

Big Data + Machine Learning = Scared banks - magoghm
http://pandodaily.com/2012/02/27/big-data-machine-learning-scared-banks/

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casca
Wonga is a great example of a company taking advantage of people who are too
desperate to have a choice and feel that their local loan-shark is too
inexpensive for them.

The banks are not scared, they're just currently unwilling to plumb the moral
depths that Wonga is.

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ahi
Wonga is a rather poor example. They charge interest rates > 4000%. At that
APR you can hand out loans to fourth graders and still make bank.

edit: first attempt at finding a payday lender with cheaper rates was a
success: 600% <http://www.paydayone.com/texas-loan-cost-and-terms.aspx>

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jgrahamc
Perhaps, but the banks are also big Big Data users. My old company, Causata,
had lots of relationships with banks wanting to unlock the value in their
data.

It's true that startups will always challenge big businesses (such as banks),
but don't think the banks aren't data savvy. In fact, they have a tremendous
history of using computer systems to process and analyze data.

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mcfunley
I can't read this kind of thing without wondering who these ML experts are
that feel personally fulfilled putting their skills to work for 4000% APR
payday loans. ML skills are in demand in a lot of industries that aren't
directly or openly fucking the desperate.

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rglullis
The payday loans are only that high because the associated risks are immense.
And this is precisely why you need to have ML experts working on this problem.

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rbarooah
First - I don't know anything about Wonga, nor do I think that vulnerable
people being forced into needing a loan at enormously high interest rates is
somehow a good thing for society.

However, as I read the comments here simply condemning payday loans without
further explanation, I find myself wondering whether anyone has a better
suggestion?

A 4000% interest loan might seem like a terrible deal, but simply being
evicted, or not being repair a vehicle essential for work could far more
costly. If happens occasionally and it really is paid back at payday, I can
see it being a lifeline.

The article suggests that the interest rate is basically directly related to
the default rate, and that ML is enabling better credit assessments, and thus
lowering the default rate and interest rates correspondingly. The fact that
there are now competitors in the market should keep pressure on this.

It sounds to me that the ML experts are contributing to making loans available
more cheaply to those who need them and can pay them back, potentially helping
people who have a job not to fall into even worse poverty.

Again, I think that the poverty trap is an abhorrent thing for society, but it
sounds as though ML experts are making the payday loan industry less harmful.
Am I missing something?

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nuje
Ugh. Don't they have laws against usury in UK?

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kolektiv
Disappointingly not. In fact recent government commissioned studies
recommended not regulating this further for fear of driving customers to more
unscrupulous lenders (presumably ones without flashy offices and good
marketing - not actually more expensive ones, which are hard to find).

It's pretty disgraceful. Thankfully it is beginning to be flagged up as more
of a problem as some of the better newspapers are beginning to do some proper
investigative reporting.

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bdg
A bank unable to provide value to their customers because a core technology
they operate on daily changes is a bank that has lots of be afraid of.

These large business need to stop clawing to fading paradigms of the past and
keep re-focusing on showing me why they're worth my money. This is the
critical flaw of the so many industries we see fall. Perhaps the best example
is the music industry's massive efforts to fight what their customers want.

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retube
How do Wonga et al tie a borrower to his facebook/twitter/osm account? And
then how do they get the data for an account?

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illumen
They buy it.

