ways to deal with large parts of regulation. But it
sounds like your case is that that is not.
Speaker 3 (12:16):
Going to happen. It depends in something that gets put
into the human body. The regulations there for a reason. Yeah. Yeah,
it's a little different. Say financial services, okay, that necessarily
got to create a health outcome.
Speaker 2 (12:30):
Okay, So what other sectors will have a regulatory remote
that will limit the use of AI elsewhere?
Speaker 3 (12:37):
Well, iound I've been talking about software as a service.
This sounds a little silly, but it's tangential. The SaaS
companies have all sold off this idea that you're a
software business, you had a seventy plus percent gross margin
or higher. Now your business is losing its mode and
the software will be vibe coded. Anybody can now code,
(13:01):
but code isn't the mote. And these software companies that
provide like SAP or Oracle very comprehensive for Fortune for
five hundred global companies, and SAP in particular this mission
critical software where they're dealing with systems of ledger in
businesses that are heavily regulated. That means that data is crucial.
(13:24):
There can't be errors in the outcome. So software needs
to be deterministic. Yet generative AI is non deterministic. We
can be a useful tool for users in the enterprise
to get access to their data and see it in
different ways. But it can't run the business. It can't
run HR, can't run account it can't run supply.
Speaker 2 (13:46):
Chain, can't run relations.
Speaker 3 (13:49):
Yes, so I think about that as the market has
just decided these companies are all to be incurring great competition,
and we would disagree. It's the it's regulation and the
need for the businesses out everything they do to be
fully audible and transparent, auditable that that make it will
(14:13):
make it quite hard for new AI native AI startups
to undermine them.
Speaker 2 (14:18):
Okay, so you quite heavily invested in the likes of SAPA.
Speaker 3 (14:22):
We are. We are fundamentally the good management, incredibly sticky
business and all that migration to cloud that's coming up,
that's one of the absolute So what we know, there's
a lot we don't know. What we do know is
that for enterprises to take advantage of AI, they need
to move their data to the cloud, they need to
(14:44):
have it accessible for the AI, and they need to
be able to access that tremendous compute on an as
needed basis.
Speaker 2 (14:51):
And are you on the other side of this, are
you and any of the hyperscalars that they don't fit
into your your fundamental matrix.
Speaker 3 (14:58):
Some of them do, some of them do. For example,
the two great digital advertising leviathans, Meta and Alphabet generate
enough free cash flow to where they can fund their
foundational model ambitions and so they can fund their own
cap X, which is very different from some of these
(15:20):
massive new AI companies where it's all about finding more
investors who believe in the dream.
Speaker 2 (15:28):
They're going to be voyant with the opena ipo.
Speaker 3 (15:32):
I cannot say.
Speaker 2 (15:34):
I'm kind of guessing where else are you finding value
in the market?
Speaker 3 (15:39):
Well, I did mention in passing medical technology. I just
think it's fascinating that you could find companies like Boston
Scientific and heart valves and very complex, important cardiovascular devices
that you cannot get anywhere else. They used to trade
twenty five or thirty times earnings and now they're multiples.
(15:59):
Are half that. Uh, Companies like Striker or zimmer BioMed.
They're fantastic medical devices as long as human bodies break
down are going to be needed. And the very research
intensive business. And to the degree they keep innovating and
(16:22):
they're not in commodity products, they should do quite well.
Part of what's weight on them has been concerns about
the g LP one trends and consumer and individuals will
no longer need new body parts, and we think that's unlikely.
In fact, the longer they live, the more part replacements
(16:44):
they'll need.
Speaker 2 (16:45):
Okay, so people will get thin, they'll still need the
replacement polsitives. I quite need them until later.
Speaker 3 (16:50):
Yes, and they won't.
Speaker 2 (16:51):
They won't.
Speaker 3 (16:52):
They won't all get thin, sadly, wun't they? No, Some
people will neither want an injection or where they wanted
they will take a pill, they won't, they won't do it,
and compliance will well, as always with drugs, they're not necessary.
People aren't necessarily willing to comply.
Speaker 2 (17:10):
Sure, it has been fascinating seeing the obesity rate in
the US drop. It has for the first time.
Speaker 3 (17:15):
Yes, it has change, and that should lead to better
healthcare outcomes and lower cost healthcare.
Speaker 2 (17:25):
Two new hips each whenevery one's ninety, yes one at sixty,
I'll take two, please, and a couple of knees. Or
(17:56):
when I look at your at your your main vehicles
ugly global, global, international, two different words for it. But
you also have some emergen markets exposure. The Global fundkind
of twenty percent in emerging markets, and there's also one
Emerging Markets fund, right what's interesting there, And we've talked
about this quite a lot recently about how the difficulty
of emerging markets being now so defined by career in
(18:18):
Taiwan and that market concentration making a nonsense of the
idea that you can get diversified exposure within index has
been one of the things we've been I'm afraid going
on about for rather too long. But then the question
is if you're not going to have index index style
exposure to those two countries. Of course, to China, what
are you going to have?
Speaker 3 (18:36):
Well, I would argue vociferously against indexing emerging markets, and
I don't just give recent examples. Maybe twenty twenty two
isn't that recent, but Russia, like, why would you even
wanted an index weight in that market? We were underweight
and very underweight, and that was extremely helpful. Sometimes emerging
markets go to zero, and that one did. That's why
(19:01):
they're emerging. They have much higher levels of risk because
they're growth markets, and they interestingly, they're not all demographically
in that growth phase. China, we didn't. It's been the
largest of the emerging markets, and now it's number three
behind South Korea and Taiwan, which is also fascinating, but
(19:21):
it's within China, and that.
Speaker 2 (19:22):
All three of them have shrinking populations.
Speaker 3 (19:25):
They do, but at least South Korea and Taiwan have
semiconductor giants in memory, and Taiwan has TSMC in chip production,
and there are no substitutes at present, there won't be
for a couple of years. No matter how many fabs
are built or semiconductor facilities, it's going to take some
(19:49):
time for supply to catch up with the demand. If
demand may sag, and there may be technological reasons why
we don't, you know, memories and quite hot as hotly
demand as it is now. But that's very clear, and
I can see those markets of those are highly highly concentrated,
and the stocks they're those big three stocks are very
(20:12):
large in the benchmark. It's beginning to look a little
bit more like the US, oddly than anywhere else. What's
interesting in emerging markets. I think in China there are
all kinds of companies that have been left behind. We
were talking about US hyperscalers. You could have the Chinese version,
effectively the operating system of China through we chatter wishin
(20:34):
which is Tencent. They're the largest publisher of music.
