Faster credit decisions mean more business. However making faster, efficient credit decisions is not all that easy.
Watch this Emagia MasterClass video to learn about how AI can facilitate faster B2B credit decisions while automating 70-80% of manual work in credit vetting, setting credit limits, and enforcing credit controls.
This video will preview how AI can:
- Automate manual, paper-based credit function
- Accelerate credit processing and onboard customers faster
- Minimize the credit risk and bad debts
Video Transcript
our attendees uh welcome to a master
class
a session today is on
making same day credit decisions using
ai
and we have with us our master class
speaker john selick
john is a strategic advisor at imagia
corporation i’d like to invite sean to
take through the master class for today
thank you everyone
and um
welcome on
Agenda
credit risk management how it’s changed
and how it’s changed
pretty rapidly
over the last couple of years
not only pandemic caused but other
factors as well so we’ll start off with
an introduction
and we’ll talk um
we’ll talk about
what those
specific challenges to credit risk
management are
and then we’ll talk about solutions
what do we see as the solutions to those
challenges
share with you a case study
to find the benefits
from the solutions
wrap it up with a conclusion and then
take your questions
Todays Focus
all right
so
quickly what is what is our focus for
today
well
if
if you’ve been paying attention for the
last two and a half years you know the
demands on credit management have
intensified in in a variety of ways
and you know the old
peril of uncertainty and credit risk
always with us but they’ve increased
even more
um
post pandemic with the onset of
inflation
um
increase in interest rates
and the threat of a recession
yet through it all
the mission of credit
credit management remains to promote
your company’s revenue in accordance
with their tolerance for credit risk
and promoting revenue is going to be
even more important if
this anticipated recession materializes
and you start to see
revenues decline
or not increase
so it’ll it’ll uh
it’ll be a challenging environment and
Challenges to Credit Management
let’s talk specifically about
what these challenges are
well as been following the news you’ve
seen that the reduction
of uh government financial support
as a result of the pandemic is
being reduced
fading into the past
so that
introduces a higher risk of bankruptcy
companies that may have been able to
survive through the pandemic
with
the government aid
uh may not be able to once that
government aid
ceases
and you know this doesn’t happen
overnight it unfurls unrolls
uh over over a period of a couple of
years
a recent
challenge that emerged is inflation
think of it this way if a customer
pays you 90 days beyond terms
well that money is worth with current
inflation about two and a half percent
less
in real terms
than if
they had paid on time
you know that’s
that’s a pretty steep price to pay
you know a few percent here a few
percent there
and you uh
heads up to real money to kind of
paraphrase uh
senator everett dirksen
and then of course higher interest rates
you know if you were borrowing before
three percent four percent
and you’re borrowing now at five six
seven percent
um you’re going to feel that
and you’re going to want to minimize
your borrowing
i think
you know to amplify
a risk that i i’ve already mentioned
is
is the workload
you know we talk about credit risk
increasing
well
for a lot of your customers
timetable of reviewing their credit
limit annually probably not good enough
anymore uh things are changing too fast
if they were dependent on
uh government aid during the pandemic
the chances are their financial
condition
is changing or the worse
pretty quickly
so that means every 12 months to refresh
the credit reviews probably not adequate
anymore you may have to do it every six
months for some customers every three
and what does that mean
well
it means a higher workload for your
department
you know you could be looking at a 40 50
60
increase
in credit investigations
so you’ve got uh
additional challenges
and you’ve got a higher workload
uh to complicate things a little bit
more as e-commerce
has become
the norm or close to the norm
you know customers are expecting
everything to move fast you know they
place an order electronically
they get an acknowledgement
electronically they get an electronic
