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'cause, you know, we all own money, your
mortgage, your car, your whatever, your
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credit card, let's say your student loans.
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So we all own money.
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You're not going to jail.
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And there, there are ways
to manage it and pay it off.
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We've spoken about this before in
previous episodes on collection.
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The fact is we can learn an incredible
amount from the mistakes we make,
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but too often in lending businesses,
we don't build the feedback loops
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that are needed to bring lessons back
from collections to originations.
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Welcome to how to lend money to strangers.
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I'm your host, Brendan look range.
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And I have been working in consumer
lending for the last 20 years.
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Delivering projects in Africa, Asia.
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And now as the chief solution
architect at confirm you a FinTech
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that's game of finding access to
credit among the end bank, check out
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our story in episode 24 of the show.
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But if we can learn from collections,
then it stands to reason we can learn
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even more from the companies that
specialize in helping consumers, when
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loans go wrong, like the New York.
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Debt MD's whose founder and CEO.
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James Lambrettas is here with me today.
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James.
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Lambrettas welcome to the show.
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You have a undergraduate degree in finance
from Penn state and an MBA from NYU stern.
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So all the typical qualifications
of a banker and yet the last decade
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or so of your career has been spent
some might say on the other side
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of the fence, Helping consumers
to push back against the bankers.
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That's probably a little bit of an
aggressive description, but certainly
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helping travel datas to extract
themselves from bad credit situations
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and take control of their own debt.
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So let's start with that
interesting contrast.
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Could you expand a little bit on your
background and what got you to move
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into this world of debt solutions?
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For sure.
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So before launching that MD Brandon,
I worked a, as you said, in the debt
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relief industry for five years, my job
was to advise people as to what their
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best option was to pay off their debt,
predominantly credit cards, and then
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some medical bills and student loans.
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So everyday for five
years, I would speak with.
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Both in-person and on the phone,
assess their financial situation
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and then recommend a solution based
off their unique circumstances.
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What I've found from doing that every
day, because, you know, as you can
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imagine, when you speak to the same
type of person or same type of customer
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every day for five years, you begin
to glean insights on them, right?
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So people in debt they're
stressed out, they're under time
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constraints to find a solution.
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Many of them are misinformed as to what
their best option is to become debt free.
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So.
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That got me thinking, you know,
how can I improve this situation?
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Make it easier for them
to find a solution.
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And that's ultimately when I
thought of the idea for dead MD.
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So I wrote a business plan,
raised some capital, and then we
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built and launched the platform.
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Well, one of the things you have
is certainly quite an in-depth
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blog section on your website
with quite a few good articles.
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And one of them that I've seen
uptake quite recently was a stat
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that 74 million Americans have
more credit card debt than savings.
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So this really is a huge, I don't
want to say problem, but a huge
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section of the market that need to
be thinking strategically about it.
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One question I did have was, do you work
primarily or exclusively with consumers?
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Who've got problems with
their data that I know of.
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So consumers that are
already in delinquency or.
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Struggling to make payments, or
do you also work with consumers
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who are just acknowledging that?
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Look, I'm paying all my debts,
but I've got a lot of them and I'm
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sure there's a better solution.
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I just don't quite know how to solve it.
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That's a great question.
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So to answer it, honestly, both
because you do have that first
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group of people that you mentioned
where, you know, they're really
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struggling, they have average to poor.
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They, they can barely keep up with all
their debt payments and for people like
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that, there's solutions, whether it's
a credit counseling or debt relief,
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but then you have people who, yeah.
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They may have a little
bit of a, of on security.
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But they're there.
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Credit's good, but they're just
looking to lower their interest rate
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and lower their monthly payment.
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And if they have good credit,
they're able to do so, because if
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the average interest rate on a credit
card today, I believe is like 19%.
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So why pay 19% interest?
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If you could consolidate your debt
with a loan, lock yourself at say 7%.
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So you could save hundreds, if not
thousands of dollars on that debt
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and pay it off in a reasonable time.
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Instead of kind of spinning your wheels,
paying on the individual credit cards.
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So in the end, whether you're you have
bad credit or great credit, it comes
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down to making a wise financial decision.
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So you can ultimately become debt
free in a short period of time.
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So that's what it comes down to.
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And before we deep dive a bit of
how Tet MD is helping, let's take a
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consumer's point of view here quickly.
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What are some of the common routes
into trouble that you see from
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your bird's eye view of the market?
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Are there certain specific events or
choices or even mistakes that people
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are making to lead them to need
the assistance of someone like you?
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For sure.
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And we've actually done some
research on this, the top
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reasons why people fall into.