Speaker 2 (20:39):
Video or.
Speaker 3 (20:41):
Video games globally, and they have a music business, they
have a messaging business, they have the most amazing flywheels.
So they're massively cash generative like US hyper scalers, and
they're developing through HY three their own foundational models. They
got they were a little behind in a but it's
when you have that kind of that that sort of
(21:03):
financial resource, their net cash, it's not too hard to
catch up, and they will. They'll find a way to
get AI infused throughout their consumer products, that all the
social media they do, and they'll keep their customers and
that what is it one point three billion monthly average users?
(21:25):
Like they're just this doc just keeps falling and we
just look at it and we wonder, why, what an
amazing company. It shouldn't trade at mid teens multiples of earnings.
It should be much And part of this is just China.
No one's interested right now. It's so there's this love
hate relationship with China. Only if three or four years
(21:46):
ago it was uninvestible, that's probably the time we all
should have bought a lot of it. But now all
eyes are in one area and not there. And especially
for these Chinese companies that aren't necessarily at the considered
at the absolute forefront of AI, they've been discarded. And
(22:08):
this is where taking a two year view is really
useful as opposed to just thinking out the next three
to six months, because it gives us a chance to
accumulate what maybe one of I think the I think
my colleagues would agree with me, probably one of the
best companies in China overall for a very attractive valuation.
Speaker 2 (22:27):
Yeah, and the lack of interest in it is just fashioned,
just people coming slowly back to being in the Chinese market. Again,
the fact that it's impossible to draw your eyes away
from the stars and the etector in the US. And
as they said, these few as you market.
Speaker 3 (22:41):
Yes, I think so. I think so that there's a
certain amount of short term ism baked into that. It
may or I mean, we could be we cause we
could be wrong and ten Cent doesn't develop out their
AI features fast enough and and part of their business
gets competed away. But it's very unlikely that's going to happen,
(23:02):
given their track record, given what they've already built, and
given the marketplaces where they dominate. They you know, they've
got infrastructure as a service, their platforms a service, and
software as a service, and they will they have this
cloud business and that gives them a lot of compute
and a lot of flexibility. And again that balance sheet,
(23:23):
it's like they have all the raw materials and they
have the history of doing it, and that usually convinces
us as fundamental investors. And given how low the valuation is,
this isn't the risk is very modest. Versus I mean
you mentioned semiconductors we started. Given where they trade, they're
(23:44):
very risky right now.
Speaker 2 (23:46):
Well, because they're cychnical businesses. Right, this is exactly the
wrong point of the cycle historically, if you were looking
at this is a normal cycle, exactly the.
Speaker 3 (23:54):
Wrong cycle exactly. You don't believe in a cycle if
you think that they the demand goes on prepared actually
like this, and the supply will be will not meet
demand indefinitely. But that's I think physically impossible.
Speaker 2 (24:08):
Yeah, normally at this point you would stop to see
a shot rise and supply and the fool of and
demand at the same time.
Speaker 3 (24:13):
Or all the market needs to perceive is that their
supply is planned. That's all. That's all it'll take to
tip them back the other direction.
Speaker 2 (24:23):
Well, the always us to say, I remember someone telling
me when I was a very very junior broker that
the chip makers you seld them when they were very cheap,
and you bought them when they were very expensive, because
that's how the cycle looks.
Speaker 3 (24:35):
Yes, yes, exactly. The multiples tend to be low. This
is where people often get confused. They think very low
multiple stocks are value stocks, so they're cheap, but it
could be. You have to look carefully. If they're in
cyclical industries, their earnings are at a peak, and conversely,
when their earnings are at a trough, their multiples.
Speaker 2 (24:55):
Are look very expensive. But that's exactly the time is
their earning start to go up gun.
Speaker 3 (25:00):
And it's really helpful from an investor perspective to be
in a cyclical business because at least you have history
as a guide. If you're in a business that has
no history or everything has changed, you can't use the
past as a predictor of the future. And in my view,
it makes cyclical investing, assuming there isn't some massive change
(25:23):
in the business, lower risks than appears at first glance.
Speaker 2 (25:28):
Let's go back to the US. We've talked briefly about
the intense concentration in the US indices, and we've talked
a little bit about biotech and pharma, other other sectors
in the US that you are finding very interesting at
the moment that outside these hugely expensive tech companies and
outside what we've READI discussed that.
Speaker 3 (25:46):
Well, because tech is so massive. Technology communications services and
another stock that's come out of our research is in
the IT services area, and this is a major contract
of the US government Booze Allen and again in the
category if we didn't used to be able to buy
these stocks because the growth rates were high and the
(26:08):
multiples were even higher. The concern about reduced use government spending,
especially in civil but seventy three to seventy five percent
of booz Allen's revenues come from military defense. So the
US government needs to modernize its systems and it needs better,
(26:30):
much better cybersecurity. This was all common sense, Like nobody's
ever said to me, Oh, that's not true.
Speaker 2 (26:37):
Yes, in any cybersecurity they'll be fine.
Speaker 3 (26:39):
Exactly. So, this is an eighty five year old company
and ninety percent of the revenues come from US agencies.
They've they've had somewhat of a partially rocky relationship, and
yet nobody else can do what they do. They they're
partly they collaborate as well as compete with Palenteer can
(27:00):
take all the business. There's you know, there's military cryptography needed,
there's I mean, there's just so many different areas where
Booze has has that dominant expertise, and it's a it's
just eight billion dollar market cap now and it trades
at high single digit earnings. You can then market has
(27:21):
said it's going out of business or it slowly surely
will melts like an ice cube in the sun, and
we disagree. And valuations, yeah, well, evaluation they're very attractive,
probably should be at least fifteen times next year's earnings.
And then you get a three point six percent dividend yield,
which is something a lot of these tech stocks don't
give you much in dividend. They may do share of
(27:44):
purchases like SAP does big buybacks. I think they've been
out something like ten billion euros over the next couple
of years.
Speaker 2 (27:52):
It's extraordinary, isn't it. We've talked about this quite a
few times recently as well, the way that ever the
last decados the stock market has become at an extra
machine for investors, where you take out your dividends, you
take out your special dividends, you get your money back
and buy backs, et cetera. Whereas originally the whole idea
was that individuals gave money to companies, then the other
way around. Well, there's still plenty of that happening too, well,
(28:13):
there is now, But if you have to think about.
