How Artificial Intelligence is Changing the Financial Services Industry @BarryLibert #DataTalk

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- Hello and welcome to Experion's Weekly Data Talk,
a show featuring some of the smartest people
working in data science,
as well as thought leaders leading the industry.
Today we're very excited to feature Barry Libert.
He's the CEO of Open Matters and a strategic advisor
for some of the biggest global brands
like Goldman Sachs, Microsoft, GE, and ESPN.
Barry is also a bestselling author
and has written for the New York Times,
Wall Street Journal, Financial Times,
Harvard Business Review, and many others.
Barry, it's an honor to have you in our chat today.
- Thanks for having me today.
- Barry I thought it'd be great if we can just kick this off
if you could share a little bit about yourself
and the work you're focused on right now.
- Sure, so this work started a long time ago.
It's the basic thesis that just like the human genome,
there's an economic genome and you can use data science to
basically find out what that economic genome is.
- Very, very cool.
I mean, it seems like every single day
I'm reading articles about artificial intelligence,
how it's changing the workforce.
There's a lot of fear I think,
sometimes those articles about robots taking over
and definitely in the financial space
we're seeing signs of robo technology
and artificial intelligence.
In one of your latest articles
you wrote for Harvard Business Review
you wrote an article focused on how even top consultants
in financial services may soon be replaced,
and was really curious if you could talk
a little about that
because that was a really great article you wrote.
- Sure, so the article was more
than just financial consultants.
It was marketing consultants,
strategic consultants, financial consultants,
auditors, legal, doctors, all consultants.
So if you think about the consulting industry,
just talk about one piece of it,
strategic consulting industry in the United States alone
is about a 70 billion dollar industry.
Think of them as doctors
that are doing business the old fashioned way,
which is a patient, a CEO,
comes into my old alumni firm, McKinsey, or Bane, or BCG
and they ask them a question, what's wrong with me?
And that doctor, that consultant,
gives them a piece of advice based on their own experience.
None of that experience is captured in a data structured way
that benefits in today's machine
learning artificial intelligence.
All our article was proving is that it's not just medicine
that artificial intelligence or machine learning,
or in financial services where artificial intelligence
and machine learning are taking an impact.
It's going apply to every single industry
where the services industry has had a huge growth cycle
in the last 50 years.
And that means all the best consultants
are going to have to deal with the fact
that machines learn faster, are more scalable,
and more repeatable than you and me.
Nothing more complex than that.
- Yeah, I think I even read an article a few months ago
talking about Goldman Sachs had a layoff
of a lot of their financial advisors.
Did you happen to see that one?
- I did.
And that's happening around the world
in the financial services industry.
You look back awhile, which is decades now,
the financial services industry
went from what's called active managers,
which was financial advisors giving advice to you and I
about what stocks or bonds to buy
based on what that manager had as his or her perspective
on the financial markets.
A long time ago, really a long time ago,
John Bogle, who was the chairman CEO of Vanguard
had a thesis that monkeys made better decision makers
than financial advisors.
That you could basically throw darts at the wall
and get a better return.
Now, the truth in there is he was right.
ETFs or what's called passive investing,
have outperformed the smartest
of all stock and bond managers.
Which means that the construct of actively advising
is doing less well than passively investing.
You've seen the explosive growth of not just ETFs
and passive managers, you're now seeing
what's called robo investing like Wealthfront and Betterment
begin to offer for you and me, the individual investor.
- Yeah, and I think it seems that from what I understand
around Betterment and some of these robo advisors,
sometimes the combination of artificial intelligence
choosing what stocks or indexes for people to invest in.
But also, there is some element of human management.
Do you happen to know how humans are working with AI
despite the layoffs?
- Sure, the layoffs aren't that big, right?
In fact, they're not big at all.
Growth in the industry is outpacing layoffs by far.
So, there's a massive fear, I call it,
on layoffs by, you know, robots displacing you and me.
I don't believe that.
It's going to create new skills,
obviously we might argue that 100 years ago
machines displaced humans when we started building cars,
or 150 years ago, tractors started displacing farm workers
and we started automating farms.
This is just the next iteration of machines
complementing human workers in ways
that you and I don't scale.