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Number one is a job loss.
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We've also seen, you know, a lot
of people that get divorced end
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up in debt because you go from two
incomes to one and then you might
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have to pay child support alimony.
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So that's another big one.
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And then the third one is
like a medical emergency.
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You know, stuff happens
in life, as we all know.
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And you know, if you have to get
rushed to the emergency room, Now in
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your, in the UK, but here in the U
S a lot of people don't have health
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insurance, or aren't completely covered.
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So when you have that medical emergency,
a lot of times, unfortunately, you're
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stuck with massive medical bills and a lot
of people end up either taking out loans
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or charging the medical bills on credit.
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Those are the three major life events
that we've seen that caused people to
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go in debt, which is quite interesting
because, you know, there's still, I would
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say a stigma around getting yourself
into this sort of financial trouble.
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And the assumption would be that, oh,
these are people who've, overborrowed.
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Spent excessively on trivial items.
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And of course they are people who struggle
with spending on their credit cards.
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But it's also clear that these are
just a lot of the factors that all
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of us face, as you say, we're all
liable to hit by a medical emergency.
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Things like divorce, obviously
sort of wanting to couples will go
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through, but you know, a lot of the
headlines now buy now pay later.
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And whether it's going to encourage
young people to overspend where it sounds
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like we also need to be thinking a lot
more about the other changes, unforeseen
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events, bigger events, where it's less
of a, a bad habit to more of where you
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need some help to get back on your feet.
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Yeah, for sure.
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And there is this negative
stigma for people in depth.
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There are a lot of people who
they overextend themselves.
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They spend more than they bring in.
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You know, unfortunately those people
end up in that as well, but there's
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one point I want to get across.
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Sometimes it's people are unlucky.
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They, they have these emergencies
and getting into debt as a result of.
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And I think that if we go looking for
silver linings in something like COVID
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one of those silver linings might be
that it's normalized collections to
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some extent, and certainly normalized
going to your lender and asking for
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some assistance in repaying, your.
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We've had people that
are losing their jobs.
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We've had people who've had the hours cut.
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On the other hand, we've had people who've
benefited from government programs, or
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simply because they couldn't spend, you
know, saved money during the crisis,
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but you've got a better view of that
than I to what have you seen through
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COVID through all the way that this
has maybe changed the tit environment?
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Yeah.
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And believe it or not actually
during COVID we in the U S I can only
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speak for the us, but we actually
saw one of the biggest pay downs of
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credit card debt, unsecured debt.
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In a long time, I want to say 10 or
20 years with the lockdowns people
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couldn't really go out and spend money.
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With the federal unemployment benefits.
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Some people were actually getting more
income than they were at their job.
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So what a lot of people did was
pay down their debt and then the
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government did implement these grays
periods, especially with student
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loans, president Biden actually just
extended that, uh, up until may.
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Not to mention there was a freeze on for
sure rent, and I believe you, you could
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get approved to not pay your mortgage.
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So that gave people the
opportunity with no expenses.
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Really everything's closed.
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Everything's locked down.
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Why not pay down some debt.
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So that's kind of surprising.
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You think all, everything is so bleak
with COVID, which let's be real.
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It kind of was, but you know, the
one positive is that a lot of people
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were able to pay down some debt.
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Yeah.
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And I think that pattern is repeated in
many markets, certainly in the UK as well,
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where payment, holidays, or mortgages,
where the most publicized first step.
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And for most people who have a mortgage,
that's your biggest monthly expense.
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So it only took one or two months
of not paying your mortgage
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to pay down your other debts.
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Now, some people took it because they
lost their jobs and they need the
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extra money, but others simply took
the payment holiday, use the spare
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capital to pay down their credit cards.
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And I know Peter position, it will
be interesting to see was this just
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a pay down that everyone benefits and
they start to build back up again,
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or will this change behaviors, but
yeah, an interesting time, certainly
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to be in this side of the market.
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Clearly, there's a number of reasons
that consumers have caught into
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the situation where they asking
for some help with managing the.
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Let's talk about how debt
MD provides that help.
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What services do you do?
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What does it look like
to work with Tet MD?
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We're the platform that connects
people with the professional help
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they need to become debt-free.
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We help people with credit cards,
medical bills, and student loans.
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So the user they'll go onto our platform.
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We have what's called
our smart debt analyst.
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It asks the user questions about their
types of debt, total debt, what their
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main goals are, whether it's, you know,
lower their monthly payment, lower their
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interest rate, who's their credit score.
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And then based off the answers to
those questions, we connect them with
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the relevant company or companies
that can best assist them with their.
