Hello, and welcome to this Section 1.8,
which is in Part C of Module 1 of Digital Finance.
It's very, very brief and then we'll move on to Section 1.9.
We look at the Current use of FinTech
by Accountanting and Finance Professionals.
And the examples given include like the pay later,
area which I'm going to call very similar
to a credit card function.
Open banking, it's only briefly introduced two lines now,
but covered in a later module,
mobile POS, cross-border payments,
and no-checkout stores and Amazon sort of at the forefront
of this type of activity where you walk into the shop,
you pick stuff off-the-shelf
and you can walk straight out the door.
You don't have to scan it, you don't have to check out,
that's all taken care of by itself.
So, that's some FinTech available
Accounting and Finance Professionals.
So, the question is,
what are the accountants doing in this space?
What do they need to know?
And then interestingly,
the heading here says Innovation incentives
in Financial Services.
But I think that a better word might be opportunities
and areas that need to be done well.
So, one is, generating profitability.
To make profit you need products and services
that customers want.
So, that is an incentive to innovate.
The rest of them are opportunities.
So, basic necessity.
People need access to banking and fairness.
So, the unbanked need access to bank.
So, there's two key themes,
which I'm going to say are opportunities
for organisations in FinTech to innovate?
The other thing we have as an opportunity
is we have these old legacy systems
that are often clunky and inefficient.
So, if we can streamline them, improve them, replace them,
especially with the evolving preferences of millennials
and younger people coming through who want their services
delivered in new and better and different ways,
then that's great.
In the old days, people would ring up their insurance
and organise your insurance and that might be for years
then they just renew the policy once a year.
But nowadays people can take out daily insurance,
weekly, monthly, you can switch your power company each day
depending on the cheapest rate.
So, this hyper informed lots of data,
quick movement is much, much different
to when you would call the insurer,
you'd have to speak and they'd have to capture
all your information over the phone
and it would take quite a while.
So, there was a transaction time and cost involved
that no longer exists.
And then, regulation.
There's a lot of regulations in place
that can stifle innovation,
but sometimes regulation can create innovation by saying,
how can we do this regulation section quickly and easily
if we have to verify things?
We can automate these processes.
So, that was a very quick tour of Section 1.8.
It was only, I think a page or two long.
Now we get to Section 1.9,
which is Innovation thinking in FinTech.
So, some FinTech areas in relation to Wealth Management.
We'll explore a few key areas.
So, Wealth Management, there's going to market
and onboarding, that's a fancy name for bringing new clients
onto your system.
So, KYC is this idea of Know Your Customer
and you have to find out about them
because you can't be allowing criminals onto your system
without putting in checks and balances.
That stops the AML,
well, stops the AML, the money laundering.
So, there's Anti Money Laundering monitoring
that needs to take place.
And if you can do this in a paperless way,
quickly and efficiently,
that's one of those regulation innovation areas.
You've got to do it.
So, do it the cheapest and most efficient way possible.
And then distribution.
So, giving roboadvice,
so, pre-programmed advice and good data analytics
and automating more risk.
Interestingly, it talks about,
e-trade and all of these share brokerages
which are quicker and faster,
now, one of the benefits in the old days
of calling a broker was they would only give you advice
and wisdom and you would have money to invest,
but you would take your time.
Now you can trade in seconds
without any guidance or information.
And it's a little bit of a game you hear
about the trading that's happening on Robinhood.
You hear about the cryptocurrency
and all these millennials working with that.
Just because it's quicker and faster and cheaper
doesn't mean it's more valuable to people.
And there's an interesting Super Bowl ad by E-Trade,
for example, you've got kids,
it's a bit like gambling, they make it fun.
You can get wealthy just by doing this all.
If it was that easy to get wealthy, we would all do it.
So, we have to be a little bit careful there.
Then in the payments realm,
Airwallex has given us a good example
that talks about that virtual cards,
and they have these ability to just pay.
You can load up your nine or 10 currencies
on your card and then pay.
And this makes things much, much speeder.
If you've ever had to travel for work,
no one's probably doing that with COVID at the moment,
but if you go overseas into multiple countries,
there used to be a lot of transaction.
(chuckles)
If you remember the olden days using travellers checks,
but carrying different currencies
versus loading them up on a card is very different.