And all our research has shown and our article was about,
was sorry, for all of you people that don't think it's
coming to your industry,
which is all the services industries,
not just the financial services industries,
the marketing service industry, the audit service industry,
the legal services industry.
We gave examples of every industry,
the medical service industry,
where robots and artificial and machine learning
are going to complement human intelligence
and human learning.
- Yeah, it's amazing.
It's amazing to see the growth
and I feel like just in the last year
just tremendous growth in people interested
in machine learning, artificial intelligence.
I mean, I was looking at some Google trends
on the amount of traffic being generated around those terms.
Part of it might be out of fear, but then to your point,
there is going to be this strategic alignment
between human and artificial intelligence working together.
And, I think it's going to be a beautiful thing.
And I really like your positive outlook about,
just as we looked in the past,
how technology has displaced some workers,
there's just new jobs that were created from that.
So, I love your positive outlook.
I'm curious about some of the feedback you received,
because your article in Harvard Business Review
was very very popular, was shared all over the web.
I loved reading it.
I'm just kind of curious at the responses you've got.
- Well, surely there were both positive and negative
as you might imagine because we were taking a pot shot,
right, at the world's most elite.
My alumni firm, McKinsey, and Megan Beck who's my co-author
is an ex-Bain person.
So Bain-iac, right?
And my brother was at BCG,
you know, this our heritage from a lifetime ago.
It's hard for them to understand when they are reporting
all day long, McKinsey at their very best, is reporting
on the impact of AI in all other industries.
But not their industry.
It's like them suggesting,
like the taxi industry wouldn't be impacted by Uber,
the consulting industry wouldn't be impacted by AI or Alexa,
right, which what I think is coming anyway.
You and I will be getting my advice from what's sitting
right there on my desktop.
And, so, we had obviously had negative feedback.
Consultants saying, well what job will I have
and who's going to write your next article Barry?
- (laughing)
- According to your interview, a bot is going to have
some influence on that as well.
But there's negative and there was a lot more positive.
Which was trying to understand what does it mean to me,
just like you said, how do I think about it?
We were surprised, on my own LinkedIn page,
2,500 reviewers, right, and likes.
It was amazing to me.
- Yeah.
- HBR, I think there was 400 or 350 comments.
It just blew my mind.
- Wow.
- People are interested, right,
in this article on this area.
- Yeah, like I said, it popped up on my radar,
I saw all the sharing.
People obviously loved it.
And yeah, so I was just curious to hear about,
obviously there's going to be people
that are kind of frustrated or upset,
especially in those in Fintech,
who might be fearful of their jobs.
But I think you definitely touched on a hot topic
that everyone's very very concerned about,
but also excited about too.
- Yep, I think that's was our point.
But the most important part of our point was to tell
truth about something.
Megan and I were both presenters
at the annual MIT Platform Event.
And, it wasn't just falsehood in that article.
My co-presenter as the keynote speaker
at the annual MIT Platform Event was Alexa.
We had to mike Alexa.
And, we literally asked the machine questions
that no consultant could ever
ask about global economic trends that were the synthesis
of machine learning AI looking at 40,000 companies
across the world, across thousands of variables,
and tens of millions of words over 40 years.
- Oh, wow.
- It wasn't that we were kidding.
But, we're happy to share an image
that shows me talking to Alexa on stage.
I mean, of course I started with a silly quote,
an Alexa knock-knock joke, but I took Alexa
all the way to the end, asking board level questions
of things they couldn't get from their consultants
if they had to pay 10 million dollars.
- Wow, that is amazing, that is amazing.
Just seeing the voice, AI, products being developed,
Alexa, Coursera, and what's possible.
And like, what you just shared
because of artificial intelligence,
because of the amount of data that could be crawled
and analyzed and for Alexa to be able to return back to you
smart answers very very quickly
where it would take an advisor a lot more time
to go do some digging.
I mean, the ROI on that is just phenomenal.
- Yep, my always message is I have a simple thesis in life.
I wanna replace a Barry call, a call to Barry,
with a call to Alexa.
I'm tired of getting calls
that ask the exact same question to me every day,
I don't wanna become a platform network and AI company
for the last 20 years when AT&T was my first client
a long time ago.