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There is no one size fits all
solution for anyone in debt.
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Everyone's got a different credit score.
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Everyone's got a different income,
everyone's got different financial goals.
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So we want to lay out their
options in front of them.
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You know, the pros and cons
of each, whether it's credit
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counseling, that settlement alone.
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We want to be that educational partner
and form them on, on all these options.
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Cause once again, a lot of people,
aren't sure the difference between
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those three and then ultimately they
can decide for themselves what's best.
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Yeah.
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And I think it's interesting that we've
seen a lot of apps on the front end to
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helping you to better understand which
credit card will give you the best air
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miles return, but you're filling that
same sort of role at the back end saying,
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look, you've taken on these various parts.
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A lot of them have terms and conditions.
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You probably haven't written yet.
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None of us do then you're not coming
in from a data is bad approach.
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Or, you know, there's an
industry here in the UK.
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I'm sure it's in there around the
world as well, where people will
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come in and say, okay, well we
can get your data as an office.
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And it will cause quite a lot of knock-on
impacts people don't fully understand.
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Whereas you've taken this neutral approach
and sometimes that at approaches, yeah.
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He has a debt consolidation loan, which
has, you know, this is still taking
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on credit and sometimes it's okay.
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We need to make a payment plan,
but it's not a, uh, out the door.
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We want to get all this data to north
and we want to make the lender suffer.
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One of the things that I saw again
on, on your blog when I was scrolling
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through it the other day, though,
was a warning about scams to look
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out for in d'etre payment service.
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What are the things to
people need to be aware of.
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Yep.
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Unfortunately like the debt
settlement industry is widely
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known for having a lot of scams.
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If you're looking into like that
settlement, that relief, if there's
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companies that they say they do not charge
you any fees, I would run away as fast
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00:13:35,235 --> 00:13:39,944
as I can because in the end, whether
it's a lender or a credit counseling
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agency, any company on the planet,
they're in the business of making sure.
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If they're telling you that they're not
charging any fees, that that's a red flag
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and I would not do business with them.
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And then you have some companies
that offer like some form
233
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of money back guarantees.
234
00:13:55,910 --> 00:13:58,190
Usually this is with
debt settlement as well.
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You're not buying like vacuum cleaner.
236
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If it doesn't work, they're going
to give you your money back.
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This is your financial
future at stake here.
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So once again, that's,
that's another major red.
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And then I guess I'll leave it at.
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00:14:11,370 --> 00:14:15,240
And, uh, I know you're, you know,
you're in the lending industry, but
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some people can't get a traditional
loan from a traditional lender.
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So they end up going
the payday loan route.
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00:14:22,740 --> 00:14:26,339
And, you know, I don't know
how it's still legal, but a lot
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of people do get payday loans.
245
00:14:27,660 --> 00:14:30,150
You're talking like
hundreds of percentage.
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00:14:30,785 --> 00:14:33,785
And you literally keep paying
and paying and paying and, and
247
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the principle never goes away.
248
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Yeah.
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You get to pay off credit cards,
but you, you put yourself in
250
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a worse financial situation.
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So those are the three main red
flags I would watch out for yeah.
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On the payday lending industry.
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As you said that it's a quick one until
suddenly it just builds up and pulls up.
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00:14:52,655 --> 00:14:56,225
One, one thing I'm interested in
is if I've, if I've got this right,
255
00:14:56,225 --> 00:14:57,425
somebody will come engage you in.
256
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He has my date situation and you'll
help them solve their problem today.
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00:15:01,990 --> 00:15:05,560
And sometimes that's enough because as we
say, sometimes it's just through divorce,
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a medical emergency or student debt.
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That's got them where they are.
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But for other people where it might
be more of bad spending habits are
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the other tools that you provide to
help them in the longer run I've seen.
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00:15:16,750 --> 00:15:20,470
As I mentioned already a few times,
you've got that great blog and you put
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out a lot of good content that how else
can you perhaps build these strong.
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00:15:25,710 --> 00:15:28,440
So that they don't fall into
the same situation down the.
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00:15:29,460 --> 00:15:34,530
I feel like most people keep some type
of spreadsheet or budget to see what's
266
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coming in, what's going out, but we've
actually built out basically this debt
267
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analysis, personal finance spreadsheet.
268
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As long as you input your debt correctly,
with your monthly payments, you can see
269
00:15:47,310 --> 00:15:49,260
exactly what you're paying out each month.
270
00:15:50,045 --> 00:15:53,314
You know, if you keep paying X
dollars, this is how long it's
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going to take you to pay off.
