Name: Inscribe at Money20/20 USA 2023 – Enabling instant trust for financial services
Uploaded: 2023-12-08T14:49:47.305Z
Duration: 831.3

03-Inscribe  v3.mp4

03-Inscribe  v3.vtt

ENGLISH

{{00:00:04}}
Hi, I'm Heather Sugg here at Money
2020 USA reporting for Fintech Futures.

{{00:00:10}}
I am pleased to say that we have
Ronan from Inscribe visiting with us

{{00:00:14}}
today, and we are going to talk about
fighting the good fight against fraud.

{{00:00:19}}
So Ronan, thanks for joining us.

{{00:00:21}}
Thanks for having me.

{{00:00:21}}
Let's start out with just
talking about Inscribe.

{{00:00:24}}
What inspired you to found the company
and tell us a little bit about yourself.

{{00:00:28}}
Awesome.

{{00:00:28}}
Yeah, so I'm Ronan, CEO
and co founder of Inscribe.

{{00:00:31}}
And, yeah, we I founded the company with
my co founder Connor, who's also my twin.

{{00:00:36}}
And it was actually an experience
he had at a bank back in Ireland

{{00:00:40}}
which catalyzed our, journey.

{{00:00:42}}
And he was working for a consulting
company, and a consulting company

{{00:00:46}}
was brought in to help them with an
automation project for automating review

{{00:00:50}}
of documentation that was submitted for
mortgage applications and digitizing

{{00:00:55}}
historical records from 30 years.

{{00:00:57}}
And it was a very difficult
project ultimately.

{{00:01:02}}
Experienced many, challenges, and
this is the, source of where we found

{{00:01:07}}
and discovered the problem that, hey,
in back office operations at banks,

{{00:01:10}}
there's a lot of manual work to be
done, and we primarily just complained

{{00:01:15}}
about the problem at that time, but a
year later, we spoke to FinTechs out

{{00:01:20}}
in the Bay Area, and when we learned
that they, too, had a similar problem

{{00:01:23}}
with automating back office tasks we
knew there was an opportunity here,

{{00:01:27}}
because if these tech forward FinTechs
also couldn't solve the problem

{{00:01:31}}
despite having the technical skills.

{{00:01:33}}
We knew that there's something
funny and unique going on here,

{{00:01:35}}
and that was our unique insight.

{{00:01:37}}
But yeah also, the benefit of these
FinTechs also having a problem was that

{{00:01:42}}
they were a very good collaboration
partner to work with in the early days

{{00:01:45}}
to, to build a product to get it up to
a point where it can achieve superhuman

{{00:01:51}}
accuracy and then start helping more
and more types of companies after that.

{{00:01:55}}
And so yeah we got started.

{{00:01:59}}
In 2018, working on that problem,
and since then, we've been detecting

{{00:02:03}}
more and more fraud and selling to
more and more types of businesses.

{{00:02:06}}
Tell me about your mission
and your grand scope to help.

{{00:02:09}}
Yeah, so our mission at
Inscribe is to enable instant

{{00:02:12}}
trust for financial services.

{{00:02:14}}
And ultimately, this stems from the,
huge shift that's happening in the

{{00:02:18}}
world right now where, and probably
for the past number of years even,

{{00:02:21}}
but it's a very large shift, is
the move to online especially for

{{00:02:25}}
very traditional banking services.

{{00:02:28}}
A decade ago or more.

{{00:02:29}}
You would have walked into your local
bank branch to avail of a loan or even

{{00:02:35}}
just to set up a new bank account.

{{00:02:37}}
But now, these banks are trying to
push you online, and for good reason,

{{00:02:41}}
lots of great benefits of that.

{{00:02:43}}
And also, FinTechs are starting
out online from day one.

{{00:02:46}}
But when you move online, the
whole trust equation changes.

{{00:02:50}}
Whereas previously you would have
walked into a bank and the bank manager

{{00:02:54}}
would have understood who you are,
where you lived, where you worked.

{{00:02:57}}
Perhaps even knew your family.

{{00:02:59}}
That trust connection no longer, or
oftentimes no longer, exists when you

{{00:03:03}}
do business online through digital
channels and that trust needs to be

{{00:03:07}}
re established from the ground up.

{{00:03:08}}
And our mission is to make
that instant just as it is when

{{00:03:13}}
you're doing business in person.

{{00:03:15}}
And to do that there's a lot of parts of
that challenge that need to be solved.

{{00:03:19}}
And so at Inscribe we're
tackling those one by one.

