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IMF researchers: digital footprint yields better credit assessment

blogs.imf.org

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Re: IMF researchers: digital footprint yields better credit assessment

#41

Post by dTal »

insert_coin wrote: post #27
thereisnospork wrote: post #21

Earlier quoted context omitted.

I agree with the premise, but the problem is that it gets ethically, uh 'interesting', if you replace 'tall' with say, 'black', in your argument.

I think it gets to the point. If blacks are for some reason (and I am not saying they are I do not know) less likely to pay back loans, then that is the problem that needs addressing. It might be a little painful to admit the huge racial divide but it is real and that is a problem we need to solve, taking the easy way out lying to ourselves only harms society in the long run and destroys the lives of people who canno…

And how do you propose we solve it?

If there's a systematic financial disadvantage experienced by black people, possibly as a result of racism, then continuing to financially disenfranchise them will hardly help, will it? Access to liquid capital is pretty critical if you want to make money, isn't it?

Judgement is notoriously self-fulfilling. The best way to keep someone poor is to treat them like a poor person. The best way to drive someone to crime is to treat them like a criminal. The best way to keep someone ignorant is to treat them like an idiot.

Re: IMF researchers: digital footprint yields better credit assessment

#42

Post by thegrimmest »

throwaway189262 wrote: post #32
thegrimmest wrote: post #17

Earlier quoted context omitted.

If these sources of data are actually more accurate predictors of creditworthiness, then shouln't we be applauding their use? If it so happens that tall people are less likely to repay loans, why is it wrong to charge tall people higher interest? Otherwise aren't we just socializing the cost imposed by artificially fuzzy criteria?

More accurate isn't always good because creditworthiness is all about stereotyping people. Consider this example: lesbians are statistically more likely to divorce. The ML models decides that lesbians are a higher mortgage risk and raises their interest rates. It does this indirectly by raising interest rates on married couples with different last names and owners of Subaru vehicles. In another, the model sees that p…

A lot to unpack here, let me try. Are machine learning algorythms capable of stereotyping people? How accurate does a stereotype have to be before it's a useful predictor?

If these models lead to good data, then what's wrong with them? If people who follow the NBA do in fact default on their loans more, shouldn't they pay higher interest?

I agree that the healthy should not be compelled to subsidize the costs of healthcare for the unhealthy. Can you tell me why it's ethical to force my compliance?

It seems you primarily see things along racial divides, grouping people into black, white, and asian. There are, more nuanced ways to group people, which is exactly what these agorythms are doing.

Also, what's wrong with wealth inequality? I'd be much more concerned about absolute quality of life, which has increased dramatically for everyone in the last half century.

Re: IMF researchers: digital footprint yields better credit assessment

#43

Post by warkdarrior »

insert_coin wrote: post #27
thereisnospork wrote: post #21

Earlier quoted context omitted.

I agree with the premise, but the problem is that it gets ethically, uh 'interesting', if you replace 'tall' with say, 'black', in your argument.

I think it gets to the point. If blacks are for some reason (and I am not saying they are I do not know) less likely to pay back loans, then that is the problem that needs addressing. It might be a little painful to admit the huge racial divide but it is real and that is a problem we need to solve, taking the easy way out lying to ourselves only harms society in the long run and destroys the lives of people who canno…

Of course we should address those problems as we identify them. But solutions may take years, even decades, to take root. What should lenders do in the mean time?

Re: IMF researchers: digital footprint yields better credit assessment

#44

Post by thegrimmest »

pmichaud wrote: post #25
thegrimmest wrote: post #17

Earlier quoted context omitted.

If these sources of data are actually more accurate predictors of creditworthiness, then shouln't we be applauding their use? If it so happens that tall people are less likely to repay loans, why is it wrong to charge tall people higher interest? Otherwise aren't we just socializing the cost imposed by artificially fuzzy criteria?

