馃攳
Why micro-lenders are investing in Africa | Thought Connect - YouTube
Channel: GrowZania
[0]
languid people thank you very much for
[3]
tuning in to our Channel
[4]
today's video is about fintechs hope you
[7]
enjoy fintechs I imagine everywhere and
[20]
the industry is growing very rapidly
[22]
according to a report published by the
[25]
Institute of Chartered Accountants
[26]
Africa FinTech is expected to grow 15
[29]
times from 200 million dollars to 3
[32]
billion dollars by the year 2020 with
[35]
Kenya Nigeria and South Africa as the
[37]
main countries the FinTech value system
[41]
can be divided into two main segments
[43]
the fastest payment where the fintechs
[45]
provide payment infrastructure for
[47]
individuals and businesses here we have
[50]
services such as PayPal a leap a peso
[53]
PAP and Mobile Money giant m-pesa the
[56]
second is mobile lending this is where
[59]
fintechs provide access to microloans
[61]
competing in a segment that banks and
[63]
other formal lenders often shy away from
[70]
[Music]
[72]
micro lending is often referred to as
[74]
microcredit and it is the lending of
[77]
small amounts of money to individuals or
[79]
businesses in micro lending payment
[82]
generation is often between one to three
[83]
months and the lenders charge monthly
[86]
interest rates which they refer to as
[87]
access fees and range between one and a
[90]
half to fifteen percent this interest
[93]
rates when annualized come to between
[95]
eighteen and two hundred percent which
[97]
is extremely high this is when compared
[100]
to the average annual interest rate of
[102]
between 10 and 50 percent that is
[104]
charged by banks with in sub-saharan
[106]
Africa fintechs are attracted to micro
[110]
lending not only for the lucrative
[112]
returns but also because with the use of
[114]
technology they are able to use big data
[117]
that they can package and sell in this
[120]
21st century data is king and any
[123]
company that has access to leads can
[125]
turn it into gold though the players
[132]
vary by country the big players across
[134]
the continent are Tala branch zidisha
[137]
Oh cash berry get box and many more
[148]
[Music]
[149]
in developing countries access to credit
[152]
is limited this is because many people
[155]
in developing countries rely on informal
[158]
and often inconsistent sources of income
[160]
that's classifying them as high-risk for
[162]
the tradition of banks and other formal
[164]
lenders digital micro lenders are thus
[166]
attractive to this borrowers because
[168]
they offer loans to millions if not
[170]
billions of Africans who banks often
[173]
turn away why do I understand this
[175]
people away this is because banks rely
[177]
on traditional methods to assess the
[179]
creditworthiness of the borrower's this
[181]
includes relying on previous following
[182]
history meaning that those with less
[184]
than ideal repayment history for
[186]
previous loans are turned away and what
[188]
happens to the ones who have never
[189]
borrowed before they have no data and
[191]
this is why they also turned away
[194]
digital lenders on the other hand use
[196]
big data to do credit scoring they do
[199]
not rely on credit repayment history or
[201]
any credit reference bureaus to issue
[203]
loans so they can reach this borrowers
[205]
that banks Stanaway
[208]
the second reason why borrowers turn to
[210]
this digital micro lenders is because
[212]
they offer shorter loan processing times
[215]
how do they do that it's because they
[217]
use big data to do credit scoring
[219]
therefore they can turn around loan
[221]
applications within an hour maximum one
[223]
day this enhances the appeal of micro
[226]
lenders who people often result to in
[228]
situations where they need the cash
[229]
urgently the third reason is because
[232]
financial information is extremely
[234]
complicated and nobody understands this
[236]
better than micro lenders so they
[238]
package the information with simpler
[240]
messaging that borrowers can easily
[242]
understand a good example is the lender
[244]
may states that you can borrow up to
[246]
$100 and repay within one month at an
[249]
access fee of $10 this simple statement
[251]
cleverly hides the interest rate and at
[254]
the same time is easy for most borrowers
[256]
to understand
[262]
fintechs managed lending risk in two
[265]
ways first is that they manage the
[267]
borrower's limits based on their
[268]
previous borrowing history borrowers
[270]
often often did low limits when they
[272]
first sign up for an account and this
[274]
limit is gradually increased and he
[276]
continued to repay their loans some
[278]
lenders even require the borrower's to
[279]
share evidence of how they use the cash
[281]
by for example taking photos of their
[284]
businesses or other investments that
[286]
they made with the cash that link
[287]
borrowed the second way that free checks
[289]
manage risk is through data fin text and
[292]
data that they collect into gold by
[294]
using it to do credit scoring before
[296]
proving the loans in traditional lending
[298]
banks and financial institution rely on
[300]
data from credit reference bureaus or
[303]
credit info sharing agreements that they
[305]
have between themselves however it micro
[307]
lending they use the individuals digital
[309]
footprint to do credit scoring what type
[312]
of data do fintechs collects let's look
[314]
at that
[315]
so fintechs collect data around the
[317]
borrowers mobile phone model how
[319]
frequently the borrower changes their
[320]
phone the time that the borrower spends
[322]
on the Internet the borrower's contacts
[324]
and they use this context to define the
[326]
borrower's network and the risk profile
[328]
they collect the borrower's location
[330]
whether they live in and happen or a
[332]
rural area they can even tell the
[334]
borough's location during the day in the
[337]
evening during the holidays and any
[339]
other patterns that they may be
[340]
interested in by collecting other
[341]
information such as SMS messages they
[344]
can even find out the individuals
[345]
purchase buttons and use this to assess
[348]
whether the person has a regular source
[349]
of income or not they also collect the
[352]
person's call patterns how do they use
[354]
the call patterns for example and
[356]
individually the high volume of
[357]
international calls may signify that
[360]
they have relatively high standard of
[361]
living
[365]
an economist by the name Muhammad Yunus
[369]
in the early 1970s began offering small
[372]
loans to women in Bangladesh to help
[374]
them start income generating projects to
[376]
support themselves and their families
[378]
this was the path of micro lending since
[381]
then many microfinance institutions have
[383]
been started across the world this is
[385]
because access to credit enables the
[387]
poor become entrepreneurs thus
[389]
increasing their earnings and improving
[391]
their quality of life it is for this
[393]
reason that many micro lenders provide
[395]
some form of peer support network
[397]
financial education and networking
[399]
opportunities to help the borrowers real
[401]
successful businesses however whether
[404]
the money poured through this digital
[406]
lending platform is actually used to
[408]
improve the quality of life or not
[409]
remains a big point of discussion let us
[412]
know in the comments what you think
[413]
about digital lending do you think it is
[416]
achieving its broad objective of
[417]
improving the quality of life of
[419]
borrowers do let us know and don't
[421]
forget to subscribe to our Channel
[425]
[Music]
Most Recent Videos:
You can go back to the homepage right here: Homepage