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And we send it to anyone who subscribes
to our email list, you know, because
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when you have four or five credit
cards, the bills are coming and
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then that one comes 10 days later.
275
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You never really have a good snapshot.
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You know, you just keep paying and
you don't really think about it.
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Right.
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00:16:13,675 --> 00:16:16,345
And a lot of people have automatic
payments set up, so it doesn't
279
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occur to them with this personal
finance, uh, analysis spreadsheet.
280
00:16:20,425 --> 00:16:23,485
They can see exactly what
they're paying when you have
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like 20,000 or 30,000 in debt.
282
00:16:25,765 --> 00:16:29,755
You'd be surprised people are
paying a thousand, $1,500 a
283
00:16:29,755 --> 00:16:31,075
month and just minimum pay.
284
00:16:31,875 --> 00:16:36,045
When you put it in front of somebody's
face and they see how much they're paying.
285
00:16:36,375 --> 00:16:38,415
That's when they know they
really need to do something.
286
00:16:39,195 --> 00:16:42,915
Get a loan to pay it off or do
it on their own, minimize your
287
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expenses, take on another job.
288
00:16:45,345 --> 00:16:49,305
But the point being is doing
nothing is like probably one
289
00:16:49,305 --> 00:16:50,565
of the worst things you can do.
290
00:16:50,805 --> 00:16:51,105
Yeah.
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00:16:51,285 --> 00:16:53,565
And it's a message has come
up in a few interviews.
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00:16:53,565 --> 00:16:56,685
I've done with people in
collections where we'd all have
293
00:16:56,685 --> 00:16:58,395
this fear of being yelled at.
294
00:16:59,035 --> 00:17:01,825
It meant that you'd scrambled
and try and make solutions.
295
00:17:01,825 --> 00:17:06,265
You take out this payday loan, or you
would go down to minimum payment and
296
00:17:06,265 --> 00:17:09,295
then maybe you take another credit card,
have minimum payment, all know hope
297
00:17:09,475 --> 00:17:13,225
you could solve this without having
to be yelled at nobody ever spoke to
298
00:17:13,225 --> 00:17:17,785
the lender until it was far too late,
but as collections as modernized, and
299
00:17:17,785 --> 00:17:19,555
certainly COVID has helped here again.
300
00:17:20,430 --> 00:17:24,060
Making it online, making ways
to communicate without the
301
00:17:24,060 --> 00:17:27,450
embarrassment of a face-to-face
or a phone call trying to make it.
302
00:17:27,450 --> 00:17:31,260
So consumers do have that conversation
early on, because as you said, the
303
00:17:31,260 --> 00:17:32,280
worst thing you can do is nothing.
304
00:17:33,435 --> 00:17:36,945
And I think that's one thing I want to
pick up on here now, because he, as you
305
00:17:36,945 --> 00:17:41,385
mentioned, I've always worked in lending
and I think one big systematic problem we
306
00:17:41,385 --> 00:17:46,845
have there is that we turned have a very
good feedback loop at an individual level.
307
00:17:47,145 --> 00:17:51,165
So we would bold a model
for a lending product.
308
00:17:51,195 --> 00:17:54,975
And we would look at the risk profile
and we'd say on this portfolio.
309
00:17:54,975 --> 00:17:59,084
So let's say if we issue a 10,000 loans,
as long as less than 2% of them go to.
310
00:17:59,940 --> 00:18:03,750
We're making profit and then we'd roll
out the product and we'd measure the risk.
311
00:18:03,810 --> 00:18:06,630
As long as it's less than 2% is going bad.
312
00:18:06,780 --> 00:18:10,530
We never really think about it, but
every one of those people that do go
313
00:18:10,530 --> 00:18:15,210
to LinkedIn for them individually as
usually some sort of personal trauma,
314
00:18:15,480 --> 00:18:18,810
not every time, but I'd say, and maybe
you do have some numbers, but the
315
00:18:18,810 --> 00:18:21,930
vast majority of people something's
gone wrong, they're upset about it.
316
00:18:22,110 --> 00:18:23,160
It's really stressful.
317
00:18:23,490 --> 00:18:23,910
It's trauma.
318
00:18:24,735 --> 00:18:27,525
And they don't want to
go through collections.
319
00:18:27,645 --> 00:18:30,675
No, never, but we kind of forget
about them because while it's
320
00:18:30,705 --> 00:18:32,625
within, within our target, for sure.
321
00:18:32,775 --> 00:18:36,885
But these consumers, no doubt, one lenders
to think about it and actually say, how
322
00:18:36,885 --> 00:18:40,635
can you build a better product so that
people don't go through that and you will
323
00:18:40,635 --> 00:18:42,645
have had a unique experience of this.
