August 2019

1. Around 23 million people have experienced
a life shock in their household in the past two
years. Our new research finds that people
have experienced a life event in the last two
years were three times as likely to be in a
problem debt than those who had not. This
points to the need for a radical overhaul of
protection mechanisms against life events.
This research really brings home the reality
that most debt problems are triggered because
of unexpected events in people’s lives. For
individuals these are unpredictable, even
though within society as a whole we know
that such events are common.
The scale of the problem demands a
coordinated approach. We know that many
people, even those in work, are finding it hard
to build up any level of protection against
these common life shocks. We need policy-
makers to prioritise this issue and we want to
work with them, and others, to identify how
support can be improved to break the link
between life shocks and problem debt.
Currently three million people are in
problem debt in Great Britain, with another
9.8 million showing signs of financial distress.
In 2018, seven in every 10 people who came
to us for advice said the primary reason they
had got into problem debt was because of a
life event or shock. Identifying ‘what works’
in helping people cope after a life shock
should therefore be a policy priority.
There are gaping holes in protection, and
to build financial resilience requires a
rethink of mechanisms to protect against
and manage the financial consequences of
life events such as birth, death, relationship
breakdown, illness, caring responsibilities
and fluctuating employment. A YouGov
survey finds not only did just one life event
increase the likelihood of being in debt, but
also the more life events people experienced,
the more likely they were
to be in debt.
The UK population is
not financially resilient
August 2019 7www.CCRMagazine.com
The Analysis
News & Opinions
Opinion
Phil Andrew
Chief executive,
StepChange
Creditors and collectors which are working
to introduce new artificial intelligence (AI)
technology must be very focused on building
the right set of business rules around the
new systems, according to senior industry
professionals.
Speaking at round-table debate run by
CCRMagazine, in association with Qualco,
Panayis Fourniotis, director of intelligent
decisions at Qualco, said: “There is always a
balance to be struck between following the
rules and challenging the rules.
“If you ask me, the job of AI is closer to
challenging the institutionalised rules that
people follow, rather than just following
those rules religiously.
That is what we use AI for: we have
seen AI as a challenge, for example, for
underwriting rules which have been in place
for so long in the industry that nobody even
thinks about challenging them.
“You will not follow an AI suggestion
automatically, but we have seen many new
ideas come out of it. This can be slightly
scary because, if you think about it, AI is
relying on past data, and so who generated
the past data? It was people making
decisions the traditional way.
“So, all of the potential biases that people
had in the past are included in that data,
and they are very likely to be inherited by
the AI.”
He added: “In the end, it is not just a matter
of using the right algorithm and having the
right data, it is having the right process in
place to validate the outcomes, choose the
ones that make sense, make sure that you are
not doing something unfair or biased, and
then repeat the process after you have a better
strategy. It is a continual process.”
Meanwhile, Perry Burns, former
managing director of Working Capital
Partners, said: “Rules are there to help us to
assess any given situation. When I was
young, I was keen on flying, and in flying
there are a lot of rules. From before you are
even in the aircraft to when you are in the
air and then landing; there are checklists
after checklists.
“Nonetheless, 80% of accidents are
caused by human error and that is simply
because people do not follow the rules.
“The advantage of AI is that it always
follows the rules. You can train people to the
nth degree but they still say ‘well, it is Friday
afternoon and I really do not want to do
then call and anyway he is a nice chap’ and
all of those things, and you find you have
broken the rules. It is about using the AI to
inform a human decision.”
‘Make sure you have
the rules in place’

2. 24 August 2019www.CCRMagazine.com
This year, the hype – and fear,
uncertainty and doubt – is all about
artificial intelligence (AI). How relevant
is AI to the collections industry?
How close are we to adopting the
techniques of AI in collections
analytics and decision making?
SC: I think that there seems to be a wide
variance, it depends on the sector and
the individual companies, and the most
important point is that it depends on where
organisations are starting from.
So the technology that supports AI is
compatible with some organisations’
existing capability and a perception that
it is not with others, without significant
investment.
This leads to a perception in some
companies, which do not have the most
advanced technology, that they cannot afford
to implement machine-learning because they
are a long way behind.