invoice they make a payment
electronically
they don’t want to wait seven ten days
for credit approval they want to
start
fast
start receiving product pass so there’s
pressure
on you to meet those deadlines as well
and then
the
the last part is the great resignation
most companies have
or will
lose some employees in their credit
department as part of the great
resignation people moving on for higher
pay
different locations
greater work from home content for a
variety of reasons
and over a period of a year or two
you will probably see the average tenure
of your workforce and credit
um decrease
some experienced people leave you
replace them with new employees or on
the learning curve
so
it’s um
resulting in a lower average tenure and
again
uh the preference is to work from home
and which
kind of dictates a paperless environment
so these are some fairly significant
challenges and they’re kind of all
happening at once
which um
i’m sure this has happened before i just
can’t remember when it was tell you the
truth to have all these things
especially now with the inflation and
higher interest rates um
so it’s a
it’s some serious challenges
Credit Management Needs to Do More
so at the end of the day from our
perspective
uh
credit management
needs to do more
do it faster
better
and more efficiently
and enable
a work from home environment
so think about it
do more faster better more efficiently
and enable a new
mode of working for your employees
that’s a tall order
and
question i pose to you is
how are you positioned to meet this
challenge
Challenge of Competition
well in addition to meeting this
challenge i want to address
the
challenge of
competition
meeting the competition or creating a
competitive advantage through
rapid
credit approval or credit evaluation one
way or the other even if you don’t
extend credit at least you come back
with an answer
because remember your competitors are
experiencing the same things
the same downward pressure on revenue
and probably prices the same increase in
costs from inflation so they’re trying
to
secure new customers as well how can you
beat them well
obviously the product and service you
offer
and the way you price it
are the key determining factors but a
contributing factor is what i alluded to
earlier with a fast credit vetting
process don’t make them wait
and it enables you to onboard a new
customer fast
and kind of preempts the competition
so if you’re a supplier of steel
and
you get a new customer well that
customer probably already has
at least one supplier
if you react quickly and are able to do
business with them you’ll be the second
supplier
if someone beats you to it
chances are
they may still look for a third supplier
but the volume you get from them will be
pretty low so you want to be in there
fast
you want to be in that number two
maybe number one supplier position
and when we say fast how fast is fast
well hackett in their world-class
performance study
defines world-class performance
as making a credit decision in two
days two work days
which is pretty fast think are you doing
are you able to meet that two-day
standard
and as i say the ability to render a
fast credit decision
is one element to give you a competitive
advantage
so that’s where speed comes in same day
next day
Solutions
all right
we’ve talked about the challenges
now what are the solutions
well
there’s a number
of
incremental
solutions
you can implement improving process
uh better metrics and monitoring
um
different things like that
but if you’re looking for
a long-term
kind of major solution
that will deliver
huge increases in speed and productivity
it ultimately comes down to advanced
technology
and when we talk about advanced
technology we specifically mean
artificial intelligence ai powered
digital credit
um
and that will enable you
to
[Music]
deliver
quality credit decisions very very fast
so what do we mean by that well i won’t
get into the technology a lot but we
talk about artificial intelligence
and you’ve probably heard these terms
cognitive self-learning natural language
processing
uh
enterprise information processing which
just
alludes to its uh
close integration with your erp and then
digital assistants
what are digital assistants
well
they’re helpers
they’re
like robots but only
much more capable they assist your team
to do tasks and
provide information to management
more importantly they engage and insist
with customers and of course they can do
that 24 7.