324
00:18:42,645 --> 00:18:44,835
You know, we were supposed
to learn from our mistakes.
325
00:18:45,135 --> 00:18:47,505
You can see the lending
industry's mistakes.
326
00:18:48,395 --> 00:18:52,475
Have you got any thoughts about how
lenders should be designing their
327
00:18:52,475 --> 00:18:56,315
products or doing their marketing
or managing their customers in a
328
00:18:56,315 --> 00:18:58,205
way that can be better for everyone?
329
00:18:58,980 --> 00:18:59,400
Yeah.
330
00:18:59,700 --> 00:19:04,920
And I'm sure as, you know, every loan
company markets, the quote unquote
331
00:19:04,950 --> 00:19:08,340
debt consolidation on that's like
one of their big offerings, it's
332
00:19:08,340 --> 00:19:12,150
a buzz term and maybe they market
it, you know, and everyone sees it.
333
00:19:12,270 --> 00:19:17,580
Now the purpose of the debt
consolidation loan is pay off their debt.
334
00:19:17,580 --> 00:19:17,850
Right.
335
00:19:17,880 --> 00:19:19,860
Let's just say they paid
off their credit cards.
336
00:19:20,130 --> 00:19:24,060
And I'd love you to chime in
here, Ken, the lender who who's
337
00:19:24,060 --> 00:19:25,770
offering that consolidation.
338
00:19:26,550 --> 00:19:29,880
Ask or somehow make the bar.
339
00:19:30,645 --> 00:19:35,355
Closed down their credit cards that
they just paid off or refrain from
340
00:19:35,355 --> 00:19:39,885
using them because I've seen this
firsthand where a person gets the loan,
341
00:19:40,095 --> 00:19:44,235
pays off their credit card and then
proceeds to charge them back up again.
342
00:19:44,295 --> 00:19:47,625
And that's a situation where
they're most likely going to default
343
00:19:47,715 --> 00:19:51,315
if they have to now pay their
credit cards and this new loan.
344
00:19:51,525 --> 00:19:55,425
So you mentioned, how can
they make everyone better off?
345
00:19:55,665 --> 00:19:56,805
Is there a way to.
346
00:19:57,639 --> 00:20:01,060
Oh, you have to close the cards
though, or you can't charge on
347
00:20:01,060 --> 00:20:04,320
them because once again, I think,
you know, everyone benefits from.
348
00:20:05,055 --> 00:20:09,165
One other thing, and I'm sure you
definitely know more about this than I do.
349
00:20:09,405 --> 00:20:14,265
We're working on, it's almost dumb, a
machine learning application where we
350
00:20:14,265 --> 00:20:20,415
can actually predict what the optimal
debt relief option is for a user dive
351
00:20:20,415 --> 00:20:22,395
deeper into their financial profile.
352
00:20:23,070 --> 00:20:25,020
Yes, I'll speak to your first one.
353
00:20:25,020 --> 00:20:29,520
When in the very early days, we, and
this was partly because logistically
354
00:20:29,699 --> 00:20:33,240
you couldn't easily do this, but
we would manually take on the job
355
00:20:33,240 --> 00:20:35,040
of closing the consumer's account.
356
00:20:35,040 --> 00:20:37,470
So we would say, bring your
data across to us and we will
357
00:20:37,470 --> 00:20:38,879
close your other cards for you.
358
00:20:39,270 --> 00:20:41,100
And we could get away with that.
359
00:20:41,100 --> 00:20:43,560
But what happened then is
from a competition point of
360
00:20:43,560 --> 00:20:44,970
view, smooth the process.
361
00:20:45,360 --> 00:20:47,370
People would start giving up on that.
362
00:20:47,730 --> 00:20:50,669
So now we have this situation
where exactly as you described.
363
00:20:51,720 --> 00:20:55,530
I will give you a debt consolidation,
loan, but your credit limits.
364
00:20:55,530 --> 00:20:57,540
So sitting there and it's
in the back of your mind.
365
00:20:57,750 --> 00:21:00,300
And next thing you know, you've now
just caught the debt consolidation
366
00:21:00,300 --> 00:21:04,980
loan, and your credit limit used up
that said, you know, can we stop?
367
00:21:05,774 --> 00:21:08,445
It wouldn't be something
that needs new technology.
368
00:21:08,445 --> 00:21:10,155
It's only doesn't even need new networks.
369
00:21:10,365 --> 00:21:12,885
If we look at something like
the gaming industry, you know,
370
00:21:12,885 --> 00:21:14,595
you can blacklist yourself.