{{00:03:22}}
And ultimately what this means in
the long term is good customers.

{{00:03:28}}
Particularly customers who
wouldn't necessarily have access

{{00:03:32}}
to financial services in the same
way as everybody else gets access.

{{00:03:35}}
But also, bad customers also stay out in
terms of fraudsters and customers that

{{00:03:40}}
might lead to credit losses as well.

{{00:03:43}}
Ultimately there's a huge amount
of benefit for individuals and

{{00:03:46}}
businesses and also to the financial
services companies themselves.

{{00:03:52}}
With what you're seeing you
said you had 70 customers?

{{00:03:57}}
I'll ask this again.

{{00:03:58}}
Okay.

{{00:03:58}}


{{00:04:00}}
With what you're seeing with your
70 customers across the scope,

{{00:04:03}}
what major trends should both
banks and lenders be watching for?

{{00:04:09}}
Yeah, I think for me,
there's a couple of trends.

{{00:04:11}}
One of the big ones is just the increase
and pervasiveness of first party fraud.

{{00:04:16}}
Oftentimes if the person applying
to you is who they say they are,

{{00:04:19}}
oftentimes all the information about
how much they earn and where they

{{00:04:22}}
work often isn't necessarily true.

{{00:04:24}}
And if it's a business,
how much revenue they have.

{{00:04:26}}
And so the increasing and Placing
diligence on customers you already do

{{00:04:31}}
business with but also just extra mindful
at the application process that identity

{{00:04:36}}
isn't the only data point you need to
verify things like income and revenue

{{00:04:39}}
to get access to a credit product that
wouldn't otherwise get approved for,

{{00:04:42}}
just increasing the amount or getting
a better rate these are types of risks

{{00:04:48}}
that we see continue to increase.

{{00:04:51}}
Secondly, I think the pervasiveness of the
use of social media to share techniques

{{00:04:55}}
and templates online are fueling a whole
new wave of fraudsters, and I think a lot

{{00:05:01}}
of this is probably spurred on from the
pandemic and the PPP loan scheme where

{{00:05:05}}
fraud became accessible in a way for a lot
of new fraudsters and we're still dealing

{{00:05:10}}
with the ramifications of that, and so
what we typically see are instruction

{{00:05:14}}
sets on social media platforms of how
to commit fraud to a particular, with a

{{00:05:18}}
particular type of FinTech or a particular
FinTech itself and these targeted attacks

{{00:05:25}}
from large numbers of people are a second
trend and finally I think the very large

{{00:05:32}}
trend of artificial intelligence and the
advancements that have been made here

{{00:05:35}}
in the past number of, quarters I think
banks and fintechs are trying to grapple

{{00:05:40}}
with what this means for them in terms
of how it can help them, but also the,

{{00:05:44}}
any kind of threats it poses as well.

{{00:05:47}}
I think we're still very early in
the adoption Here but there's a

{{00:05:53}}
very large eagerness and there's
a ton of use cases as well.

{{00:05:56}}
So I think financial services
will be transformed by this.

{{00:05:58}}
And so I'm very excited
to see how this unfolds.

{{00:06:02}}
I want to dig deeper into
that because you're right.

{{00:06:04}}
The fraudsters are becoming more and more
aggressive and they're not hiding in as

{{00:06:10}}
much anymore, which helps them proliferate
their ideas and they're using AI and ML.

{{00:06:15}}
And so how is financial services
using AI and ML to combat this

{{00:06:20}}
and where are our strengths?

{{00:06:22}}
Yeah.

{{00:06:23}}
So I think machine learning and
artificial intelligence fraud

{{00:06:27}}
detection is one of the best use cases.

{{00:06:29}}
It's you need to look at a large
amount of data and identify the

{{00:06:33}}
patterns and have a very good memory.

{{00:06:35}}
I know humans are pretty good at this,
but machines and machine learning are

{{00:06:39}}
even better and significantly better.

{{00:06:41}}
And so when it comes to AI and machine
learning, I think fraud detection is

{{00:06:45}}
one of the best applications of that.

{{00:06:47}}
But also it also helps a lot of
operational work that, Humans would

{{00:06:53}}
are good at, but it's just not
necessarily the best use of time.

{{00:06:56}}
For example classifying certain
information as a particular type of

{{00:06:59}}
information, or extracting information
from documents, or categorizing things.

{{00:07:04}}
These are things which, you know
machines are just extremely good at,

{{00:07:08}}
extremely efficient at, but also types
of tasks which humans don't like doing.

