Hi, welcome to the learning
series for Fraud Protection. We
will be inviting industry
experts to talk about best
practices that top concerns and
the solutions that they have put
in place. Not only that, we will
also be inviting Microsoft
engineering teams to talk about
the innovation that is happening
in Microsoft around Fraud
Protection. In this episode, we
have a very special guest with
us today. His name is Jay Nanduri
and he's the GM and a
Distinguished Engineer with
Microsoft.
Welcome, Jay. Thanks, Kapil.
Thanks for having me here.
So why don't you tell us a
little bit about yourself, Jay.
I've been in the software
industry for more than 24 years,
and in the last 20 of those
years have spent at Microsoft,
and in the last five years have
been working in cloud on AI in
the Commerce ecosystem. How do
we understand our customers and
their purchase behaviors? What
kind of data assets that we need
to drive a better business for
Microsoft, but also create
products that the customers
love.
Wow, that's very impressive all
together. So tell us a little
bit about Fraud Protection. How
did you get involved with Fraud
Protection?
Microsoft was going through a
kind of a transformation as you
know, you know, Microsoft is a
predominantly an enterprise, you
know, engine player and
most of the economics come from
there, but we were also getting
a lot of kind of purchases
customer purchases from app
stores. So as we were going
through the transition, we have
seen that we needed to make the
system more efficient. It was a
play where we wanted to increase
our top line and also kind of
reduce our OPEX,
right. That's very cool actually
impacting the customer
experience as well as the
revenue altogether. What did you
guys do? And how did this
actually end up becoming
Dynamics 365 for Fraud
Protection?
We pretty much had a
predominantly a rule-based
system, any fraud system that we
were doing is we were looking
at, "Hey, is this a good
geolocation where the purchase
is coming from?" Then approve, or
deny. The only way we could do
it is look at Microsoft
holistically, so that we can
look at a customer's journey
into Microsoft, across all the
product segments. In the same
vein, we can also look at the
fraudster's journey across the
products. And that itself has
given us a little bit of a, you
know, uplift because now
fraudsters were not able to go
attack business by business
because if we stopped them at
one gate, they cannot come in
through another gate. Right.
And the second thing what we saw
is the rule-based systems could
not scale right? We saw that,
hey, we need to actually improve
this technology. Let's bring all
our AI
power to this problem.
So basically going from reactive to
proactive. Proactive, right. So
then we, the data that we brought
from all these stores. Now we
let loose all of our ML capabilities
on them. We see that we were
almost 5 to 6% of
transactions were getting
manually reviewed, and it had
gone again, there is a cost
associated. Right, there's an
operations cost. Operations cost. So
now we took our AI assets and ML assets
and we generated deep learning
models on top of this data. And
so we could reduce the manual
reviews and also increase what
we call as our efficiency in
which we can catch the fraud.
Right, okay. So, when we send
this transaction over to the
banks, banks do not have the
kind of knowledge that we have
on the transaction, right. So
our legitimate shoppers were
getting rejected. So at that
particular point, we go we
created a KPI called Profit
Efficiency. What Profit Efficiency
is, what is the maximum profit
that we can achieve by selling a
product- is in the denominator.
And in the numerator, we were
actually looking at what is the
profits were actually making? We
were between 90 and 92% between
the businesses. And then we
looked at it it is just not a
decision sized problem. It is
also an operations problem
because you need to be very
diligent, right about how to
approve or deny transaction,
how do you move forward to the next
party. All this innovation can
be given to our customers on
Azure as an offering, right? And
that's exactly what became a
Dynamics 365 Fraud Protection.
Why it is a compelling product
is because it came from
Microsoft's own experience of
processing billions of
transactions every year, right,
which actually is based on OR as
well as ML. So tell me one
thing, one last question for
you. This is an amazing journey
all together. What is the, what
are the innovation pieces that
you would say? Make Dynamics
Fraud Protection, very different
from what's that in the market?
Whenever a transaction comes in,
we can tell the probability of
fraud, probably very accurately.
We also have an, a connected
fraud protection network, that
is- when merchants are coming in.
Yeah. And their data actually,
when we look at the fraud lead
behavior pattern, we bring into
an anonymized consortium. Right.
And the consortium actually gets
better every day. It learns a
lot more about fraud patterns,
we have a world class, what we
call as a virtual fraud analyst,
kind of an offering, which looks
at a merchant's transaction, and
automatically actually recommends
where is the operating point
the model should be performing
at. And a business manager from
the merchant side, you can look
at it and actually adjust so
that they can achieve the kind
of profit efficiencies that
Microsoft has been enjoying.
Last, but not the least is
we have a feature called
Transaction Acceptance Booster.
 As I told you earlier, in
an e-commerce situation banks do
not know all the information
that the merchants 
knows about. And we have found a
way in which actually we can
transmit this knowledge to the
banks in a very anonymized way
so that the banks can
incorporate this data in making
their acceptances better. Coming
from the real world experience
of a merchant like Microsoft.
And as you know, Microsoft is
one of the top 10 and it gets
attacked quite a lot. Yep. So we
learn on an every second
basis. Yep. And our models learn
and I'm proud to announce that
our time to learn and
actually update a model is less
than 45 minutes today. Wow, that
is amazing.
So the technology itself is
pretty amazing. And just
understanding that Dynamics
365 Fraud, Protection actually
improves the customer
experience, decreases fraud and
increases acceptance is just
unreal. So thank you so much for
being here. And thank you for
the education session that we
just had with you. So I hope
this episode was valuable for
you as as much as it was
valuable for me. It was really
exciting talking to Jay. And
going forward, we will have
industry experts who will be
talking about Fraud Protection,
including our own engineering
team, who will talk about
innovations. Now to learn more.
And to see more of these videos,
join our LinkedIn group, where
all of these videos will be
available as a learning for
everyone in the industry who is
impacted by fraud. Thank you so
much.