When I have this conversation with myself, here's what I come up with: Shouldn't we be allowed to everything into account when determining credit worthiness? Even if it's socially uncomfortable? We get locally more accurate pricing / risk assessment that way, but we also create feedback loops that we as a society have decided we want to not contribute to. The cost for this is the pricing inaccuracy which we collectiv…

Well, I personally haven't consented to socializing the cost of anything. I'm not sure what the ethical grounds are for imposing this on me, and in so doing dilluting available accuracy of data about people.

These feedback loops you're referring to, what order are you proposing for your chicken and your egg? What's causing what in your view?

Re: IMF researchers: digital footprint yields better credit assessment

#45

Post by ChrisIsTaken »

da_big_ghey wrote: post #10
dang wrote: post #9

Earlier quoted context omitted.

Submitted title was "IMF says credit score should incorporate browsing history". That was egregious editorializing. Submitters: please don't do that! Cherry-picking the most sensational detail and making that the title is definitely not ok, and fabricating something the article doesn't say is right out! https://news.ycombinator.com/newsguidelines.html When a title buries the lede in favor of bland corporate rhetoric,…

That wasn't intended to be editorializing or picking a sensational detail. Rather, I found that to be the most relevant point and believed that it would be most salient to HN. I certainly wouldn't call it fabrication; it explicitly states that this data could be used to qualify many people for better credit, doubtless via some credit score system or similar. I think this quote best lays out that position: > Recent re…

Tl;Dr.

"The lower strata of society are being forced into precarious employment and debt slavery. (What's new?) Here's how to use a global surveillance apparatus to enable more debt slavery."

Re: IMF researchers: digital footprint yields better credit assessment

#46

Post by hntrader »

aneemzic wrote: post #40
thegrimmest wrote: post #17

Earlier quoted context omitted.

If these sources of data are actually more accurate predictors of creditworthiness, then shouln't we be applauding their use? If it so happens that tall people are less likely to repay loans, why is it wrong to charge tall people higher interest? Otherwise aren't we just socializing the cost imposed by artificially fuzzy criteria?

No. Credit worthiness should be because of an individuals past actions and not some attribute they may have been born with. Why should a tall individual who's never missed a payment have some invisible penalization applied because some other tall people are worse at re-paying loans. Don't you see the issue here? You're penalizing individuals not based on their own measurable behavioral signals, but simply due to some…

We must disambiguate between political objectives and the practice of credit risk modelling.

Credit risk, f(X), is an unknown population function that needs to be estimated using observed data X.

If including tallness into X improves our estimate of f(X), then we've gotten a better model.

You've asserted that X should only contain an individual's past actions instead of their inherent traits such as tallness. This may satisfy certain political objectives, and that's fine if we're being upfront about the underlying motivation, but from an ML perspective your prescription doesn't make much sense unless you have some prior knowledge about the function f(X) that tells you that tallness both isn't relevant and isn't acting as an instrumental variable for some other missing feature.

Unless you have such domain knowledge, you've little business asserting what are appropriate features to use in order to improve model quality.

Re: IMF researchers: digital footprint yields better credit assessment

#47

Post by thegrimmest »

austhrow743 wrote: post #29
thegrimmest wrote: post #17

Earlier quoted context omitted.

If these sources of data are actually more accurate predictors of creditworthiness, then shouln't we be applauding their use? If it so happens that tall people are less likely to repay loans, why is it wrong to charge tall people higher interest? Otherwise aren't we just socializing the cost imposed by artificially fuzzy criteria?

Yes, we are just socialising the cost of different races, sexes, ages, etc being different. Many people like that.

People like many things, not all of them are ethical. Why do you think it's okay to impose this on people who don't consent?

Re: IMF researchers: digital footprint yields better credit assessment

#48

Post by insert_coin »

dTal wrote: post #41
insert_coin wrote: post #27

Earlier quoted context omitted.