{{00:07:13}}
It's extremely mundane, and it
doesn't tap into their creative

{{00:07:16}}
and problem solving potential.

{{00:07:18}}
And yeah, I think You know, across those
two domains, there's a huge amount of

{{00:07:24}}
benefit and value to be added there.

{{00:07:27}}
Specifically at Inscribe,
what are you doing now to help

{{00:07:30}}
fight that fight against fraud?

{{00:07:31}}
What are some real life
use cases we can see?

{{00:07:34}}
Yeah at Inscribe we've
two primary use cases.

{{00:07:38}}
Account opening and then underwriting.

{{00:07:40}}
On the account opening side, we help
companies detect fraud that occurs when

{{00:07:44}}
Folks are trying to prove who they are,
where they live, and what businesses

{{00:07:48}}
they're associated with, and do they
have permission to make a certain

{{00:07:51}}
decision on behalf of that business.

{{00:07:53}}
And oftentimes what we see here are folks
tampering with an article's incorporation,

{{00:07:58}}
or SS4 documents to prove tax IDs,
or utility bills to prove addresses.

{{00:08:03}}
These types of data points are often
manipulated, and across our customer base

{{00:08:08}}
we see a 5 percent fraud rate and flag
rate of these types of manipulations.

{{00:08:13}}
And so or Document Fraud Detection
Product or Fraud Intelligence is

{{00:08:19}}
how we help customers deter this
and detect this type of fraud.

{{00:08:23}}
And then second use case is
on the underwriting side.

{{00:08:25}}
Once you've onboarded a customer
and you need to underwrite their

{{00:08:29}}
ability to repay a loan either
on a personal or business basis.

{{00:08:33}}
What we often see is a manipulation
of income or revenue details on

{{00:08:37}}
bank statements or tax forms, etc.

{{00:08:39}}
And we also help our customers
detect fraud on these.

{{00:08:42}}
Documents as well, and in particular,
like tampering and reusing of the

{{00:08:46}}
same documents and templates, etc.

{{00:08:49}}
And then in recent months, we've
been solving more and more credit

{{00:08:54}}
type problems as well with our
credit intelligence products.

{{00:08:57}}
Once you know you can trust a document,
the next question is, okay, how

{{00:09:01}}
much business should I do with them?

{{00:09:02}}
And this requires you to understand
the transactions, let's say,

{{00:09:05}}
in a bank statement or fed
from an open banking service.

{{00:09:09}}
And we've recently been helping
customers in that area as well, in

{{00:09:13}}
terms of parsing the transactions
from a bank statement, categorizing

{{00:09:16}}
them, and then providing insights on
that, so our customers can use those

{{00:09:20}}
insights, funnel them into their credit
models, and make a decision from there.

{{00:09:23}}
So one of the areas that every bank
seems to have a unique way to address

{{00:09:29}}
is the debate between user experience
and not wanting to create any friction

{{00:09:34}}
and having a hard line on fraud,
especially on the onboarding that

{{00:09:37}}
you were just talking about too.

{{00:09:39}}
So what are you seeing there
as that balance comes in?

{{00:09:43}}
Yeah, it's a very tricky problem and
one in which has always existed between

{{00:09:49}}
various different teams and functions
at financial services companies.

{{00:09:52}}
Particularly like the risk
team and like the sales team.

{{00:09:55}}
The sales and marketing org want
to grow as fast as possible.

{{00:09:57}}
The risk team want to make sure
that they don't lose any money

{{00:10:00}}
to fraud or credit losses.

{{00:10:01}}
So you need to meet in the middle.

{{00:10:04}}
It is quite tricky.

{{00:10:05}}
And I think for me, it comes
down to understanding where you

{{00:10:11}}
do want to draw that line there.

{{00:10:13}}
And that's like, the minimum level
of trust you need to establish

{{00:10:17}}
to do business with a customer.

{{00:10:19}}
For example, if you detect outright
fraud, or they're a previously confirmed

{{00:10:22}}
fraudster that's the easy case, but
there's a large middle ground and

{{00:10:27}}
gray area where you don't necessarily
have enough signals to outright reject

{{00:10:30}}
them, but you don't have enough signals
to outright accept them, and so they

{{00:10:35}}
operate somewhere in the middle.

{{00:10:36}}
And that's also where a lot of
customers are incorrectly rejected, and

{{00:10:39}}
particularly a lot of good customers
are incorrectly rejected, and that's

{{00:10:43}}
like a very large problem in terms of.