Speaker 3 (28:16):
How in the in the idea of gaining a return
if you were expecting let's just say ten percent annually
from your global equities, which I think is a very
punchy number, but let's just throw that out there so
we can all smile and love the fact that our
money is doubling every seven years. What if you can
(28:37):
get a third or forty percent of that in dividends,
that's phenomenal. Then you don't have to rely so much
on capital gains. Is this sort of dividend one oh one?
But the dividends are a signal management saying we're so
confident in our business. We're sending money back to you
shareholders and that's great. We want them to be confident
(28:59):
if they once dividends are paused or eliminated, that's a
time to be a little nervous.
Speaker 2 (29:06):
It's not like an add for the UK market.
Speaker 3 (29:09):
Well, the UK given that we passed these great dividends,
hits the bargains in the UK market, there's no doubt
about it. And it's just a question of when the
global spotlight turns to it. Somebody say this week they
thought that your private equity was galloping over here to
take a good look.
Speaker 2 (29:26):
Oh, yes they are. And then we find ourselves in
this ridiculous situation where you can investors won't buy UK companies,
private equity arrives here, buy them up, and then we
buy the private equity companies or the private equity funds
and just have the same stuff in them and pay
five times the fee. Yes, yes, not ideal.
Speaker 3 (29:44):
Not ideal. There's so many things in the world that
aren't ideal.
Speaker 2 (29:47):
What might make global spotlight move here in a good way,
because it quite often moves here in a bad way
these days. Still make stable government, stable government, good luck.
Speaker 3 (29:57):
Hand yields remaining stable, if not dropping slightly, which would
mean getting inflation under control and having a fiscal stability. Yes,
well I didn't. I don'ty it was gonna be easy.
I just said that would.
Speaker 2 (30:12):
Be I was just for those of you who are listening,
not watching. I'm just looking there going well. I mean,
I don't even know what to say to that, because
these things sound quite unlikely for world you get about it.
Speaker 3 (30:22):
Globally competitive companies. I think about astrozenic and pharmaceuticals. What
a what a what an incredible innovator they're based here,
but they don't. I mean, I don't know what percentage
of revenue I guess is less than ten in this country.
But to have a company like that listed here is
tremendous or in life insurance and Prudential Plc. They're an
(30:45):
Asian life insurance giant.
Speaker 2 (30:49):
Well, I mean, we always say that a very small
percentage of forty one hundred revenues actually come from the UK,
well under forty percent.
Speaker 3 (30:55):
Yes, yeah, but that's okay. The fact they've chosen to
domin style here and use UK jurisdiction is an endorsement
of the UK legal system and they like the weather.
Speaker 2 (31:12):
When you look at your portfolios, Sarah, all the many
portfolios across the board, look at them, and is there
anything that you worry about?
Speaker 1 (31:19):
What?
Speaker 2 (31:19):
You look at them and you think, oh god, if
this thing happens around a whole part of dropt And
one things that one of our most recent guests was
talking about was if AI works as suggested, and perhaps
is in the way that you've suggested taking away a
lot of the grunt work, and we see a lot
of highly paid jobs disappear. And this guest was saying, well,
maybe fifteen percent of of high income jobs will disappear.
(31:40):
I might call high income jobs. Then that has an
immediate knock on effect into the flows into four to
one case, which again has not gone effect into the
flows into passive funds, and then we might see a
massive market collapse of GFC style collapse. That was his worry.
Speaker 3 (31:57):
I don't share that. I'm more in the mark and
in camp that the day. I think there are some
industries or even sectors that we're going to struggle a
little bit, are gonna have to find new ways of
proving their value to consumers. But as for employment, I
would have more software engineers because they're doing so much
(32:17):
like there is revolutionary. And as for analysts, our analysts
will be even more productive. We'll be able to cover
more stocks. There's seven thousand stocks and we only can
cover about ten to twelve per person pretty well, and
in quant we can cover quite a lot, but it's
a breadth strategy, so we don't have any depth there,
(32:38):
and we'd like to have more depth. I mean, why not.
It would make our models even more informed. So I
would happily take on more analysts if the AI tools
make them even more productive, because then they sort of
pay for themselves. So I think it really depends on
the industry you're talking about. First, I thought it would
put lawyers out of business, and of course I should
(32:59):
never have thought that.
Speaker 2 (33:00):
Nothing everything is that, of course not but whatever it is,
But there is why they didn't train enough people at
the boatman And then there aren't enough experienced people in
the middle to check the mistakes of the LLLM.
Speaker 3 (33:11):
Yes, well, so that's Look the LM's that right now.
The AI coding agents do the coding and then check
the coating, and but somebody has to be there across
the table from the client. Somebody has to supervise it all.
And then the amount of legal work is just urgin.
Speaker 5 (33:31):
Look at radiologists, we thought maybe they would go out
a bit with all the scans in the AI, and
when you get a scan, it's compared to thousands, maybe
hundreds of thousands of different and you have the benefit
of all these different radiologists' opinions.
Speaker 3 (33:46):
But you still want the radiologists in fact now too.
Speaker 2 (33:50):
You want one to do well.
Speaker 3 (33:51):
Not just that, but if it brings down the cost
of the radiology process, then more people who heretofore wouldn't
have been scanned because it was too expensive, can afford it,
Like the marketplace, the tam the total dress ball market
gets bigger, so you need more radiologists.
Speaker 2 (34:07):
It's like a hypochondria extreme.
Speaker 3 (34:11):
Well, yes, one can find things if one goes to look.
It's so true. But every once in a while it's
saved somebody's life, so why not.
Speaker 2 (34:19):
Yeah? Absolutely, all right. Last question, last question. You said
that people come to London for the weather, when at
the moment we are talking, it is very, very hot
in London. Well, hope for us anyway, hold for us
over thirty degrees, So a lot of people heading to beach.
When you go, what are you going to take to read?
Be reading at the moment.
Speaker 3 (34:41):
I really like sci fi, so I will read as
much science fiction as I can get my hands on.
