The atmosphere here is fantastic, isn't it?
I just genuinely get a sense of this.
A collective goodwill to do something.
I think what I feel this time, I've had lots of feedback from previous Davos events.
What I get a sense of is it's quite pragmatic.
There's lots of action orientated and clearly
now the world is observing as to what's going to happen next.
But I hear there's lot
I've been in lots of great conversations
and lots of exchange of information and ideas,
and it is such a beautiful place here in the Swiss mountains.
One of the things that's scary is we're
seeing firsthand the impacts of climate here,
climate change, because there's not as much snow anymore.
And so people are very aware of this here in Davos.
And there is a tremendous concern about the existential challenges we're facing.
And it definitely feels real.
I think this year, more than any other year, from all the feedback
I've had and in all the conversations I've been in.
So one of the things I find absolutely surprising is
more data is going to be created
in the next two years than all human history combined.
And so how do we use this data?
And we're seeing companies use AI and machine learning
to better predict what their customers are going to want.
You know, predictive maintenance and analytics and data science.
These all become very important tools in bettering the customer experience.
No, absolutely.
You're right.
And, you know, people often refer to data as the new gold.
But actually it's you're right.
You know,
as we stand here, we can say this is lots of data spewing from what's emerging
that we're saying our devices, all that kind of great stuff.
But it's what do you do with it.
And I think where the insurance and reinsurance industry
have a really big role to play is to use that data to create solutions.
Services to help resilience.
So we can give, you know, from our organization's perspective,
give real insights into
where you know, what's going
to happen to your supply chain, what's your risk to national catastrophes.
And I think that's what we need to use the data for.
And we're doing it now.
So it's not something that's going to happen in the future.
This is the here and now.
I like this example.
I haven't seen it done, but real time pricing of insurance.
So, you know, your 16 year old son borrows your Tesla
and trumps it on the highway doing 120 miles an hour.
And in real time, the voice comes in and says, if you keep driving for
one more minute, we're going to increase your premiums £2,000 next year.
And if you drive for 2 minutes, it's going to be $10,000.
So especially, I mean, today already there are insurances are offered.
So I think people often face to them as a black box
that sits in the car but has your driving data
and based on your risk profile, you can dictate your premium.
It's not as advanced as the, you know,
telling the parents that they need sort out the kids driving
hasn't got that far yet, but the using the data to understand
the risk and price risk is already like today in many countries.
So this is a great example for driving.
But in in industrial setting we call it predictive maintenance.
I was at a train Italia launch of a 300 kilometer an hour train
where they've put a thousand points of presence measuring
different pieces of equipment and it yells out, Hey, we're vibrating too much.
We're going to break down within the next week, replace me tonight
rather than wait until it breaks down and the whole train schedule
is thrown out of whack.
So this is actually creates better outcomes at a lower cost.
They're saving 10% of their maintenance budget, which is €2 billion.
So sorry, $2 billion, €1.4 billion.
So it's just incredible how do we get better performance for a lower cost?
And I think that data plays a whole host of reasons.
It's about better solutions, better analytics and better insights,
but it's also about the customer service that you have.
So if you can think about an end to end consumer journey today, already
you can see where is the customer dropping out and why they're dropping out.
And then from a consumer's perspective,
you can put in interventions to create a better buying experience
because insurance is not something
that someone wakes up in the morning just, yeah, let's go and buy it.
So the easier the process is,
the more understandable it is, the easier it becomes for the consumer.
And as a result, it will drive down the cost.
Absolutely.
And there is a PNC company
out of the US out of New York City called Lemonade.
You can only apply for it on your smartphone.
And for many Gen Zs or millennials, younger millennials,
all they have that they want to insure is their laptop, their scooter,
you know, and their smartphone so they can bind a new policy.
In 3 minutes, you answer a whole bunch of questions.
It runs against fraud algorithms and so on.
And they have the fastest claims settlement record
in the world of 3 seconds.
Yep, I've heard of that.
So, you know, it's 18 fraud algorithms and they hope to solve
80% of their claims in basically instantly.
Exactly.
So this strips out costs so you get better,
better outcomes, better customer service at a lower price.
This is a reality.
And that's why
when you think about the usage of data, I think it's a thing of the future.
But that example, there's an example.
You know, we have an automated underwriting engine.
It's known in the market as Magnum.
We have three different versions of it which sits in our platforms.
We provide it to our clients that does automated underwriting at point of sale.
Fantastic!
So it's here that's I think that's the key thing.
So in the current way the partners work with each other,
creating value in an ecosystem is incredibly important,
but there are some preconditions that you have to get right.
So first of all, is a single organization on their own.
It's really hard to create that end to end value.
So you have to learn how to collaborate
in an efficient way, but in a productive way as well.
And that's often starts with having aligned interests.
I think many times where collaborations and ecosystems fail is because partners
don't know their role in that value chain and they don't know how to win win.
And it's always people come out thinking someone's won and someone's lost.
I think that has to change.
And one of the good things I've picked up around
from my conversations here has been a lot of people are taught how to negotiate.
You go to business school, you're taught how to negotiate,
how many people are taught to collaborate?
- Yes! - And I think that's the value of an ecosystem.
And it's specifically important in the insurance world
as much as in any ecosystem that you have.
Pravina, what made me think what the example was.
Right now, Uber
is worth more than every taxicab company in North America added together.
Yeah.
And so I've talked to CEOs of taxicab companies
and they say to me, Jim, we're developing, you know, an app on our smartphone.
We're spending a quarter million dollars.
And I think like, good for you, you know, but I live in Toronto
and I'm not going to download 20 Toronto
taxi apps and keep my data in each one with my fat thumbs.
Right? They don't understand that.
They have to think at a higher level, a meta level.
So if all taxicab companies globally developed a single app,
call it like Global Taxi, I'm great marketer, but
you know, I download it, but instead they're all spending
a quarter million to develop something I'll never use.
So collaboration is key to survival and thriving,
but it also requires a mental agility in thinking differently.
Yeah, but in that example there's a fear, and you see this in many ecosystems,
and in that specific example, each cab firm is probably worried if I share
my customer base, if I share my data, are they going to win?
Instead, there needs to be;
How can we all share it for the greater good so that we get an equal share
and a greater scale?
Because that's one route to scalability.
Absolutely.
And the benefit another one is that, you know,
they only share in 1/20000 of the development cost of the app.
But I would download that and I transact here in Davos
and in Shenzhen and in Rome,
but I have never downloaded a single taxi app.
And so whether you, you know, collaboration and cooperation
we think of within our current ecosystem, but there's this notion of coompetition
for the sake of the industry, you may have to collaborate with somebody.
You've perceived some company as a competitor.
Absolutely. And and create win wins.
The other great example I've come across and sometimes when people think about
ecosystems, I think that this flash value chain actually happens at the micro level.
So where startups or new entrants in the market,
they all need a data officer or they need a security officer,
but no one can afford one.
So a group of companies come together and share.
And then that's very simple,
but that's a real simple example of collaboration that is productive.
We're seeing that, you know, we know about NetJets
and fractional ownership of jets, but we're seeing fractional CXOs.
So CFO for a day once a week or once a month
for a small startup they can't afford or don't even need a CFO.
Exactly. For the entire time.
So we're seeing talent shift to on demand talent.
It's a very different paradigm.
I think it's a great way forward.