1_A20B7A96ABC4F6BA098D948A72F452BC.RESIZEDmp4.mp4

1_A20B7A96ABC4F6BA098D948A72F452BC.vtt

ENGLISH

Hello everybody and welcome
to this very exciting webinar.

I'm very happy to have
you all join us today.

This webinar will be focusing
on revolutionizing SME

decisioning and open banking to
assess the credit worthiness of SMEs.

intelligence and open banking to
revolutionize online financing and

We'll also be investigating how the
FinTech enables its credit team to gain

a complete picture of an applicant's
creditworthiness, from external data

Lastly, we'll be seeking to answer
how these streamlined processes have

increased the automatic approval rate
of loan applications by 10%, resulting

in faster loan application approval
and disbursement times for SMEs.

I am very happy to be joined
today by Matteo Camelia.

I'm very well, thank you, Matteo,
and thank you for taking the

time today to come speak to us
about this fascinating topic.

I'm going to hand over to you
now, Matteo, so why don't you

your position within the FinTech is,
and then go straight into a presentation

That is to simplify the life
of Italian entrepreneurs.

So this is why our core business
is to lend money with a 100 percent

digital process to small and medium
enterprises, leveraging on the

opportunities granted by the open banking.

introduce myself, I'm
the head of data science.

As I mentioned, I am now the Head
of Data Science in Bankadexa.

I studied mathematics in
Padua between 2009 and 2014.

Then I moved from biology
to quantitative finance.

I had a master in quantitative
finance in Politecnico di Milano.

Then I started working in CRIF as
a management consultant, mainly

There I re experienced the transition
from the so called traditional models

In 2021, I wanted to start contributing
full time to a committed machine

learning approach to credit risk,
and that is something that you

cannot do as a consultant because
you depend on the client's approach.

I started from my comfort zone, so
credit risk modeling, but I quickly

The first one, data are not
to be taken for granted.

Two, in a startup, you need to be
flexible to help the organization.

That's why I expanded
my area of expertise.

Sorry for that also to that
management and to data governance.

If you don't mind, Tyler, I will
skip the, core of the presentation.

be 100% digital and want to
help the Italian entrepreneurs.

The key aspect here is how, and the
answer I'm going to give is, Data

Before going into technical details
however, let me describe you a bit

of the landscape about the Italian
banking system when it comes to

SMEs are historically the black
swan of the credit market.

First and I'm on the left side
of this slide SMEs are clearly

The market sees them when they
really suffer from shocks in

Second point, commercial banks
tend to put the most experienced

That's because in the corporate
segment, there are the highest de cuts.

And from a business perspective, it is
just a bit more cost efficient to use the

most expensive resources in that segment.

Third point, the company valuation core
has been for a very, long time the balance

sheet, and the balance sheet for SMEs
is unaudited and it is not as predictive

Also, when it comes to the relation with
banks, There is no CFO in SMEs, so the

relation is harder, and the companies
do not have a person specialized in

communicating with financial institutions.

At the end, it creates misunderstanding
on what the company needs to request a

loan, needs to provide to request a loan.

And last but not least, SMEs
are simply not cost efficient.

Because, as I mentioned
before, small companies...

We explore how Banca AideXa uses artificial intelligence (AI) and open banking to revolutionise online financing and support the growth of small businesses.
How Banca AideXa’s technology enables its credit team to gain a complete picture of an applicant’s creditworthiness from external data to automated assessment results.
How these streamlined processes have increased the automatic approval rate of loan applications by 10%, resulting in faster loan application approval and disbursement times for SMEs.