My experience is that is that many
organisations do not have leading-edge
technology. It can be challenging,
particularly in the utilities sector as an
example; to implement new technology
across businesses with such complex and
varied deliverables.
There is a big understanding gap and the
hype is in danger of alienating organisations
that could otherwise benefit from some
help. More education and transparency to
make such developments accessible and
understood, would be really helpful.
MOR: We can use all kinds of different
terminology and I would challenge that
predicted behvioural characteristics have
always been there and we have not needed
AI to do that. The question will always
come back to whether the financial gain
pre- and post-implementation of any of this
technology actually gives benefit in collecting
more and reducing bad debt or else being
able to sell more by making broader products
available to the consumer.
I fully embrace everything that is
developing in the industry, but my question
will always be ‘what is my return for doing
X, Y, and Z’.
PF: Proving the ROI is the holy grail when
anyone is adopting AI or any other form of
analytics, but it is a problem that can be
broken down into pieces.
So, firstly, you do not necessarily need to
prove a huge change in ROI if you are
actually touching processes where you had
no analytics in the past.
For example, if you are attempting to
contact the entirety of your portfolio just
because you do not know which people are
going to be contactable or not, then having
analytics which tells you which part of the
portfolio to focus on brings a very clear
argument in terms of cost reduction on the
rest of the portfolio, where is does not make
sense to do anything. So it can be broken
down and the costs do not have to be
immense.
Everybody focuses on the exciting parts
of AI, but the truth is that, especially in an
industry as conservative as collections, you
never hope to make all of the difference by
adopting new technology, it is always a
combination of technology and process
restructuring and commonsense.
It is just that AI gives you more tools and
flexibility to change your processes.
The promise of analytics, machine
learning, and AI is that they can turn
raw data into business gold. But are
the data really there in the collections
space? What obstacles do you see in
the gathering and use of data for
advanced analytics purposes? Do
you think they can be overcome, and
how?
SC: I wonder if the reality is that those
customers who embrace Open Banking and
make their data available to us all; are the
ones who have better credit records.
PB: If you have been underwriting for a
long period of time, you suddenly get a
‘sixth sense’ when something untoward
happens. You can often be pretty sure that
the next bad thing is going to happen as well.
So, for example, a client asks you for an
over-advance or they are late in making a
payment or there is a sudden change in
director, you get a sense that something
is up.
Someone saying that ‘I do not want to
share my Open Banking data with you’
In Focus
Consumer Credit
Left-right: Alex Woodcraft; Elliot Alexander; Frank Johnstone; Guy Stutter; John McLellan
It can be challenging,
particularly in the utilities
sector as an example;
to implement new
technology across
businesses with such
complex and varied
deliverables.There is a big
understanding gap and
the hype is in danger of
alienating organisations
that could otherwise
benefit from some help

3. Getting to grips
with the AI opportunities
August 2019 25www.CCRMagazine.com
would also be one of those things. It seems
to me that, if humans can build that
experience up over a lifetime of experience,
then AI should be able to do the same, but
a lot quicker.
The trick is that, if AI is spotting those
changes in behaviour, the only control you
really need is to have a human asking ‘is
this an aberration or is it indicative of
something that I then need to look into?’
If AI is used in that sense and it has the
capability to flag anomalies, then it makes
sense.
The danger is that if you build something
from scratch, it is very difficult to
predetermine the precise incongruities
that you need to identify. We had the
experience where we built a chat-bot and
sat for a week thinking about all the precise
questions that people would ask it. It was
and anyone is not using AI, then it will be
extraordinary.
PF: Of course AI can pick up on these
points of human intuition, but the question
is whether it can explain them, because
intuition is very often something that
you can explain: so I saw that someone
withdrawing Open Banking permission and
I know that is a danger sign.
The kinds of AI that a fashionable these
days, such as deep-learning, are not very
good at explaining their predictions. That
is a problem for the collections industry
because we are outside the fashionable
mainstream of AI and, if we do AI, it has
to be human-understandable, which is not
very fashionable these days.
We find that this is one of the areas
where we need to innovate the most
In Focus
Consumer Credit
Last month, a major group of professionals joined a debate led by CCRMagazine and Qualco, to
look into the major issues around artificial intelligence and its developing role in the industry.