And I said to them, I'll have a call answering service,
they can call right to Alexa and they can say
I'm calling Barry and Alexa will answer the phone.
- Yeah.
I think there's gonna be a Barry bot.
- There you go.
I'll hook it up so you can answer
some of your other interviewees
and people that you've had on your show
so I can figure out how to do that next.
- Yeah. (laughs)
It's so funny because when I, when Alexa first came out
I was thinking, oh, so it's just something
you can ask about the weather, you know?
I had a very small knowledge of what capabilities
of some of these voice AI systems were doing.
Like oh, weather, shopping, basic things like that.
But yeah, when you're talking about
being able to use it for strategic business intelligence,
being able to crunch numbers and return back to you
the data that you want, that is outstanding.
I mean, I'm really curious about, you know,
with all of these developments Barry, and especially too,
the article you've just written,
where are the boards and the C suite?
Where is their pulse?
How are they feeling about these different issues?
- Oh, they're nowhere.
They are stuck in Excel land,
which is about 40-year-old strategy technology,
getting annual reports put up in board packs, right?
You know, technology's in place
in board packs on their iPads.
They're nowhere.
I mean, every board meeting I attend or participate with
on executive teams, I say, it'll finally be somewhere
when the data, chief data scientists,
not the chief data officers, the chief data scientist
is sitting next to the chief financial officer
and he or she is reporting the status of the business
because there's more non-financial data out there
that provides the vitality of the company
than there is financial data.
So they're nowhere.
They literally have no insights
about what is possible today.
- So like, with that lack of knowledge,
because part of it is just like,
the tremendous growth in AI, in big data,
that's been happening and it's just skyrocketing right now.
So I'm kind of curious, for those that work in data science,
thinking about data labs, data science teams,
how do they and how do you recommend that they
approach senior leaders, maybe it's the chief data officer
or the CTO, how do they make a clear business case
for you know, using AI and doing business in this way?
- So it's really important, you know,
when in Rome, you know, speak Roman, you know,
things like that, or when here speak English,
whatever the words or language.
When you're in China, speak Chinese,
when in business speak business speak.
And my data scientists don't know
how to speak business speak.
Even my chief digital officers
don't know how to speak business speak.
There are no shortage of digital guys who report to me
through their companies that they tell me,
I'm the tech guy, I'm the tech woman.
They go, I don't speak that language.
Even if I get it, they're not gonna get it.
So data scientists now have to learn
the science of business models as well,
which is today's business models are powered by AI.
I mean, think about the fact that Facebook
is spending two billion a quarter in AI and data science.
Data science inside incumbent organizations
have to explain in economic terms,
what are the revenue opportunities,
what are the cost saving opportunities,
what is the shareholder value opportunities?
And if there's a social enterprise,
what is the impact opportunities
that you can create as a data scientist
that will impact the agenda of the organization?
Otherwise, you know, you'll be reporting
to somebody in the tech department.
- Where, I mean, so for a data science team,
who, like in the, who should they be reporting to?
Because sometimes some companies
don't have a chief data officer,
so in those types of companies,
where should data science report to
and where would they make that business case to?
- Well, you know, the CFO, otherwise known
as the chief financial officer,
I call him the chief no officer, the CNO.
They have to go report to the CNO and explain to the CNO
why data science is today's oil rush, it's today's gold.
It's the insights that power tomorrow,
they would argue, tomorrow's organizations,
but in fact, it's today's five,
what I call the trillion dollar behemoths,
the Apples, the Amazons, the Alphabets,
the Facebooks, the Microsofts.
They need to go to the CNO and say look,
those companies are worth almost a trillion dollars,
it'll be our first trillion dollar organizations of all time
because they understand at the base and the foundation
of those organizations are data, platform and network.
And it's that three, that Venn diagram
that creates all the economics.
The CNO, if he or she is any good, will understand wow,
that's something I've never heard before,
let me see what I can do to achieve that goal.
So if I were them, I would report to the CNO.
- And for those companies that are looking to hire
a chief data officer and the CDO was kind of a new role,
emerging role that we're seeing more companies bring on,
what skillset should that CDO have?