I don't know what it is. I've never really been
that interested in history. I've forced myself to. Thank God,
my husband is a great historian, so he helps full
(35:03):
need offense for me. Yeah, but when I have one
of those husbands, taos great. Thinking about the future is
fascinating going back and reading some of the great sci
fi of the past and anything that's been written in
the last ten years. But when when an author who
has a great mind divines the future, and it turns
out that's sort of where we're heading today. And they
(35:24):
wrote it forty or fifty years ago or more. I
just find that thrilling. Yeah, I ask you.
Speaker 2 (35:30):
And I think I might even have mentioned this on
another book case. My son was reading something called The
Invasion of the Aliens Wells and that fascinating because a
lot of it is like, how did you think of
that back when in horsing garriage days? How do you
think of this? Yes? Exactly the extraordinary? Do you prefer
utopia or a dysktype? Yeah, and your satisfaction where you're
not quite.
Speaker 3 (35:50):
Sure where the word ends, where it could go either way,
because dystopian is depressing.
Speaker 2 (35:56):
Yeah, yeah, a lot of that about a lot of
depressing about an invest Sorry, you have to ultimately be
an optimist otherwise you're not going to hold anything. Oh well,
we'll leave it there, Darah, thank you so much for
joining us today.
Speaker 6 (36:06):
Thank you, Mary, thanks for listening to this week's Marryn
Talks Money.
Speaker 2 (36:17):
If you like our show, rate review and subscribe wherever
you listen to your podcasts, and keep sending questions or
comments to Marryn Money at Bloomberg dot net You can
also follow me and John on Twitter or x I'm
at Marinus w and John is John Underscore Stepic. This
episode was hosted by Me Marrin's UNSEP Web was produced
by Someersadi Moses Andam and Jennifer Seely. Sound designed by
(36:39):
Blake Maples and Aaron Kaspers and special thanks of course
to Sarah and Kett
Bloomberg Audio Studios, Podcasts, Radio News.
Speaker 2 (00:18):
Welcome to Marin Talks Money. In the podcast in which
people who know the markets explain the markets. I am
Maren Somerset Web and this week I am speaking with
Sarah Catterer. Sarah is the CEO of Causeway Capital Management
affirm and she co founded in two thousand and one.
Today we speak about how AI is going to impact
and is impacting the fund management industry. We talk about
(00:38):
bargains in the UK and whether anyone is ever going
to pick them up, what's going on in biotech and pharma,
and why you may need more medical devices than you think. Sarah,
Welcome to Marin Talks Money.
Speaker 3 (00:50):
Thank you for inviting me right now. Why don't we start?
Speaker 2 (00:53):
Can I just ask you to tell me what it
is the Causeway actually does. You've been on the podcast before.
We've got piles and you listen, it'll rundown of what
is your business actually do.
Speaker 3 (01:03):
Cosway is a fund manager. We manage approximately eighty billion
dollars of client assets and our clients are largely institutional
and our business is global equity. So we have both
fundamental research and quantitative research, and we have strategies that
deploy primarily fundamental with quantitative risk control and then primarily
(01:26):
quantitative with fundamental risk control. So that's what distinguishes us.
It's the it's the convergence of both fundamental quant.
Speaker 2 (01:35):
Yeah, the combination of the two, which is not something
you find that often. Okay, So following directly on from that,
I wanted to ask you about AI because I know
you've been thinking about a lot. I know you've been
talking about it, but the key question is how are
you using it in your own business. You know, hearing
a lot about the businesses that are being disrupted by
AI and how they're being disrupted, and I'm beginning to
hear a lot from people saying, well, what do we
(01:57):
need fund managers for because AI can do this?
Speaker 3 (01:59):
Yes, if only I know. Well, I believe that the
initial applications of AI for us at Causeway has been
that we've had a similar experience to other enterprises and
that we've got tremendous efficiency gains from coding so that
our software engineers could do so much more in the
(02:21):
same amount of time. And I've noticed this based on
our head of investment, technology has been able to do
much more for our quant effort and the people who
work for him that the quant software infrastructure has become
much more developed more quickly. That means that our quant
researchers can test more ideas more and do so not
(02:46):
just more quickly with more accuracy. The head of our
digital services just our whole it effort. He's been able
to help us produce tax optimizer. He did in about
two weeks and normally would have taken months. This was all,
I guess in part. Vibe coded using AI models to
(03:08):
accelerate the software development. But the output has been really good,
and the interaction with our team to make sure that
it does what it's supposed to do for our mutual
funds has been great. But I'm going to just step
back and say that from a coding perspective fantastic. From
an investment perspective, the answer is mixed, and it's that
(03:33):
AI has been made us, each of us as research
analysts able to read everything. We have an assistant now
our AI agents who read everything, every company transcript, earning transcript,
every government agency filing, every every trade journal, every bit
(03:55):
of news.
Speaker 2 (03:56):
Every actually the annual report. Someone's reading the report.
Speaker 3 (03:59):
Finally, it reads them all it can do all of that,
but what it can't do is make decisions with the information.
I don't know how AI will replicate the fundamental portfolio
manager who relies on his or her experience, has a
level of intuition that's probably thirty to forty percent of
the investment decision comes from something that you can't even quantify.
(04:23):
It's this instinct honed after decades of doing this, and
from a quanm perspective, with AI, the ability to find
signals that aren't actually explainable to clients as quite a temptation.
We'd be really careful not to go and use the tool,
(04:45):
i'd say ineffectively. So in short, AI is an accelerant
to productivity improvement, but it hasn't yet developed where it
can replace that human judgment. And I think that's true
across many of the companies that we research. They have
some of the similar experiences. So it doesn't confine to finding.
Speaker 2 (05:07):
When we're talking about it reading everything, every research report,
every every company announcement, every everything, and that'll be done
and summarized and presumably produced for enos. That's I mean,
if you're looking at thousands of companies, which I know
you are, that's a massive time saving. But back to
the intuition bit. It is the reading of those reports,
the reading of the company announcements, followed by the reading
(05:30):
of the transcripts of earning calls, et cetera, et cetera,
where a good analysts might pick up the bits and
bobs and make the connections that create the intuition. So
without the without the hard graft bit, yes, can you
have the bay.
Speaker 3 (05:42):
I can make some connections. You can find in the
footnotes where there might be counting anomalies. What it can't
do is what we're doing. It can't have a meeting
with management and observe the body language. You can't say,
you know, this doesn't feel right. I don't even know
how to put it into words. But I think they're
becoming the measure a little more caution, and I'm going
to take that back and assimilate that information. We don't
(06:05):
record meetings we I think management would find that a
little off putting and probably we wouldn't get any meetings.