Airwallex, though interestingly,
they went down the paperless card, the virtual card,
but they have actually moved
into the virtual card realm as well.
So, pretty well from the 31st of July this year.
So, people get these cards
and they can use them and purchase,
and it tracks all of their purchases quickly and easily.
And that's great data for accountants.
So, the next one is Financial Markets.
And the first example given is P2P lenders.
So, this is disintermediation.
And I mentioned this in an earlier webinar,
where instead of lenders having to give money to the banks
and the banks having to find the borrowers
and these extra costs and time,
P2P go straight to each other.
So, examples of this given include,
RateSetter and MoneyPlace.
So, you go to there or ThinCats
and you put in what you want to borrow
and see the bottom right of the screen,
25,000 for five years.
And you can obtain this funding much, much faster
through P2P lending than ever before.
So, that's one example, FUNDTAP, INDIEGOGO.
So, all of a sudden we're moving into SME Finance
and an example.
This is FUNDTAP, a New Zealand organisation.
So, inventory financing create your free account,
no paper-works are quick, easy, efficient,
and then you choose invoices
and they effectively give you money for those invoices.
And then when the invoice's are paid,
they'll collect that fund
and they'll clip the ticket at the end.
So, you can have money within hours,
inventory financing used to take days to organise.
And then once it was organised with a supplier like FUNDTAP,
you would have to fill in forms every time,
and it was complicated.
There was a cost attached to transaction time and costs.
So, it's speeding that up in a phenomenal way.
I mean, INDIEGOGO, another one,
getting funding for actual projects
or products that you want to launch.
So, that's a really interesting one.
So, you've got some movies being made.
There's "The Red River Expressway Killer" horror movie
is one example of trying to raise funding.
It's a bit like Kickstarter, but more of a business item,
an Ausker, these multifunctional kitchen utensils.
So, they're raising a bunch of money
and it looks like many, many people
want very cool kitchen utensils
because they only wanted $10,000
and they've raised nearly $34,000.
So, this is how people are funding,
not just their businesses, but operational activities.
The next section is APIs/Cloud Accounting/Open Accounting.
And the Xero app marketplace is a really good example.
It's a bit like going to the app store
for Google or Android,
but this is for Xero and accounting plugins.
So, you can plug in decks, prepare,
and you can plug and sift
or spotlight reporting or expert a2X,
all of these different things that may help you
run your business much faster than before.
And then there's Neobanking.
Now I'm a little bit old school.
I'm not as convinced by fancy words.
So, Neobanking kind of sounds like new banking,
which sounds a lot like old banking,
but it's just describing companies that have set themselves
up as banks.
So, I don't think that's that exciting,
but one of the things they do
is because they're starting from scratch,
they don't have to worry about all those branches
in the old system.
They don't have to worry about computer programmes
that were written in the 1970s and 1980s,
those legacy systems.
So, they can be built on modern platforms,
they can be built in the cloud.
They can be built much faster, more efficiently
'cause they don't have to update the old ways.
You don't need to retrain all those old staff.
So, Atom, UK based.
One, is an example.
They make their websites look very fresh and exciting,
but a bank is still a bank.
Then we move on to Emerging FinTech
and we've got this idea of Edge Computing.
Now, the study guide doesn't really go into much detail.
Literally, I don't know a paragraph,
but the concept is normally the internet of things,
the devices, so, if you have a smoke detector,
if you have a doorbell at the front of your house,
if you have light switches,
all of these things are being internet enabled,
capturing all this data.
So, you can get home
and the lights will turn on automatically
when you drive down the driveway,
for example, when you really think about it,
wow, it doesn't really rock your world,
but that's what's available.
These internet of things.
These devices are normally just create data,
but using these to actually do some of the processing,
more efficient, more reliable, faster.
So, pushing computing to the edge.
In the old days,
we used to have everything on a mainframe,
then we pushed everything that was called client server.
And then we pushed everything onto the computer itself,
which is what you would experience with desktop computing.
Then we've sort of moved back to what's called the cloud,
which interestingly,
is a bit like going back to the mainframe,
going back to the server
and Edge Computing is really the next iteration of that.
So, do a little bit of Google reading if you need to,
or some videos, but you hear more about that in the future.
Other things we'll cover a later stage
'cause DeFi, decentralised finance.
I'm not, why we have to do these crazy acronyms,
but that's using blockchain and the AI Robo Advice
are emerging FinTech.