- So currently I think CDO means chief digital officer,
right, which is an important distinction
from data science, right?
Digital officers in my view
are really important in an organization.
They're the intersection
of information technology and business.
They're the people who can speak the business language
and make a business case for technology
as the core of the organization.
They're often not data scientists, at least I've not seen.
They come out of the technology realm.
And I try to explain the difference
between a software architect and a data scientist,
are like the difference between a plumber
and electrician, right?
Or a neurosurgeon and a cardiologist.
They're not from the same -ology.
They're called data scientists and technologists, right?
They come from a similar lineage but a different lineage.
And so data science has to find its own voice.
And I think it's okay to be into the traditional CDO,
the chief digital officer,
but I think data scientists need to make a business case
to be right to the CEO.
- Okay.
Yeah, I like that, I like that.
But like you said, it needs to be done in business speak,
in the language.
- Correct.
Otherwise it'll be underfunded and too late to the party.
I mean, this stuff, like tensorflow is a free offering
since November from Google, right?
So you get these spectacular open source environments
like Linux now and Aioworld, and they're moving so fast.
If you're not in the world of being there all the time
as an organization, forget about some data scientists,
you're just gonna miss the whole game
because by the time you get into the game,
it'll be generations further.
It's already free, so the question is
it's free between base needs, it's free
with AWS or so inexpensive.
And Google offerings and Microsoft offerings.
It might as well just be free.
The question is its application and its economical impact
on an organization.
- Barry, I wonder if you could share some of the ways
or stories that you see consulting firms or businesses
using AI right now to improve their business decisions?
- Sure, let's start with the big one that was announced
a few months ago, which was Blackwall, Blackstone rather.
Which is a five trillion dollar
investment management organization publicly traded,
made an announcement that
they're going to approve their returns using robots.
Quote unquote robots, AI machine learning robots.
Because they realized at a scale they needed to use,
at five trillion dollars at scale,
they need to be able to use large amounts of data
that historically viewers could watch, you know,
all of those screens, watch these traders
or watch 100 screens or four screens while you did it.
It's impossible to look at the amount of data
that we're consuming and absorbing
in our data science group.
It's not possible to see it all, right,
and to make sense of the pattern recognition.
So I think Blackstone is a really good example of that.
From there, I think that's, sorry I meant Blackrock.
Not Blackstone, sorry, which is another investment.
So Blackrock is a really good example of that.
You're now seeing it obviously in the healthcare world,
right, you see now, you know,
the original Craig Venter experience of doing the genome.
You're now seeing AI use the human genome
to create something called Crisper, which is g editing,
which is an amazing thesis.
Last week alone was the first time ever, said this article,
or this news announcement, last week,
for the first time ever, a human embryo
was genetically modified using Crisper,
which is an AI-based tool
to alter the genetics of the DNA of that human.
They didn't let that embryo live, but that was last week.
- Wow.
- So Crisper, an AI-based tool for genomic editing,
just like we're suggesting
you can do economic editing, right?
A second example.
But you're now seeing it in the mining industry.
Something you'd never imagine.
Which is, we see it in the gold and oil industry
where they're trying to understand the data
from below the level of the ground in the water,
to do that as well.
So this is at the tip of the iceberg
of where large amounts of data,
which historically have been unmined,
are gonna be organized, structured, create data links
and on top of those large expansive data links,
create machine learning capabilities
that will produce insights for humans to learn from
and humans and machines to work together.
- Yeah, I think I saw that article
and then I saw a similar article about some scientists
that were able to inject like, animated gifs or video
into human cells.
And it's just mind boggling
to see the amount of work that's being done
in the human body to help make, you know,
human life better for health reasons, etc.
- Correct.
So you can imagine just like Blackrock
is gonna try to make investment decisions better,
and you can imagine how we're helping
make business decisions better,
you can imagine how the healthcare industry is gonna use it
to make better healthcare decisions.
Now they have a culture to decide,
because you could decide you wanna have blonde hair
and blue eyes, right, and do some gene editing.
If I'm in Poland, maybe being you know, from there.
I could decide I wanna be
completely a different human, right?
Well that's gonna be some ethical questions that are,
you know, should that really be possible, right?