But we're taking notes. But what we're it's what we're
hearing and the way we're observing how the message is
being delivered. That's so incredibly important. And this is not.
(06:27):
Someday when robots are doing the job and it's all visual,
I think the other side of the table will be
a robot too. It's going to be a pretty grim world.
Speaker 2 (06:38):
How And I don't normally get into young people early on.
We normally save that for the end. But the way
you're talking about the fund management business now the fundamental
part of it. Yes, what is the young person who
wants to be in fund management these days do because
all that grunt work that was the training ground.
Speaker 3 (06:52):
Yeah, yes, the grunt work initially is probably a good idea.
We encourage analysts to do everything from scratch to understand
what the meaning is of all these documents, where where
to go? When you in a prompt, one has to
ask the AI to search certain areas, or we have
(07:14):
agent builders that link into systems. It links into databases
and you have to know which database is to plumb.
But once an analysis has done this a few times,
they don't necessarily want to do the gruntwork because it
displaces in a zero sum day any something more higher
(07:35):
level thinking oriented. So I'm okay with the AI doing
the grunt work. It's just that if people stop thinking,
that's when we're in trouble. It's it's using that time
freedom where you're not entering the entering in the quarter's
earnings into your spreadsheet, but the AI is doing it
your clawed ad in or whatever the tool is. What
(07:57):
how else is the analyst using that freedom time? Is
he or she thinking about more about the assumptions, really
testing the model, going back to the notes and thinking
again about where they might have been wrong, taking a
step back and thinking more about structural change and how
this company what come out of left field being one's
(08:18):
own devil's advocate, and the AI can help with that too, interestingly,
But that's the higher level thinking that we want and
we are promoting.
Speaker 2 (08:27):
Okay, I'm convinced we still need you. Thanks. When you
look at how working in your own company, and then
you look at the businesses in which you invest, what
are you looking for in the companies you're investing in?
Speaker 3 (08:41):
Well, I'm glad you asked, because we for every sector globally,
have done a deep dive into how we believe they
will be impacted by AI. This is quite an endeavor.
We did this fundamentally in our quant colleagues observed the
process and the output. But what we found is for
many there are some structural changes that are going to
be quite significant, and then others there's a lot of upside.
(09:03):
Let's go to healthcare to start. We have a number
of pharmaceutical companies in the portfolio and now we're adding
more medical technology because they've been left out in the
cold in this huge AI driven rally. But their ability
to innovate, their ability to in the case of pharmaceuticals,
discovered new molecules advance them through the clinical trial process
(09:25):
more quickly, efficiency, lower cost is that could be given
that patent lifes remain the same. That means more years
out in the marketplace and less in development. That's a
profit booster. It's more hard pressed to see how there'll
be some sort of mysterious AI entity that will develop drugs.
(09:49):
Pharmaceutical business is very laborious and involves a lot of
interaction with the health authorities and clinical trials are carefully
scripted and then being able to target patients with AI
in advance of a doing trials so they are they
are the right individuals for that particular drug. That's another
(10:10):
way to accelerate the process and get output that can
be get that drug into the market more quickly. So
for healthcare, we think this is going to be fantastic.
Healthcare companies they gather lots and lots of data and
their ability to use it in ways they never could
before with AI is not that dissimilar from other industries.
(10:31):
It's just they have so much intellectual property and their
ability to innovate now is improved. And innovation equals pricing power,
and pricing power is margin, and margin is profitability, and
profitability leads to cash flow, and cash flow gets returned
to shareholders.
Speaker 2 (10:48):
Okay, that makes sense. How does that then interact? I
mean one of the one of things about healthcare sector
is how regulated. It hugely regulated across the board, regulated
in different ways in every country, but the layers of
regulation massive.
Speaker 4 (11:01):
Is that a barrier, It's part of the moat, and
regulation and compliance and on the need for audible outcomes
are one of the reasons why some industries they will
they just won't have this sort of AI competition.
Speaker 3 (11:17):
The market might be inferring they're going to incur. So
a mote is a plus and a minus. A mote
can protect the business from competition, but it can also
mean that there will be it conhibit growth. You need competition, yes,
yes you do. But the working their way for the
(11:39):
regulatory maze is what healthcare companies do very well, and
the large ones have whole teams for this, and the
teams may be able to harness AI to be more
efficient doing that, which could be also a cost savings
as well as time saving.
Speaker 2 (11:53):
Interesting, and we've all talked on this podcast about how
big companies love regulation because nothing, nothing holds competition back
more and a good bit of regulation. And one of
the thought was about AI was that it might be
one way for new entrance to circumvent We'll find easier
ways to deal with large parts of regulation. But it
sounds like your case is that that is not.
Speaker 3 (12:16):
Going to happen. It depends in something that gets put
into the human body. The regulations there for a reason. Yeah. Yeah,
it's a little different. Say financial services, okay, that necessarily
got to create a health outcome.
Speaker 2 (12:30):
Okay, So what other sectors will have a regulatory remote
that will limit the use of AI elsewhere?
Speaker 3 (12:37):
Well, iound I've been talking about software as a service.
This sounds a little silly, but it's tangential. The SaaS
companies have all sold off this idea that you're a
software business, you had a seventy plus percent gross margin
or higher. Now your business is losing its mode and
the software will be vibe coded. Anybody can now code,
(13:01):
but code isn't the mote. And these software companies that
provide like SAP or Oracle very comprehensive for Fortune for
five hundred global companies, and SAP in particular this mission
critical software where they're dealing with systems of ledger in
businesses that are heavily regulated. That means that data is crucial.
(13:24):
There can't be errors in the outcome. So software needs
to be deterministic. Yet generative AI is non deterministic. We
can be a useful tool for users in the enterprise
to get access to their data and see it in
different ways. But it can't run the business. It can't
run HR, can't run account it can't run supply.
Speaker 2 (13:46):
Chain, can't run relations.
Speaker 3 (13:49):
Yes, so I think about that as the market has
just decided these companies are all to be incurring great competition,
and we would disagree. It's the it's regulation and the
need for the businesses out everything they do to be
fully audible and transparent, auditable that that make it will
(14:13):
make it quite hard for new AI native AI startups
to undermine them.
Speaker 2 (14:18):
Okay, so you quite heavily invested in the likes of SAPA.