and equally as important they perform
repetitive tasks
also known as grunt work
can you talk about attrition
well if you can eliminate
a lot of the grunt work
and redeploy your staff
to higher level problem solving dealing
with difficult customers
process improvements etc
you’ll have a more enriched job and one
which uh should reduce
the rate of attrition
so digital assistance can make a huge
contribution to your operation the
benefits you know we’ll be talking about
this several times but speed on boarding
new customers
for a totally manual credit betting
operation um
digital assistants with with artificial
intelligence can automate as much as 70
to 80
of those manual tasks which is huge
and even if it’s
your operation is semi-automated
even if you can uh
increase
[Music]
productivity and reduce the uh quote
grunt work by 30 or 40 that’s still a
huge
step forward and one that will be
appreciated
by your employees as well as speed
things up and ultimately it leads to
better credit decisions
so that’s ai powered digital credit kind
of an overview
sounds good right
AI Digital Credit
this slide is a little busy
but
i wanted to put some meat on the bones
here
when we talk about
what is ai digital credit and
specifically what
features what operations it automates
uh what tasks it can handle
uh on a completely
or largely automated basis
so
first of all
is the credit app
no more paper credit app it resides
online
it’s a
format is designed by you
so you can
stress
those factors you think are important
and
omit
those bits of information
you feel
are not useful so you can customize the
credit
it resides online
um
the potential customer
logs on gets the credit app completes it
and
submits it with a digital signature as
you know the signatures are important
because your
terms and conditions are on the credit
app and the customer’s
signature
designates that they
will abide by though they accept and
will abide by abide by those terms and
conditions uh whether they do or not we
all know is a different matter but um
that’s the creditor online
nice
uh and then once you get the credit out
you know the big job in credit
vetting
is gathering all the inputs from your
credit bureau whether it be dnb or
experian experience
if it’s an existing customer retrieving
the payment history
getting all those inputs in
by gathering those inputs so that your
credit professional can
make
a credit decision
um
robots rpa verification bonds they can
do um
nice work in terms of validating their
business registration oh yeah we’re
we’re incorporated in colorado well the
bots the rpa bots can verify that
same thing with tax registration
um
you’ve got the digital assistant
at the ready to support your customers
and your credit staff to secure or find
information
so gathering the information
is very time consuming
and labor intensive
and then once you get it all together
the digital assistant can actually do
the credit scoring
um you input the parameters and the
weighting of the different factors and
it will
create a credit score
you can go a step further
and um
you know have the
expected
monthly sales
volumes input and um the digital
assistant can recommend a credit limit
of course um
to be approved by a credit professional
and of course there’s a
nice approval workflow um
contained
in
the package
and of course you just
route
the credit approval
according to
executes the order polled uh very
closely with collections in your erp
system and you know
in some respects your order hold is the
last line of defense to bad debt right
um if you can
keep that order from going out put
pressure on the customer to pay
and
keep the total ar balance down um you’re
in pretty good shape and of course
it can
produce
credit score cards
uh that you design
and
generally they have some pretty nice
analytics packed so you can start to get
a sense
for the overall credit risk inherent in
your portfolio
so a lot of competition there a lot of
Advantages
capability there excuse me and i
mentioned some of these before what are
the advantages well time saving and both
dimensions of time both the work time
and the elapsed time you know just
something like
securing a credit app you know if you
have a hard copy credit app or
even if it’s online and then the
potential customer just submits it
online
you know if it has uh missing
elements
um
with ai powered digital credit
the applicant can’t submit
the application
you know it rejects it you’re missing
you’re missing the information on line
seven and nine
uh and that eliminates a lot of back and
forth with customer you get the credit
app and you tell them oh
didn’t fill it out completely need you
to do that blah blah blah you know but
tedious time consuming and then the
other big thing is automated gathering
of information if you think about a
credit investigation
60 70 80 percent of the workers in
gathering the credit information you
know you give all that to a credit
professional it doesn’t take long for
them to make a decision on whether or
not to extend credit and how much
they’re verifying of information um is
is critical
uh you know certainly if someone
misrepresents something on a credit app
you you’re going to be very concerned
about that and then as i mentioned
earlier the automated scoring and
the ability to
recommend a credit
and and again
if all this today is manual you’re
looking at significant savings
all right let’s um
Case Study