Should I be able to have, I can't get,
my wife and I couldn't have any more children, you know,
but maybe my children are gonna decide
they wanna have specifically engineered children using AI.
Those are gonna be awesome questions for us to answer.
- Yeah, yeah.
I mean, all the ethics involved, it's fascinating.
Especially as things are moving so quickly.
I'm kind of curious Barry, are there any other,
as you look into the future,
especially in terms of financial services,
do you see anything upcoming as far as things
that'll be AI-based to help improve those
that are looking to invest or manage their finances?
I'm just really curious.
- Absolutely.
So we're working on risk AI products, which is really cool.
Right now Finch and Moody's S&P provide debt rating,
you know, all these funny looking letters.
But we're doing risk AI products now,
not just strategy AI products.
And that is really critical, because now you can look across
these non-financial variables like customer retention,
customer intimacy, human capital you know, engagement,
and begin to see ways that risks are created
from what used to be called intangibles,
which is you and me,
and create these extraordinary risks for organizations.
Even organizations that have quote unquote assets.
Those assets become liabilities
because you and I change a platform overnight, right?
We decide we don't wanna have that asset anymore
and all of a sudden
those physical assets become liabilities.
So these new insights that are being generated
by massive social media pipes and now soon, like,
human engagement pipes like Glassdoor.com,
you're gonna see us grab and take that stuff,
not just Bureau of Labor statistics,
and being able to basically match it up
which is what we're doing, to give new insights
to risk-based metrics for organizations and investors.
Huge issues, and same for governments.
I mean, right now government risk is the ability to pay.
Well, you know, what happens
if Trump decides to do something we don't like,
it's gonna create some economic risks
that are knowable from the language that we're using.
So that stuff's all available today.
- You know, you talked just briefly
about the big shakeup over Blackrock
and how they're shifting over to less human involvement
in investing and more AI approaches.
I'm curious about, do you see any drawbacks
from removing people from these investment strategy roles?
- So you know my comment on that,
I don't think humans will be removed.
I think they'll be changed.
Just like I think farmers and mechanics have changed.
- Gotcha.
- Those people had to evolve in the world.
I don't know what the future looks like
in the financial services world,
I know they lead the rest of the world
in terms of industries.
Not necessarily believe, they don't change themselves,
which is the funniest thing.
They change the products they offer to us,
but they don't change their business model,
which is quite ridiculous, right?
They're still selling financial services, right?
Insurance services are the same thing, right?
The whole financial services industry is broken,
but they have these amazing capabilities
for product-centric capabilities to do something different.
So the question is, how will their industries change
to begin to look more like realtime, Alexa-driven,
Siri-driven, Google Home-driven whatever I want
when I want stuff?
I mean, it's gonna be an interesting question.
- Yeah.
I'm curious about, for those financial companies
that have not adopted AI,
maybe they want to,
I'm kind of curious about what are some initial challenges
you've seen for companies that begin to adopt AI
and maybe some advice you could give them
as they move in that direction?
- Well, have you seen the boards
of most financial services firms, do you have any idea
what most of them look like?
They look like me, right?
Old guys, old white guys, right?
The statistics are clear,
more than 90 percent of them are men and over age 60, 63.
Can't believe I'm 63, but the point is
they need reverse mentoring, right?
They need to be mentored by my kids who, you know,
understand these constructs and they live it every day.
It's not just about social media anymore
being reverse mentored, what is Twitter and what is a tweet?
What is Facebook and how do you do Facebook Live?
That was last generation a decade ago.
Now these are the new technologies
that sit on top of these experiences.
They need reverse mentoring
so that they can bring into their board
not just social media people like Starbucks did,
they need to bring into their board young AI data scientists
so that every board has as a part of its journey
a daily dialogue, because they can come up to speed
on this conversation and they could be part of it,
not resistant to its reality.
So I really believe in reverse mentoring
for these boards and the infusion of new competencies.
And the same into management teams.
- You know, when I was reading your article,
you wrote something
that I would love for you to elaborate on.
You said that tomorrow's elite consultants
already sit on your wrist, and you said Siri,
on your kitchen counter with Alexa,
or in your living room, Google Home.
