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IMF researchers: digital footprint yields better credit assessment

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Re: IMF researchers: digital footprint yields better credit assessment

#31

Post by da_big_ghey »

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.

Without "making up" a headline, and were I to have used the original headline of "What is Really New in Fintech", I would not have considered this a useful submission due to the complete lack of information conveyed by the headline. The article contained important info but the headline was meaningless, so I did my best to come up with something. I guess my first attempt fell short.

Re: IMF researchers: digital footprint yields better credit assessment

#32

Post by throwaway189262 »

thegrimmest wrote: post #17
hn_throwaway_99 wrote: post #15

I hope that regulatory agencies start cracking down on these "alternative sources" for credit-worthiness data. Researchers have shown how it's very easy to attribute things like political party, race, sexuality, etc., things that are often illegal to take into consideration when determining credit, to other things like where you live, TV shows you like, apps you have on your phone, etc. And strangely (or not) this bl…

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 people who follow NBA players on twitter are more likely to default. It then assigns then higher interest rates. Well, it turns out that poor urban black people are far more likely to be interested in the NBA than the average person. Probably because it's one of the only sports you can play in a parking lot. The model decides to raise interest rates and cut lending to most black people.

"Perfect" credit worthiness modelling is only going to be beneficial to rich white and asian people. Essentially favoring the stereotypically richest ethnic groups.

This is extremely problematic for any sort of equality initiatives.

Treating everyone the same regardless of means is definitely socialist. It's the same as removing the pre-existing conditions exclusions for health insurance. It favors the unfortunate at the expense of the fortunate.

I'm not going to go into whether that is good or bad for society but I ask you to consider the extreme, historic level wealth inequality in the US where 1% of the population has over half the money.

Re: IMF researchers: digital footprint yields better credit assessment

#33

Post by slg »

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…

That is a good summary. An analogy I might add that could further clarify things would be preexisting condition protections for health insurance. Preventing insurance companies from turning down people who they know will require expensive medical care is going to lead to worse pricing for the rest of us. However much of society has decided that is a cost worth enduring in the name of fairness.

Re: IMF researchers: digital footprint yields better credit assessment

#35

Post by insert_coin »

hammock wrote: post #30
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…

So should we use the algorithms to charge different races different interest rates? Or should we not use them. And address the problems you mention? Because in the previous comment it sounded like they wanted to use them with applause.

Using the algorithm is addressing the problems by not hiding them.

Re: IMF researchers: digital footprint yields better credit assessment

#36

Post by hntrader »

drtillberg wrote: post #28
hn_throwaway_99 wrote: post #15

I hope that regulatory agencies start cracking down on these "alternative sources" for credit-worthiness data. Researchers have shown how it's very easy to attribute things like political party, race, sexuality, etc., things that are often illegal to take into consideration when determining credit, to other things like where you live, TV shows you like, apps you have on your phone, etc. And strangely (or not) this bl…

This. Slippery slope to denying credit based on a consumer's decision to avoid using Facebook or to search using DuckDuckGo.

DDG is more popular in the tech-literate crowd, most of whom are earning large salaries and therefore we'd expect that DDG usage should be positively (not negatively) correlated with credit worthiness

Re: IMF researchers: digital footprint yields better credit assessment

#37

Post by anothernewdude »

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.

No, you have to allow the source to do the editorializing, because that's so much better.

Re: IMF researchers: digital footprint yields better credit assessment

#38

Post by hammock »

insert_coin wrote: post #35
hammock wrote: post #30

Earlier quoted context omitted.

So should we use the algorithms to charge different races different interest rates? Or should we not use them. And address the problems you mention? Because in the previous comment it sounded like they wanted to use them with applause.

Using the algorithm is addressing the problems by not hiding them.

Should we legalize drunk driving, and address the problem by trying to solve alcoholism?

Re: IMF researchers: digital footprint yields better credit assessment

#39

Post by elil17 »

Hacker News headlines of the future:

Chrome extension which changes your user agent request header to get you a better mortgage

Googling "Fun activities that don't cost money" increases your interest rates, study finds

Samsung partners with Equifax to offer better car loans to users who upgrade to a new phone

Re: IMF researchers: digital footprint yields better credit assessment

#40

Post by aneemzic »

thegrimmest wrote: post #17
hn_throwaway_99 wrote: post #15

I hope that regulatory agencies start cracking down on these "alternative sources" for credit-worthiness data. Researchers have shown how it's very easy to attribute things like political party, race, sexuality, etc., things that are often illegal to take into consideration when determining credit, to other things like where you live, TV shows you like, apps you have on your phone, etc. And strangely (or not) this bl…

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 physical trait they share with others. Not to mention, we wouldn't even understand why there's a correlation in the first place. Maybe tall people are 30% likely to have some unknown gene, why should the other 70% of tall people who don't have the gene be treated the same?

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