{{00:10:46}}
Folks who are underbanked or don't
have the traditional profiles that

{{00:10:49}}
would automatically get accepted.

{{00:10:52}}
And so it's a very tricky problem.

{{00:10:54}}
I think the best thing you can do is just
increase the explainability the, number of

{{00:10:59}}
data points you're checking for and have
auditability and continual improvement.

{{00:11:03}}
And if you do make a mistake, you
learn from it, you reapply and then

{{00:11:06}}
keep on iterating over and over.

{{00:11:08}}
But it's a, constant balance and I even
think in, as economic cycles fluctuate

{{00:11:14}}
this balance between the two changes,
and I think we're, currently operating

{{00:11:18}}
in a world where the appetite for risk
is reduced, and more folks are getting

{{00:11:22}}
rejected more than ever but yeah it'll,
fluctuate as the economy recovers again

{{00:11:28}}
in a couple of years, don't know how
long it'll be, but in the short term

{{00:11:31}}
we, still can't accept it we, still need
to work to improve it, and we like to

{{00:11:35}}
help our customers talk through these
problems and, help them get there.

{{00:11:39}}
That's important.

{{00:11:40}}
Tell me more about your customers.

{{00:11:42}}
Yeah, so we we work with banks Fintechs
and regional credit union banks to help

{{00:11:48}}
them detect fraud and credit losses.

{{00:11:50}}
We work with a lot of the big Fintechs
such as Bluevine, Ramp, and Navin.

{{00:11:56}}
We've been working with them for many
years, helping them detect fraud.

{{00:11:59}}
And there's a huge amount of
benefits from doing this as well.

{{00:12:03}}
It's not just detecting fraud.

{{00:12:04}}
You, we often remove a lot of
operational overhead that would have

{{00:12:08}}
otherwise increased costs, slow down
processing, and then potentially

{{00:12:11}}
even led to lost customers who might
have come to your competitor if

{{00:12:15}}
they didn't get an answer in time.

{{00:12:16}}
And so we've been seeing lots
of great value from those

{{00:12:21}}
deployments for many years now.

{{00:12:24}}
Alright, and then I'm going
to ask you bring this up a

{{00:12:27}}
level for the last question.

{{00:12:29}}
What do you see as a big trend
coming in FinTech for next year?

{{00:12:32}}
What should we be watching for?

{{00:12:34}}
Yeah, for me, I think it's going to be.

{{00:12:37}}
Seeing how companies and financial
services companies in particular

{{00:12:41}}
utilize AI and for the benefit
of individuals and businesses.

{{00:12:45}}
I think there's a lot of exciting
proposals here and ideas, but I

{{00:12:49}}
still think we're very early in
terms of actually seeing them being

{{00:12:53}}
delivered to the end consumer.

{{00:12:55}}
And this will be a, not just a next year
trend, but I think in 2024 we'll start,

{{00:13:00}}
we'll see the Kind of the real beginnings
of it occurring in a kind of a large

{{00:13:05}}
enough way that it becomes noticeable But
then it's going to continue for a decade

{{00:13:08}}
or more to completely see the disruption,
but also benefit of that So I'm gonna be

{{00:13:14}}
eagerly watching out for how companies
adopt it And you know at Inscribe as

{{00:13:19}}
ourselves We're we've been adopting it
and using machine learning and AI for

{{00:13:21}}
many years And what we're doing is trying
to help companies along that journey And

{{00:13:25}}
so we have a lot of exciting stuff that
we're building and that we're looking

{{00:13:29}}
forward to sharing with the world yeah,
I think that would be my number one.

{{00:13:32}}
Yeah, I could see it.

{{00:13:33}}
It's still in its infancy for AI, but it
is growing quickly and fraud is one of

{{00:13:38}}
the easiest and best use cases to see.

{{00:13:41}}
This has been great.

{{00:13:42}}
Thank you for joining us.

{{00:13:43}}
Thanks for having me.

{{00:13:44}}
Enjoy the rest of your
show and we'll talk again.

{{00:13:46}}
Thank you.

Hi, I'm Heather Sugg here at Money
2020 USA reporting for Fintech Futures.

I am pleased to say that we have
Ronan from Inscribe visiting with us

today, and we are going to talk about
fighting the good fight against fraud.

Let's start out with just
talking about Inscribe.

What inspired you to found the company
and tell us a little bit about yourself.

Yeah, so I'm Ronan, CEO
and co founder of Inscribe.