371
00:21:14,804 --> 00:21:17,415
You can say, I don't want
to, I don't want to Campbell.
372
00:21:17,685 --> 00:21:22,365
There is in the credit bureau world, you
can freeze your credit profile, which is
373
00:21:22,365 --> 00:21:25,125
usually a defense against identity fraud.
374
00:21:25,514 --> 00:21:27,825
I'm sure that same
process could be worked.
375
00:21:28,245 --> 00:21:31,814
And we just need to tweak it a little
bit that when somebody volunteers.
376
00:21:32,820 --> 00:21:35,880
This is what I want, my
weaknesses runaway Spain.
377
00:21:36,180 --> 00:21:37,620
And I would like to be helped.
378
00:21:38,190 --> 00:21:39,480
Would there be ways around it?
379
00:21:39,630 --> 00:21:40,500
Yes, of course.
380
00:21:40,860 --> 00:21:42,690
So, yeah, it's not perfect,
but I think you're right.
381
00:21:42,690 --> 00:21:45,810
That it shouldn't be that
hard for a consumer who is.
382
00:21:46,770 --> 00:21:48,120
This is the problem.
383
00:21:48,990 --> 00:21:49,410
Yeah.
384
00:21:49,440 --> 00:21:53,970
And you know, one last thought on that,
where you tell people, or you make people
385
00:21:53,970 --> 00:21:58,170
close out all their credit cards that
is going to impact their credit score.
386
00:21:58,170 --> 00:22:01,290
So that's why a lot of people are
going to balk at that because.
387
00:22:01,995 --> 00:22:05,835
Credit score is important, but
all these banks, they convey it.
388
00:22:05,835 --> 00:22:07,785
Like it's like your firstborn child.
389
00:22:07,785 --> 00:22:09,945
Like God forbid it goes down three points.
390
00:22:09,945 --> 00:22:13,575
And once again, I'm not, I don't want
to downplay it, but I don't think
391
00:22:13,575 --> 00:22:17,865
it's the end all be all when it comes
to having good financial health.
392
00:22:18,255 --> 00:22:22,275
I think that's more so how much cash do
you have in your, in your bank account?
393
00:22:22,665 --> 00:22:24,855
How much savings investments?
394
00:22:24,885 --> 00:22:25,815
Zero debt.
395
00:22:25,845 --> 00:22:29,745
Most importantly, the last 10 years
of my career were in quite a few.
396
00:22:30,495 --> 00:22:33,585
And I'm the biggest proponent
of look your credit score.
397
00:22:33,615 --> 00:22:36,764
If you've missed a payment,
you'll have a bad credit score.
398
00:22:36,795 --> 00:22:39,435
If you've never missed a payment,
if you keep hitting your limits,
399
00:22:39,435 --> 00:22:40,695
you're kind of in the middle.
400
00:22:41,024 --> 00:22:44,264
But beyond that, it's largely irrelevant.
401
00:22:44,534 --> 00:22:48,135
The marketplace is such that
if you qualify for a mortgage,
402
00:22:48,495 --> 00:22:49,365
there'll be competition.
403
00:22:49,365 --> 00:22:50,325
You'll get a good rate.
404
00:22:50,655 --> 00:22:53,705
If you want a credit card,
you can get a credit.
405
00:22:54,435 --> 00:22:56,655
Does your oldest account on record help?
406
00:22:56,805 --> 00:23:00,165
That helps a little, but it's,
it's not changing anything.
407
00:23:00,705 --> 00:23:06,015
The level of detail in the credit score
is fantastic, but few lenders use or can
408
00:23:06,015 --> 00:23:10,845
even use a strategy that deep and we've
wanted people to value the credit score.
409
00:23:11,175 --> 00:23:13,305
We want them to understand
it's there, but.
410
00:23:14,035 --> 00:23:17,725
One of the problems with the way we've
talked about credit scores and we've
411
00:23:17,725 --> 00:23:21,895
made them too personal mathematically,
would we do the credit score?
412
00:23:22,255 --> 00:23:22,495
Right.
413
00:23:22,495 --> 00:23:24,895
We calculate it without
knowing who you are.
414
00:23:25,285 --> 00:23:26,845
We strip away all those details.
415
00:23:26,845 --> 00:23:28,405
So it's not a judgment on ups.
416
00:23:29,265 --> 00:23:33,855
What we're saying is from the data we
have in front of us, looking back people
417
00:23:33,855 --> 00:23:36,135
with this pattern on average, that does.