I think it gets to the point. If blacks are for some reason (and I am not saying they are I do not know) less likely to pay back loans, then that is the problem that needs addressing. It might be a little painful to admit the huge racial divide but it is real and that is a problem we need to solve, taking the easy way out lying to ourselves only harms society in the long run and destroys the lives of people who canno…

And how do you propose we solve it? If there's a systematic financial disadvantage experienced by black people, possibly as a result of racism, then continuing to financially disenfranchise them will hardly help, will it? Access to liquid capital is pretty critical if you want to make money, isn't it? Judgement is notoriously self-fulfilling. The best way to keep someone poor is to treat them like a poor person. The…

And how did 'give everyone a home loan never mind if they can't afford it' worked out in 2008?

Sometimes I do wonder if people who present the argument you just presented realize that that is exactly how we've been doing things, and it just keep making the problem bigger.

Maybe I'm too much of a romantic, but I still harbor hope at some point they will realize it and begin to contemplate trying something different.

Re: IMF researchers: digital footprint yields better credit assessment

#49

Post by thegrimmest »

aneemzic wrote: post #40
thegrimmest wrote: post #17

Earlier quoted context omitted.

If these sources of data are actually more accurate predictors of creditworthiness, then shouln't we be applauding their use? If it so happens that tall people are less likely to repay loans, why is it wrong to charge tall people higher interest? Otherwise aren't we just socializing the cost imposed by artificially fuzzy criteria?

No. Credit worthiness should be because of an individuals past actions and not some attribute they may have been born with. Why should a tall individual who's never missed a payment have some invisible penalization applied because some other tall people are worse at re-paying loans. Don't you see the issue here? You're penalizing individuals not based on their own measurable behavioral signals, but simply due to some…

The point is that these algorythms do study your behaviour and correlate it with the behaviour of others. These predictions don't have to be 100% accurate to be useful. What's wrong with 70% of tall people benefiting from being associated with the other 30%? This only lasts until someone figures out how they are different and breaks the association right?

Re: IMF researchers: digital footprint yields better credit assessment

#50

Post by dredmorbius »

pvg wrote: post #18
da_big_ghey wrote: post #10

Earlier quoted context omitted.

That wasn't intended to be editorializing or picking a sensational detail. Rather, I found that to be the most relevant point and believed that it would be most salient to HN. I certainly wouldn't call it fabrication; it explicitly states that this data could be used to qualify many people for better credit, doubtless via some credit score system or similar. I think this quote best lays out that position: > Recent re…

Rather, I found that to be the most relevant point That's what editorializing is. You can point out the thing you found salient in a comment, you can find another piece that better represents the interesting thing, etc. You can't make up the title, though.

The HN submission guidelines do allow for changes in title, though usually it's to combat undue sensationalism.

Otherwise please use the original title, unless it is misleading or linkbait; don't editorialize.

https://news.ycombinator.com/newsguidelines.html

In this case, the problem is an excess of bureaucratese, euphemism, jargon, and vagueness.

As Orwell wrote in "Politics and the English Language" on five badly written English passages:

[T]wo qualities are common to all of them. The first is staleness of imagery; the other is lack of precision. The writer either has a meaning and cannot express it, or he inadvertently says something else, or he is almost indifferent as to whether his words mean anything or not. This mixture of vagueness and sheer incompetence is the most marked characteristic of modern English prose, and especially of any kind of political writing. As soon as certain topics are raised, the concrete melts into the abstract and no one seems able to think of turns of speech that are not hackneyed: prose consists less and less of words chosen for the sake of their meaning, and more and more of phrases tacked together like the sections of a prefabricated hen-house.

https://www.orwell.ru/library/essays/politics/english/e_poli...

It's very common to see this tactic used in communications from* organisations or institutions about matters of significant import. Take the recent " Email from Jeff Bezos to employees", as a classic example:

https://www.aboutamazon.com/news/company-news/email-from-jef... (https://news.ycombinator.com/item?id=26006656). The title entirely fails to adequately describe the actual subject.

As is the case with the IMF's blog entry.

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