They were: : Amanda Wyatt, operational manager, Oakam; Michelle Richardson, customer
outcomes and customer relations supervisor, Toyota Finance; Mike O'Reilly, senior manager
consumer collections and recoveries, BT (MOR); Andrew Townsend, chief financial officer, Unity
Auto Finance; Panayis Fourniotis, director of intelligent decisions, Qualco (PF); Olga Dolchenko,
chief executive, Future Finance; John McLellan, chief executive, the Just Loans Group; Sue
Chapple, director of strategic relationships, Chartered Institute of Credit Management (SC);
Michael Nicholls, director, London Institute of Banking & Finance; Frank Johnstone, partner,
Dentons; Alex Woodcraft, head of collections and insight, Gain Credit; Steve Banks, head of home
and business credit risk, NPower; Perry Burns, former managing director, Working Capital
Partners (PB); David Evans, business architect, Lloyds Banking Group; Guy Stutter, head of sales,
technology, Qualco; Elliot Alexander, business development manager, ComputerShare;
Jan-Michael Lacey, head of sales, Qualco UK; Martin O’Donnell, digital manager, Arrow Global;
Thodoris Psilopoulos, product manager, Qualco; Martin Parr, senior industry professional (MP);
and Liz Thompson, head of compliance, Lending Standards Board
>>
Left-right: Liz Thompson; Martin O'Donnell; Martn Parr; Michael Nicholls; Mike O'Reilly
useless because we were trying to anticipate
human behaviours.
But where you are able to capture those
experiences and you are able to move
faster, and you have someone controlling
that data, then I would say that, if we are
sitting around this table in 10 year’s time
The danger is that if you
build something from
scratch, it is very difficult
to predetermine the
precise incongruities that
you need to identify

4. 26 August 20189www.CCRMagazine.com
because we cannot just pick up best
practices from any other sector.
The other question is that, having
identified and understood the correlation, is
it a natural causal correlation or not, is the
event that we are seeing now causing the
outcome down the road or not?
No form of AI is capable of doing that
yet, it will just give you a list of correlations
but human analysts will need to go in and
check those.
PB: When we used Open Banking, we
had a dashboard that said ‘here are a
couple of behaviours we can see on the
bank account’ and it red-flagged them so
that you could see immediately that, for
example, someone had started spending
money on a gambling site.
You need the human intervention, but
the AI can tell you where to start looking
and that saves huge amounts of time. I
agree that it should not then send them a
demand letter!
But there is no reason why your AI
should not go to your underwriter and
say ‘you really need to take a look at
this’ because otherwise you have a million
accounts and where do you start looking.
MP: AI has been around for many years,
because it is fundamentally scorecards,
and that seems to be wrong’, the AI would
be able to take data that is current and
rapidly update it in real time, because things
move so quickly today.
You also have to always bear in mind
the big question of who makes the final
decision on what you do with the
customer; you cannot have AI make the
final decision without the customer being
able to challenge it.
PF: To an extent, AI is simply scorecards,
and, in fact, at least in the collections
space, we have not seen too much uplift
in terms of predictive power, but we
have seen a huge difference in terms of
automation.
So we can update our own scorecards
very regularly because it is basically free to
do so. AI automates the process to a point
that, once you have a data pipeline in
place, you can just update your scorecards
and obtain a validation of your scorecards
for free. We have seen that make a huge
difference in adoption rates.
In the old days, you might be able to
afford to update your scorecards every six
months or two years because it would
maybe take two months of an analysts
time to produce a new one, and that is
thankfully a problem which has pretty
much gone away. CCR
In Focus
Consumer Credit
Left-right: Olga Dolchenko; Panayis Fourniotis; Perry Burns; Steve Banks; Thodoris Psilopoulos
>> but the problem has always been the speed
with which they are updated.
You always knew with a scorecard that
you had to update it every two or three
years. What would benefit the industry
would be if someone was able to bring in
a process where scorecards are updated in
real time. So rather than someone having
to look at the scorecard and saying ‘this
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When we used Open
Banking, we had a
dashboard that said ‘here
are a couple of behaviours
we can see on the bank
account’ and it
red-flagged them so that
you could see immediately
that, for example, someone
had started spending
money on a gambling site.
You need the human
intervention, but the AI
can tell you where to start
looking and that saves
huge amounts of time