Speaker 3 (14:22):
We are. We are fundamentally the good management, incredibly sticky
business and all that migration to cloud that's coming up,
that's one of the absolute So what we know, there's
a lot we don't know. What we do know is
that for enterprises to take advantage of AI, they need
to move their data to the cloud, they need to
(14:44):
have it accessible for the AI, and they need to
be able to access that tremendous compute on an as
needed basis.
Speaker 2 (14:51):
And are you on the other side of this, are
you and any of the hyperscalars that they don't fit
into your your fundamental matrix.
Speaker 3 (14:58):
Some of them do, some of them do. For example,
the two great digital advertising leviathans, Meta and Alphabet generate
enough free cash flow to where they can fund their
foundational model ambitions and so they can fund their own
cap X, which is very different from some of these
(15:20):
massive new AI companies where it's all about finding more
investors who believe in the dream.
Speaker 2 (15:28):
They're going to be voyant with the opena ipo.
Speaker 3 (15:32):
I cannot say.
Speaker 2 (15:34):
I'm kind of guessing where else are you finding value
in the market?
Speaker 3 (15:39):
Well, I did mention in passing medical technology. I just
think it's fascinating that you could find companies like Boston
Scientific and heart valves and very complex, important cardiovascular devices
that you cannot get anywhere else. They used to trade
twenty five or thirty times earnings and now they're multiples.
(15:59):
Are half that. Uh, Companies like Striker or zimmer BioMed.
They're fantastic medical devices as long as human bodies break
down are going to be needed. And the very research
intensive business. And to the degree they keep innovating and
(16:22):
they're not in commodity products, they should do quite well.
Part of what's weight on them has been concerns about
the g LP one trends and consumer and individuals will
no longer need new body parts, and we think that's unlikely.
In fact, the longer they live, the more part replacements
(16:44):
they'll need.
Speaker 2 (16:45):
Okay, so people will get thin, they'll still need the
replacement polsitives. I quite need them until later.
Speaker 3 (16:50):
Yes, and they won't.
Speaker 2 (16:51):
They won't.
Speaker 3 (16:52):
They won't all get thin, sadly, wun't they? No, Some
people will neither want an injection or where they wanted
they will take a pill, they won't, they won't do it,
and compliance will well, as always with drugs, they're not necessary.
People aren't necessarily willing to comply.
Speaker 2 (17:10):
Sure, it has been fascinating seeing the obesity rate in
the US drop. It has for the first time.
Speaker 3 (17:15):
Yes, it has change, and that should lead to better
healthcare outcomes and lower cost healthcare.
Speaker 2 (17:25):
Two new hips each whenevery one's ninety, yes one at sixty,
I'll take two, please, and a couple of knees. Or
(17:56):
when I look at your at your your main vehicles
ugly global, global, international, two different words for it. But
you also have some emergen markets exposure. The Global fundkind
of twenty percent in emerging markets, and there's also one
Emerging Markets fund, right what's interesting there, And we've talked
about this quite a lot recently about how the difficulty
of emerging markets being now so defined by career in
(18:18):
Taiwan and that market concentration making a nonsense of the
idea that you can get diversified exposure within index has
been one of the things we've been I'm afraid going
on about for rather too long. But then the question
is if you're not going to have index index style
exposure to those two countries. Of course, to China, what
are you going to have?
Speaker 3 (18:36):
Well, I would argue vociferously against indexing emerging markets, and
I don't just give recent examples. Maybe twenty twenty two
isn't that recent, but Russia, like, why would you even
wanted an index weight in that market? We were underweight
and very underweight, and that was extremely helpful. Sometimes emerging
markets go to zero, and that one did. That's why
(19:01):
they're emerging. They have much higher levels of risk because
they're growth markets, and they interestingly, they're not all demographically
in that growth phase. China, we didn't. It's been the
largest of the emerging markets, and now it's number three
behind South Korea and Taiwan, which is also fascinating, but
(19:21):
it's within China, and that.
Speaker 2 (19:22):
All three of them have shrinking populations.
Speaker 3 (19:25):
They do, but at least South Korea and Taiwan have
semiconductor giants in memory, and Taiwan has TSMC in chip production,
and there are no substitutes at present, there won't be
for a couple of years. No matter how many fabs
are built or semiconductor facilities, it's going to take some
(19:49):
time for supply to catch up with the demand. If
demand may sag, and there may be technological reasons why
we don't, you know, memories and quite hot as hotly
demand as it is now. But that's very clear, and
I can see those markets of those are highly highly concentrated,
and the stocks they're those big three stocks are very
(20:12):
large in the benchmark. It's beginning to look a little
bit more like the US, oddly than anywhere else. What's
interesting in emerging markets. I think in China there are
all kinds of companies that have been left behind. We
were talking about US hyperscalers. You could have the Chinese version,
effectively the operating system of China through we chatter wishin
(20:34):
which is Tencent. They're the largest publisher of music.
Speaker 2 (20:39):
Video or.
Speaker 3 (20:41):
Video games globally, and they have a music business, they
have a messaging business, they have the most amazing flywheels.
So they're massively cash generative like US hyper scalers, and
they're developing through HY three their own foundational models. They
got they were a little behind in a but it's
when you have that kind of that that sort of
(21:03):
financial resource, their net cash, it's not too hard to
catch up, and they will. They'll find a way to
get AI infused throughout their consumer products, that all the
social media they do, and they'll keep their customers and
that what is it one point three billion monthly average users?
(21:25):
Like they're just this doc just keeps falling and we
just look at it and we wonder, why, what an
amazing company. It shouldn't trade at mid teens multiples of earnings.
It should be much And part of this is just China.
No one's interested right now. It's so there's this love
hate relationship with China. Only if three or four years
(21:46):
ago it was uninvestible, that's probably the time we all
should have bought a lot of it. But now all
eyes are in one area and not there. And especially
for these Chinese companies that aren't necessarily at the considered
at the absolute forefront of AI, they've been discarded. And
(22:08):
this is where taking a two year view is really
useful as opposed to just thinking out the next three
to six months, because it gives us a chance to
accumulate what maybe one of I think the I think
my colleagues would agree with me, probably one of the
best companies in China overall for a very attractive valuation.
Speaker 2 (22:27):
Yeah, and the lack of interest in it is just fashioned,
just people coming slowly back to being in the Chinese market. Again,
the fact that it's impossible to draw your eyes away
from the stars and the etector in the US. And
as they said, these few as you market.