418
00:23:36,735 --> 00:23:41,355
And I think if we can get people to stop
seeing it as that, what have I done wrong?
419
00:23:41,805 --> 00:23:45,855
I can be the most confident about
you when I've got the most data.
420
00:23:45,915 --> 00:23:49,905
So if you have lots of credit cards,
you've paid, I can see that I can be
421
00:23:49,905 --> 00:23:53,865
a little bit more confident, but if
I don't have that, it's not negative.
422
00:23:53,865 --> 00:23:54,975
It's just saying I'm a little bit less.
423
00:23:54,975 --> 00:23:55,275
Sure.
424
00:23:55,815 --> 00:23:57,305
And I think there is now a time.
425
00:23:58,200 --> 00:24:01,560
Where we almost need to step back and
say, okay, we've maybe gone a bit too far.
426
00:24:02,070 --> 00:24:03,840
You can ease up a bit
on your credit score.
427
00:24:03,870 --> 00:24:04,740
They fluctuate.
428
00:24:05,129 --> 00:24:07,950
They change on some things
that are entirely irrelevant.
429
00:24:08,760 --> 00:24:09,960
Your credit bureau score is important.
430
00:24:10,800 --> 00:24:12,180
But there's other ways
to measure your risk.
431
00:24:12,210 --> 00:24:15,690
There's other ways to measure
your favorite Realty and
432
00:24:16,020 --> 00:24:17,010
let's say, you're right.
433
00:24:17,040 --> 00:24:18,030
What is your savings?
434
00:24:18,270 --> 00:24:19,290
What is your net wealth?
435
00:24:19,320 --> 00:24:20,820
What is, how much do you owe people?
436
00:24:20,820 --> 00:24:23,430
How flexible are you to
ride through a crisis?
437
00:24:23,700 --> 00:24:26,460
All of that is going to be
more important to a lender.
438
00:24:26,460 --> 00:24:28,860
Then five points here with a, on a fire.
439
00:24:30,240 --> 00:24:30,690
And then, yeah.
440
00:24:30,690 --> 00:24:33,120
And in terms of machine learning,
I think one interesting thing with
441
00:24:33,120 --> 00:24:38,129
machine learning is that it's actually
not used all that much in the credit
442
00:24:38,129 --> 00:24:42,480
bureau world, because we use using very
structured data that doesn't necessarily
443
00:24:42,480 --> 00:24:47,190
need machine learning, but it's been
tried out in a lot more of these other
444
00:24:47,190 --> 00:24:48,990
scenarios, more like what you're saying.
445
00:24:49,379 --> 00:24:52,740
And I really think that's where
it comes into its own because each
446
00:24:52,740 --> 00:24:56,790
month while it probably each week,
each day, maybe different products
447
00:24:56,790 --> 00:24:57,810
are being offered by the model.
448
00:24:58,650 --> 00:25:00,660
Different situations are
presenting themselves.
449
00:25:00,660 --> 00:25:04,710
And that's really where something
a lot more flexible comes in to
450
00:25:04,710 --> 00:25:07,080
have a system who can do that.
451
00:25:07,110 --> 00:25:09,600
You don't have to go
through feeling the state.
452
00:25:10,365 --> 00:25:14,655
Feeling the embarrassment, feeling the
stress, throw it all at the machine.
453
00:25:15,195 --> 00:25:16,725
Come give me three solutions.
454
00:25:16,965 --> 00:25:18,735
Yeah, I can pick the
one I went from there.
455
00:25:19,635 --> 00:25:20,715
It's a clean process.
456
00:25:20,715 --> 00:25:24,525
And I think where we can take that
trauma art move away from that school
457
00:25:24,525 --> 00:25:27,675
model where, you know, you've been
naughty and are you must endure are
458
00:25:27,675 --> 00:25:29,565
shouting at you until you pass back.
459
00:25:30,225 --> 00:25:31,905
I'm still in the lending industry.
460
00:25:31,905 --> 00:25:34,155
So I probably shouldn't be too
aggressive on this note, but.
461
00:25:35,010 --> 00:25:36,270
We can push back a little bit.
462
00:25:36,270 --> 00:25:40,830
NCN if no fraud was committed, this
was a business decision that was taken.
463
00:25:41,010 --> 00:25:44,460
It's a profitable business
decision overall for the lender.
464
00:25:44,880 --> 00:25:46,980
And don't take it too personally.
465
00:25:47,640 --> 00:25:47,970
Yep.
466
00:25:48,120 --> 00:25:52,590
And, uh, a quote I heard a while
back, it's not a crime to own money.
467
00:25:52,590 --> 00:25:54,000
If it was we'd all be in jail.