But of course there's roadblocks, regulations,
stymie innovation.
There's a lack of creativity, black box algorithms.
This is what really fascinates me.
So, when people create algorithms.
So, for example,
a facial recognition software is much,
it got trained on a lot of white faces,
so it's different with Asian and black faces.
Lack of profitability and sustainability.
As an accountant, this is the one I see all the time.
And I've got a reference here to Uber,
which is not digital finance,
but it's still a digital realm.
It's still transformation using digital,
got rid of the taxi industry, destroyed it,
but didn't make any money.
So, here's an Uber in 2020, they lost nearly $7 billion,
but that's good because the previous year
they lost $8.5 billion.
Here's an organisation
that loses billions every single year.
So yes, it's transformed the taxi industry,
but it doesn't know how to make a profit.
And there are a huge number
of digital finance organisations.
Xero is accounting organisation for example,
if you adjust its accounts,
Xero does an interesting thing,
it takes it's labour costs and then it capitalises them.
So, you pay someone's salary, normally that's an expense,
they call it an asset and then that reduces their expenses.
And then they call, they have a small profit as a result.
But if you look at their true operational performance,
Xero generally makes a loss every year.
So, great product,
millions of subscribers, everyone loves it,
but it doesn't actually make money.
So, in the longterm,
that's going to become a problem at some point,
if you don't make money
for 10 years and then 20 years, and then 30 years,
sooner or later, people get a little bit tired of that.
So, talking about bias in a little bit more detail
because this digital realm
is great and full of opportunity, but full of problems too.
So, some research in 2019 in the United States,
which showed that the algorithms that have been created,
and this is quite significant,
we're less likely to refer black people and white people
who are equally sick.
So, two identical people
with the same illnesses and problems,
but one white, one black
and the white person gets a different referral programme.
And now how did this happen?
Well, we don't know
because the algorithms aren't available
to be observed and monitored.
So, these things are incredibly frustrating.
Now, interestingly,
one area that has actually helped black men
compared to white men
because they were actually discriminated against,
but it saved their lives.
So, in the past,
there was a lot of over-prescription
by doctors of opioids, painkillers in the United States.
Now people are overdosing on these like in huge numbers,
but interestingly,
more white people than black people are dying of this.
And the reason or one of the reasons why,
is that people who die of opioid addiction
start off with painkillers.
They get given them by the doctors
and then they get addicted
and then they go down this pathway.
But a lot of black people were not being given painkillers.
They were not prescribed to the same level of pain.
White people got painkillers and black people didn't.
Now, doctors don't deliberately do this,
but this is an inherent bias that we have
that we didn't even know about.
And what's happened is,
because they didn't get prescribed
the opioids in the first place, they didn't get as addicted
and many, many, few of them died,
which is an extraordinary weird outcome.
But I emphasise this point because when we create algorithms
and we sift through the data and make decisions,
these biases come up, we don't know about them.
So, you can't say,
"Oh, no, I'm not racist, or I'm not sexist."
They happen.
And so unless we find ways of interrogating these algorithms
and making sure they are valid,
many problems are going to arise.
So, bringing us to the end of this section of the module,
you'll see that the study guide
refers to AirWallex quite a lot
and then it quotes from Jack Zhang who the CEO of this.
There's going to be a lot more interesting advisory role.
So, what does this mean for accountants
well all of this FinTech's coming along?
And I really liked this.
He says, "The core skill is not to be a tech head,
"it's not to be able to code,
"it's being able to solve-problems,"
which means understanding your customer,
understanding your products and services,
helping people and their needs and their stakeholders.
So, if you've got a bit of an engineering
or science background, or you get some courses,
yes, it's going to be helpful,
but like he says, it's not about being able to write code.
The core skill set looking for is the ability
to solve complicated problems,
then use the technology to deliver that.
And I like this bit,
you're not supposed to deliver the Tech yourself,
that's the role of a software engineer.
Your job is to take the abstract
to get a complicated problem
and turn it into a simple solution
then the engineers help you.
So, that brings us to the end of Part C of Module 1,
the three objectives are there,
15 marks of your exam roughly,
20% of your study time across this module
and checking out these objectives.
So, I hope you found that tour useful. Keep on studying
and dive into Part D.
So, thanks.