let’s look at a case study a real-life
case study of a company that
utilized these capabilities in a very
fast-growing active environment
now they’re a building materials company
which means they sell to contractors
builders construction companies
and if you know anything about that
industry
it can be
charitably described as thinly
capitalized
which means they ain’t got no money you
know i mean
basically
they get paid by the general contractor
on the 25th of the month and that’s when
they have money
um
a week or two later
their cash reserves are
probably depleted so it’s a high risk
customer base
but it’s a customer base that needs the
vendor financing
otherwise
they won’t buy from that vendor
so it’s a it’s a challenging credit
risk management
tasks
this client
had a good product
kind of a new product using a new
building material
they were growing fast
and they just couldn’t keep up
with
the credit apps
so they deployed
uh digital credit automation from memaza
and
with the credit app that we described
digital signatures
uh the automated
information retrieval and checks
uh they integrated it they were using an
experian as a credit bureau
and they had designed their own
analytical tool in netsuite
which enabled automatic credit limit
decisions
um
you know they
were able to automatically verify resale
certificates
which is very important and at the end
of the day they automated over 80
percent of their credit betting process
pretty good
and they’re able to get their turnaround
time on a credit app from 14 work days
down to four
now
last i heard they’re actually
uh pushing
three days and hoping to get to two days
you know to the heck at best practice
and of course this
enabled them to respond to customers set
them up and start shipping them
very very quickly
and help to fuel their growth
Recap
so
let’s just uh
kind of recap the benefits i’ve been
mentioning them as we go here
um
but you know we we can see
significantly faster turnaround of
credit apps
increase productivity
when you eliminate all that manual
retrieval of information
and ultimately it positions the
organization to maximize its revenue
while still controlling credit risk and
enable them to onboard customers faster
and if you look at the value chain at
the bottom here um you know i think it’s
a pretty typical value chain
and certainly
uh
speeding up credit apps are a part of
that
part of that contribute to that
Conclusion
so what’s our conclusion
um remember how we started out they
talked about challenges to credit
management and and really there were
five challenges
um cited on that
third or fourth slide and we’re all
pretty serious and
um some are new some of the uh age-old
high interest rates inflation
um that sort of thing
but
i don’t think it’s overstating to say
credit management is being severely
challenged
so
you need an excellent credit risk
management capability
and as i said you can probably take some
incremental steps
streamlining processes maybe
buying some other information streams
things like that but
for the long term
kind of major improvement
it really comes down to technology
automation
and
specifically
ai powered digitization within the
credit function
Audience Question
all right
um
questions
here’s an uh audience question
you know of
of
the various challenges
cited
uh to the credit function which in your
opinion are the most serious
well one
you know the age-old
challenge is the overall increase in
credit risk in the economy um
you know if you think back to the great
recession of 2008 and nine
i mean technically the recession ended
2009-2010
but you know bankruptcies
continued
at an elevated level for another five
years
before they dropped back
to the pre-recession levels so the
bankruptcy and the credit risk has quite
a tail
long tail
um you know the um
inflation and the interest rates those
uh fine if you get make bad credit
decisions and you get stuck with slow
paying customers
um
you’re going to see a deterioration in
the value of the money you collect
and that’s simple
um and you know if you’re borrowing
you’re utilizing short-term borrowing to
meet your cash needs well that’s going
to be much more much more expensive
probably going double at least double
before um
it stops rising
so to me
um
those are the two of the major
challenges and then the third one if you
haven’t already dealt with it is work
from home
you know
employees want to work from home
and
they’ll leave your company
to get it they’ll
not join your company if you don’t have
it so
uh that’s not a huge technology
challenge
but
it’s
it is significant if you don’t have it
and you know you don’t can’t snap your
fingers and all of a sudden everyone can
work
so those those are the challenges the
other key
challenge
is you know we talk about artificial
intelligence
capabilities and everything
um
what
the key capabilities it brings to credit
management well i would say
two
one the online credit app
and two
the auto retrieval of all the
information you need to make a credit
decision i mean
that’s that’s a lot and it can be very
time consuming and laborious to get all
that information just to let you know um
the next master class in two weeks
entitled 2022 trends and integrated
invoice to cash automation
again
um
be another good program the 30 minute
program and we
suggest you book your seat today and
join us it’ll be a good one and we thank
you for your attendance today thank you
very much john