468
00:25:54,810 --> 00:26:00,360
'cause, you know, we all own money, your
mortgage, your car, your whatever, your
469
00:26:00,360 --> 00:26:02,640
credit card, let's say your student loan.
470
00:26:02,650 --> 00:26:04,050
So we all own money.
471
00:26:04,260 --> 00:26:05,550
You're not going to jail.
472
00:26:05,550 --> 00:26:08,460
And there, there are ways
to manage it and pay it off.
473
00:26:08,640 --> 00:26:12,090
Uh, well, it can, my first episode,
we did a history lesson at it in the
474
00:26:12,090 --> 00:26:15,270
past, they were jails for this sort
of thing, but yeah, I think that's a
475
00:26:15,270 --> 00:26:19,130
message that does need to be heard over
and over, or don't go wild just because.
476
00:26:19,980 --> 00:26:22,290
Uh, contract that was
entered into in good faith.
477
00:26:22,560 --> 00:26:25,800
Turns out you couldn't afford the
debt, or you got out of control.
478
00:26:26,100 --> 00:26:29,459
You know, that was a risk that
was taken knowingly by the bank.
479
00:26:29,490 --> 00:26:33,149
So at some point we do need
to just get rid of that.
480
00:26:34,110 --> 00:26:36,090
Um, but James, thank you very much.
481
00:26:36,300 --> 00:26:42,210
If consumers or anybody really wants to
learn more about how to work with debt MD,
482
00:26:42,420 --> 00:26:47,070
what's the best place for them to contact
you or to learn more about your business?
483
00:26:47,220 --> 00:26:54,180
Our website it's www dot
debt, M D D E B T M d.com.
484
00:26:54,840 --> 00:26:59,340
We have a great blog with a lot
of free resources, calculators.
485
00:26:59,640 --> 00:27:03,300
And if you are somebody who isn't
sure what to do with their debt,
486
00:27:03,420 --> 00:27:05,460
you know, feel free to take a look.
487
00:27:05,460 --> 00:27:07,860
And, uh, Brandon, thank you for having me.
488
00:27:07,860 --> 00:27:09,690
I thought this was a great discussion.
489
00:27:10,370 --> 00:27:10,610
Yeah.
490
00:27:10,610 --> 00:27:12,380
And hopefully we can do it again.
491
00:27:12,620 --> 00:27:13,400
Yeah, definitely.
492
00:27:14,030 --> 00:27:15,410
And thank you all for listening.
493
00:27:15,680 --> 00:27:19,100
If you haven't done so already, like
share and subscribe to the show,
494
00:27:19,610 --> 00:27:23,090
how to lend money to strangers is
written, hosted, and edited by myself.
495
00:27:23,120 --> 00:27:26,000
Brendan lick range, the theme
tune and show music is by.
496
00:27:27,074 --> 00:27:30,705
And you can find show notes, written
transcripts, more in depth articles and
497
00:27:30,705 --> 00:27:37,514
details on how to book me for speaking
engagements@wwwdotourtolendmoneytostrangers.show.
498
00:27:38,175 --> 00:27:38,985
I'll see you again.
499
00:27:39,254 --> 00:27:40,004
Next Thursday.
500
00:28:04,375 --> 00:28:07,435
it's me again, just in case you've
had your full of lending talk.
501
00:28:07,825 --> 00:28:10,945
Did you know that I've also published
two pulpy action, adventure, thriller.
502
00:28:12,135 --> 00:28:16,485
Dry and butterfly hill are both available
as e-books paperbacks and audio books
503
00:28:16,515 --> 00:28:18,735
from Amazon and other online retailers.
504
00:28:19,365 --> 00:28:21,915
They're not Shakespeare, but
they're not expensive either.
505
00:28:22,275 --> 00:28:26,955
And Ford Clarion reviews compare, drop to
Clive Casper turning Raiders of the lost
506
00:28:26,955 --> 00:28:29,535
Ark into a shoot them up full disclosure.
507
00:28:29,835 --> 00:28:31,295
That was in a three-star reviews.
508
00:28:31,325 --> 00:28:32,555
I'm not sure it was meant to be.
509
00:28:33,480 --> 00:28:36,810
But I think you get the picture
and Hey, I have to move soon.
510
00:28:36,810 --> 00:28:41,400
So if you'd like a free copy, drop
me an email on Brendan at how to
511
00:28:41,400 --> 00:28:45,210
lend money to strangers talk show,
and I'll send one over to save
512
00:28:45,210 --> 00:28:47,040
myself from liking it around again.
45727
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