And, yeah, we I founded the company with
my co founder Connor, who's also my twin.

And it was actually an experience
he had at a bank back in Ireland

And he was working for a consulting
company, and a consulting company

was brought in to help them with an
automation project for automating review

of documentation that was submitted for
mortgage applications and digitizing

And it was a very difficult
project ultimately.

Experienced many, challenges, and
this is the, source of where we found

and discovered the problem that, hey,
in back office operations at banks,

there's a lot of manual work to be
done, and we primarily just complained

about the problem at that time, but a
year later, we spoke to FinTechs out

in the Bay Area, and when we learned
that they, too, had a similar problem

with automating back office tasks we
knew there was an opportunity here,

because if these tech forward FinTechs
also couldn't solve the problem

We knew that there's something
funny and unique going on here,

But yeah also, the benefit of these
FinTechs also having a problem was that

they were a very good collaboration
partner to work with in the early days

to, to build a product to get it up to
a point where it can achieve superhuman

accuracy and then start helping more
and more types of companies after that.

In 2018, working on that problem,
and since then, we've been detecting

more and more fraud and selling to
more and more types of businesses.

Tell me about your mission
and your grand scope to help.

Yeah, so our mission at
Inscribe is to enable instant

And ultimately, this stems from the,
huge shift that's happening in the

world right now where, and probably
for the past number of years even,

but it's a very large shift, is
the move to online especially for

You would have walked into your local
bank branch to avail of a loan or even

But now, these banks are trying to
push you online, and for good reason,

And also, FinTechs are starting
out online from day one.

But when you move online, the
whole trust equation changes.

Whereas previously you would have
walked into a bank and the bank manager

would have understood who you are,
where you lived, where you worked.

That trust connection no longer, or
oftentimes no longer, exists when you

do business online through digital
channels and that trust needs to be

And our mission is to make
that instant just as it is when

And to do that there's a lot of parts of
that challenge that need to be solved.

And so at Inscribe we're
tackling those one by one.

And ultimately what this means in
the long term is good customers.

Particularly customers who
wouldn't necessarily have access

to financial services in the same
way as everybody else gets access.

But also, bad customers also stay out in
terms of fraudsters and customers that

Ultimately there's a huge amount
of benefit for individuals and

businesses and also to the financial
services companies themselves.

With what you're seeing you
said you had 70 customers?

With what you're seeing with your
70 customers across the scope,

what major trends should both
banks and lenders be watching for?

Yeah, I think for me,
there's a couple of trends.

One of the big ones is just the increase
and pervasiveness of first party fraud.

Oftentimes if the person applying
to you is who they say they are,

oftentimes all the information about
how much they earn and where they

And if it's a business,
how much revenue they have.

And so the increasing and Placing
diligence on customers you already do

business with but also just extra mindful
at the application process that identity

isn't the only data point you need to
verify things like income and revenue

to get access to a credit product that
wouldn't otherwise get approved for,

just increasing the amount or getting
a better rate these are types of risks

Secondly, I think the pervasiveness of the
use of social media to share techniques

and templates online are fueling a whole
new wave of fraudsters, and I think a lot

of this is probably spurred on from the
pandemic and the PPP loan scheme where

fraud became accessible in a way for a lot
of new fraudsters and we're still dealing

with the ramifications of that, and so
what we typically see are instruction

sets on social media platforms of how
to commit fraud to a particular, with a

particular type of FinTech or a particular
FinTech itself and these targeted attacks

from large numbers of people are a second
trend and finally I think the very large

trend of artificial intelligence and the
advancements that have been made here

in the past number of, quarters I think
banks and fintechs are trying to grapple

with what this means for them in terms
of how it can help them, but also the,

I think we're still very early in
the adoption Here but there's a

very large eagerness and there's
a ton of use cases as well.

So I think financial services
will be transformed by this.

And so I'm very excited
to see how this unfolds.

I want to dig deeper into
that because you're right.

FinTech Futures

Expert Insight

At the Money20/20 USA 2023 conference in Las Vegas, FinTech Futures sat down with Ronan Burke, co-founder and CEO at Inscribe, to discuss how the company is aiming to help financial firms fight fraud and boost trust with their customers when moving their services online.
Watch the video to discover:
The key fraud trends in the industry right now.
How Inscribe’s tech enables businesses to manage risk with fraudulent document detection and intelligent automation tools.
How the industry is looking to fight fire with fire and use AI/ML to combat increasingly sophisticated attacks from AI-equipped fraudsters.