Speaker 3 (22:41):
Yes, I think so. I think so that there's a
certain amount of short term ism baked into that. It
may or I mean, we could be we cause we
could be wrong and ten Cent doesn't develop out their
AI features fast enough and and part of their business
gets competed away. But it's very unlikely that's going to happen,
(23:02):
given their track record, given what they've already built, and
given the marketplaces where they dominate. They you know, they've
got infrastructure as a service, their platforms a service, and
software as a service, and they will they have this
cloud business and that gives them a lot of compute
and a lot of flexibility. And again that balance sheet,
(23:23):
it's like they have all the raw materials and they
have the history of doing it, and that usually convinces
us as fundamental investors. And given how low the valuation is,
this isn't the risk is very modest. Versus I mean
you mentioned semiconductors we started. Given where they trade, they're
(23:44):
very risky right now.
Speaker 2 (23:46):
Well, because they're cychnical businesses. Right, this is exactly the
wrong point of the cycle historically, if you were looking
at this is a normal cycle, exactly the.
Speaker 3 (23:54):
Wrong cycle exactly. You don't believe in a cycle if
you think that they the demand goes on prepared actually
like this, and the supply will be will not meet
demand indefinitely. But that's I think physically impossible.
Speaker 2 (24:08):
Yeah, normally at this point you would stop to see
a shot rise and supply and the fool of and
demand at the same time.
Speaker 3 (24:13):
Or all the market needs to perceive is that their
supply is planned. That's all. That's all it'll take to
tip them back the other direction.
Speaker 2 (24:23):
Well, the always us to say, I remember someone telling
me when I was a very very junior broker that
the chip makers you seld them when they were very cheap,
and you bought them when they were very expensive, because
that's how the cycle looks.
Speaker 3 (24:35):
Yes, yes, exactly. The multiples tend to be low. This
is where people often get confused. They think very low
multiple stocks are value stocks, so they're cheap, but it
could be. You have to look carefully. If they're in
cyclical industries, their earnings are at a peak, and conversely,
when their earnings are at a trough, their multiples.
Speaker 2 (24:55):
Are look very expensive. But that's exactly the time is
their earning start to go up gun.
Speaker 3 (25:00):
And it's really helpful from an investor perspective to be
in a cyclical business because at least you have history
as a guide. If you're in a business that has
no history or everything has changed, you can't use the
past as a predictor of the future. And in my view,
it makes cyclical investing, assuming there isn't some massive change
(25:23):
in the business, lower risks than appears at first glance.
Speaker 2 (25:28):
Let's go back to the US. We've talked briefly about
the intense concentration in the US indices, and we've talked
a little bit about biotech and pharma, other other sectors
in the US that you are finding very interesting at
the moment that outside these hugely expensive tech companies and
outside what we've READI discussed that.
Speaker 3 (25:46):
Well, because tech is so massive. Technology communications services and
another stock that's come out of our research is in
the IT services area, and this is a major contract
of the US government Booze Allen and again in the
category if we didn't used to be able to buy
these stocks because the growth rates were high and the
(26:08):
multiples were even higher. The concern about reduced use government spending,
especially in civil but seventy three to seventy five percent
of booz Allen's revenues come from military defense. So the
US government needs to modernize its systems and it needs better,
(26:30):
much better cybersecurity. This was all common sense, Like nobody's
ever said to me, Oh, that's not true.
Speaker 2 (26:37):
Yes, in any cybersecurity they'll be fine.
Speaker 3 (26:39):
Exactly. So, this is an eighty five year old company
and ninety percent of the revenues come from US agencies.
They've they've had somewhat of a partially rocky relationship, and
yet nobody else can do what they do. They they're
partly they collaborate as well as compete with Palenteer can
(27:00):
take all the business. There's you know, there's military cryptography needed,
there's I mean, there's just so many different areas where
Booze has has that dominant expertise, and it's a it's
just eight billion dollar market cap now and it trades
at high single digit earnings. You can then market has
(27:21):
said it's going out of business or it slowly surely
will melts like an ice cube in the sun, and
we disagree. And valuations, yeah, well, evaluation they're very attractive,
probably should be at least fifteen times next year's earnings.
And then you get a three point six percent dividend yield,
which is something a lot of these tech stocks don't
give you much in dividend. They may do share of
(27:44):
purchases like SAP does big buybacks. I think they've been
out something like ten billion euros over the next couple
of years.
Speaker 2 (27:52):
It's extraordinary, isn't it. We've talked about this quite a
few times recently as well, the way that ever the
last decados the stock market has become at an extra
machine for investors, where you take out your dividends, you
take out your special dividends, you get your money back
and buy backs, et cetera. Whereas originally the whole idea
was that individuals gave money to companies, then the other
way around. Well, there's still plenty of that happening too, well,
(28:13):
there is now, But if you have to think about.
Speaker 3 (28:16):
How in the in the idea of gaining a return
if you were expecting let's just say ten percent annually
from your global equities, which I think is a very
punchy number, but let's just throw that out there so
we can all smile and love the fact that our
money is doubling every seven years. What if you can
(28:37):
get a third or forty percent of that in dividends,
that's phenomenal. Then you don't have to rely so much
on capital gains. Is this sort of dividend one oh one?
But the dividends are a signal management saying we're so
confident in our business. We're sending money back to you
shareholders and that's great. We want them to be confident
(28:59):
if they once dividends are paused or eliminated, that's a
time to be a little nervous.
Speaker 2 (29:06):
It's not like an add for the UK market.
Speaker 3 (29:09):
Well, the UK given that we passed these great dividends,
hits the bargains in the UK market, there's no doubt
about it. And it's just a question of when the
global spotlight turns to it. Somebody say this week they
thought that your private equity was galloping over here to
take a good look.
Speaker 2 (29:26):
Oh, yes they are. And then we find ourselves in
this ridiculous situation where you can investors won't buy UK companies,
private equity arrives here, buy them up, and then we
buy the private equity companies or the private equity funds
and just have the same stuff in them and pay
five times the fee. Yes, yes, not ideal.
Speaker 3 (29:44):
Not ideal. There's so many things in the world that
aren't ideal.
Speaker 2 (29:47):
What might make global spotlight move here in a good way,
because it quite often moves here in a bad way
these days. Still make stable government, stable government, good luck.