I'm wondering if you could elaborate on that.
- Sure.
So you think about it, you know,
Amazon purchases Whole Foods at a fairly reasonable price
to get access to more customers and to sell more food,
right, it's a big business.
So the consulting industry globally is massive, right?
It's in the hundreds of billions if not trillion dollars.
And I'm talking about all services, right?
Now you know they're sitting on data
regarding customer data, marketing data,
data analytics on product data, right?
You just know they're sitting on all this data.
All the data that consultants have to work really hard,
they're called bespoke,
which is like they're the old tailors of London,
the bespoke tailors, thinking that they're basically,
you know, somehow immune from this movement
of data-driven decisions, which is outcome driven decisions
like in the healthcare industry.
My view is, since we're already doing it,
it's already within Amazon,
not that they're picking it off now or Apple's
or Google's or Microsoft's capability,
to displace their services partners, right?
Now they don't do that yet
because they have other more attractive low-hanging fruit.
But they're not stupid, right?
As they, just like Apple did
when it put these funny looking devices in our hands, right,
these music things, they now provide
a lot more than music, right?
They provide almost everything to me,
from education to healthcare.
You can do a pinprick here and get your, you know,
your blood type and these are biometric devices.
It's only a matter of time til the big five say,
hey, would you like some advice?
So my view is these guys, these five big,
I call them the fab five, are just sitting and praying,
ready for you know, when they think this is,
the services industry is what they're going after next.
And they're in our bedrooms, they're in our kitchens,
they're in our living rooms, they're in my office.
- Exactly.
- They're right here.
I don't have to call McKinsey, they're right in here.
I don't have to call.
Hey Alexa, Hey Siri, you know, give me an in.
A lot of things for a lot less hassle.
- I think about all the data when I'm walking around,
when I go hiking with my family
and I'm using apps to track where I'm at on the trail,
just the amount of data
going into the health section of my Apple product
and data that's being tracked all around me,
so elevation gains, etc.
So it's just fascinating to think about, yeah,
our phones are massive sensors
collecting so much data about us.
- Right, and that's about us,
which is only part of the story about us, right,
which is every one of us.
And they're watching every one of us, I think,
I think in numbers I've gotta come in small,
something like 2,000 times a day, right, you know,
I'm being hit on my phone, right?
Which is a lot of times.
McKinsey's not hitting me 2,000 times a day,
which is my alumni firm, they're not even hitting me at all.
They don't even know what I'm doing right now
when I'm talking to you.
So if you think about it,
it's not to suggest that bespoke consulting firms go away,
it's just that, it's just like the Google world will just,
we're gonna organize, we're gonna make stuff.
I mean, Google's taught us this.
I want it when I want it just as I want it, right here,
right now in my home.
Amazon delivers it within 24 hours.
They have their widgets over within an hour at my house.
And the thing about, it wasn't when I grew up,
it used to take a week or two to get stock to my house
and then to return it, right?
Now you know, gosh, I don't even know
what a stock looks like.
- Well Barry, I wanna thank you.
We've just come upon the hour
and I wanna thank you so much
for you being part of Data Talk,
for sharing your insights with our community.
I have certainly learned a lot from you
and I can't wait to re listen to this broadcast again.
I wanna let everyone know
that you can learn more about Barry Libert
over at OpenMatters.com, I have the URL on the screen.
Barry, is there anything else you'd like to share
about how people can get in contact with you?
- Sure.
You can find me at my Twitter handle,
it's @BarryLibert, B-A-R-R-Y-L-I-B-E-R-T.
My personal website is BarryLibert.com,
and we're a machine learning data science company
that examines the economics of the world.
- That's awesome.
Thank you so much Barry.
Barry, for those viewers who are new to Data Talk,
you can find out more
about our weekly data science video chats
by going to Experion.com/datatalk and our next chat
will be with Dr. Alberto Cairo
as he'll share with us about misleading data
and how to avoid creating the wrong data visualizations.
You can find more about that
in the about section of this video.
Thank you all for watching today's chat
and we'll see you all next week.
Barry, thank you again for sharing your insights
with our community.
- Thanks for having me today, I really appreciate it.
- Thank you, take care.
- Bye bye.