Speaker 3 (29:57):
Hand yields remaining stable, if not dropping slightly, which would
mean getting inflation under control and having a fiscal stability. Yes,
well I didn't. I don'ty it was gonna be easy.
I just said that would.
Speaker 2 (30:12):
Be I was just for those of you who are listening,
not watching. I'm just looking there going well. I mean,
I don't even know what to say to that, because
these things sound quite unlikely for world you get about it.
Speaker 3 (30:22):
Globally competitive companies. I think about astrozenic and pharmaceuticals. What
a what a what an incredible innovator they're based here,
but they don't. I mean, I don't know what percentage
of revenue I guess is less than ten in this country.
But to have a company like that listed here is
tremendous or in life insurance and Prudential Plc. They're an
(30:45):
Asian life insurance giant.
Speaker 2 (30:49):
Well, I mean, we always say that a very small
percentage of forty one hundred revenues actually come from the UK,
well under forty percent.
Speaker 3 (30:55):
Yes, yeah, but that's okay. The fact they've chosen to
domin style here and use UK jurisdiction is an endorsement
of the UK legal system and they like the weather.
Speaker 2 (31:12):
When you look at your portfolios, Sarah, all the many
portfolios across the board, look at them, and is there
anything that you worry about?
Speaker 1 (31:19):
What?
Speaker 2 (31:19):
You look at them and you think, oh god, if
this thing happens around a whole part of dropt And
one things that one of our most recent guests was
talking about was if AI works as suggested, and perhaps
is in the way that you've suggested taking away a
lot of the grunt work, and we see a lot
of highly paid jobs disappear. And this guest was saying, well,
maybe fifteen percent of of high income jobs will disappear.
(31:40):
I might call high income jobs. Then that has an
immediate knock on effect into the flows into four to
one case, which again has not gone effect into the
flows into passive funds, and then we might see a
massive market collapse of GFC style collapse. That was his worry.
Speaker 3 (31:57):
I don't share that. I'm more in the mark and
in camp that the day. I think there are some
industries or even sectors that we're going to struggle a
little bit, are gonna have to find new ways of
proving their value to consumers. But as for employment, I
would have more software engineers because they're doing so much
(32:17):
like there is revolutionary. And as for analysts, our analysts
will be even more productive. We'll be able to cover
more stocks. There's seven thousand stocks and we only can
cover about ten to twelve per person pretty well, and
in quant we can cover quite a lot, but it's
a breadth strategy, so we don't have any depth there,
(32:38):
and we'd like to have more depth. I mean, why not.
It would make our models even more informed. So I
would happily take on more analysts if the AI tools
make them even more productive, because then they sort of
pay for themselves. So I think it really depends on
the industry you're talking about. First, I thought it would
put lawyers out of business, and of course I should
(32:59):
never have thought that.
Speaker 2 (33:00):
Nothing everything is that, of course not but whatever it is,
But there is why they didn't train enough people at
the boatman And then there aren't enough experienced people in
the middle to check the mistakes of the LLLM.
Speaker 3 (33:11):
Yes, well, so that's Look the LM's that right now.
The AI coding agents do the coding and then check
the coating, and but somebody has to be there across
the table from the client. Somebody has to supervise it all.
And then the amount of legal work is just urgin.
Speaker 5 (33:31):
Look at radiologists, we thought maybe they would go out
a bit with all the scans in the AI, and
when you get a scan, it's compared to thousands, maybe
hundreds of thousands of different and you have the benefit
of all these different radiologists' opinions.
Speaker 3 (33:46):
But you still want the radiologists in fact now too.
Speaker 2 (33:50):
You want one to do well.
Speaker 3 (33:51):
Not just that, but if it brings down the cost
of the radiology process, then more people who heretofore wouldn't
have been scanned because it was too expensive, can afford it,
Like the marketplace, the tam the total dress ball market
gets bigger, so you need more radiologists.
Speaker 2 (34:07):
It's like a hypochondria extreme.
Speaker 3 (34:11):
Well, yes, one can find things if one goes to look.
It's so true. But every once in a while it's
saved somebody's life, so why not.
Speaker 2 (34:19):
Yeah? Absolutely, all right. Last question, last question. You said
that people come to London for the weather, when at
the moment we are talking, it is very, very hot
in London. Well, hope for us anyway, hold for us
over thirty degrees, So a lot of people heading to beach.
When you go, what are you going to take to read?
Be reading at the moment.
Speaker 3 (34:41):
I really like sci fi, so I will read as
much science fiction as I can get my hands on.
I don't know what it is. I've never really been
that interested in history. I've forced myself to. Thank God,
my husband is a great historian, so he helps full
(35:03):
need offense for me. Yeah, but when I have one
of those husbands, taos great. Thinking about the future is
fascinating going back and reading some of the great sci
fi of the past and anything that's been written in
the last ten years. But when when an author who
has a great mind divines the future, and it turns
out that's sort of where we're heading today. And they
(35:24):
wrote it forty or fifty years ago or more. I
just find that thrilling. Yeah, I ask you.
Speaker 2 (35:30):
And I think I might even have mentioned this on
another book case. My son was reading something called The
Invasion of the Aliens Wells and that fascinating because a
lot of it is like, how did you think of
that back when in horsing garriage days? How do you
think of this? Yes? Exactly the extraordinary? Do you prefer
utopia or a dysktype? Yeah, and your satisfaction where you're
not quite.
Speaker 3 (35:50):
Sure where the word ends, where it could go either way,
because dystopian is depressing.
Speaker 2 (35:56):
Yeah, yeah, a lot of that about a lot of
depressing about an invest Sorry, you have to ultimately be
an optimist otherwise you're not going to hold anything. Oh well,
we'll leave it there, Darah, thank you so much for
joining us today.
Speaker 6 (36:06):
Thank you, Mary, thanks for listening to this week's Marryn
Talks Money.
Speaker 2 (36:17):
If you like our show, rate review and subscribe wherever
you listen to your podcasts, and keep sending questions or
comments to Marryn Money at Bloomberg dot net You can
also follow me and John on Twitter or x I'm
at Marinus w and John is John Underscore Stepic. This
episode was hosted by Me Marrin's UNSEP Web was produced
by Someersadi Moses Andam and Jennifer Seely. Sound designed by
(36:39):
Blake Maples and Aaron Kaspers and special thanks of course
to Sarah and Kett
Host
Merryn Somerset Webb
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