Genuinely surprised that "bank managers" either exist or have any say in loan decisions. In the UK it appears to be pretty much entirely computerised, with a small amount of oversight from teams of analysts if the computer decision is borderline. Different elsewhere?
‘Simple’ AI can anticipate bank managers’ loan decisions to over 95% accuracy
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Re: ‘Simple’ AI can anticipate bank managers’ loan decisions to over 95% accuracy
#22minimum_credit_score = Loan.joins(:borrower).where("loans.default = true").average("borrowers.credit_score") if loan_applicant.credit_score > minimum_credit_score decision = "approve" else decision = "reject" end
Would a linear decision barrier not be fit by the logistics model?
Re: ‘Simple’ AI can anticipate bank managers’ loan decisions to over 95% accuracy
#23Loan decision is relatively straightforward algorithmic process. I see no reason why AI is needed or wouldn't give similar answers.
Shouldn't the sentence be flipped in that case? I see no reason why expensive human is needed or wouldn't give similar answers.
Re: ‘Simple’ AI can anticipate bank managers’ loan decisions to over 95% accuracy
#24This isn't surprising. Most 'AI' comes down to correlating a small number of variables (one or two) with a prediction target. The real benefit of any form of machine learning is detecting functional relationships between variables (ie, "when this AND NOT that OR this"). It's just that these relationships don't provide a real benefit in 99/100 real world use cases. In the case of a loan, if the credit score is high th…
Yes. But there is also an interesting failure mode - people don't bother applying if they don't think they'll get accepted. So presumably even just a "YES" will be a fairly good model of what actually happens without necessarily capturing the real model that the bank is using. A 95% accuracy rate isn't necessarily very good because of this effect (it might be, it just isn't certain).
Re: ‘Simple’ AI can anticipate bank managers’ loan decisions to over 95% accuracy
#25This headline and article are horrible and misrepresent the problem and the outcome.
The paper is about the manual process of re-assigning a credit score on a scale of 1 to 15 based on other customer criteria. Really the fact that this process exists at all shows that their initial credit scoring approach is flawed or too simplistic. The argument of "just replace it with an if statement" does not hold up in this scenario.
So this is not a "if number big lend. If number small no lend" problem. Its a 15 way multi-class classification problem. They even give a baseline for what happens if they randomly pick or always pick the biggest class in the paper
> As is typical in machine learning we also report the Accuracy p-value computed from a one-sided test (Kuhn et al., 2008) which compares the prediction accuracy to the "no information rate", which is the largest class percentage in the data (23.85%).
So yeah, 95% is somewhat better than 23.85%.
I agree with the general sentiment that is is likely a fairly straight forward problem to predict if you are familiar with the bank's operating procedures as there is no way these individuals are making their own risk models and independent decisions. They are there to follow the rules and provide human accountability.
An error analysis on the items the model couldn't predict would definitely have been most interesting.
Re: ‘Simple’ AI can anticipate bank managers’ loan decisions to over 95% accuracy
#26Loan decision is relatively straightforward algorithmic process. I see no reason why AI is needed or wouldn't give similar answers.
Shouldn't the sentence be flipped in that case? I see no reason why expensive human is needed or wouldn't give similar answers.
The point is that it can be solved with simple algorithms. No expensive human nor AI needed.
Re: ‘Simple’ AI can anticipate bank managers’ loan decisions to over 95% accuracy
#27Loan decision is relatively straightforward algorithmic process. I see no reason why AI is needed or wouldn't give similar answers.
Shouldn't the sentence be flipped in that case? I see no reason why expensive human is needed or wouldn't give similar answers.
Mostly they are there as sanity check. Just collect the numbers and input in the system. Humans really can't be trusted, especially with money. So someone in the loop have to check can the information provided be trusted.
Re: ‘Simple’ AI can anticipate bank managers’ loan decisions to over 95% accuracy
#28Earlier quoted context omitted.
Shouldn't the sentence be flipped in that case? I see no reason why expensive human is needed or wouldn't give similar answers.
The point is that it can be solved with simple algorithms. No expensive human nor AI needed.
Not to forget that AI can be essentially a black or grey box. You have some inputs and you have some outputs. Mostly correct, but what if that fails catastrophically? At least algorithms, in this case can be mostly walked through by regular humans and errors possibly be noted. Unless the complexity isn't idiotic in charge of profits.
Re: ‘Simple’ AI can anticipate bank managers’ loan decisions to over 95% accuracy
#29This isn't surprising. Most 'AI' comes down to correlating a small number of variables (one or two) with a prediction target. The real benefit of any form of machine learning is detecting functional relationships between variables (ie, "when this AND NOT that OR this"). It's just that these relationships don't provide a real benefit in 99/100 real world use cases. In the case of a loan, if the credit score is high th…
Yes. But there is also an interesting failure mode - people don't bother applying if they don't think they'll get accepted. So presumably even just a "YES" will be a fairly good model of what actually happens without necessarily capturing the real model that the bank is using. A 95% accuracy rate isn't necessarily very good because of this effect (it might be, it just isn't certain).
My SO used to work in a bank in the business loan securities back office. Believe me. Lots of people and businesses apply even if they themselves see no realistic chance of receiving a loan.
And in private non business customers there are even a significant amount that have less than nothing to their name, living of welfare and still don't see, why they should not receive a loan from the bank for the newest iPhone. Or a new car. Or TV because "football's coming home".
Excuse my snarkiness, but the stories she told me from her apprenticeship in the bank, when she was customer facing were not painting a good picture of humans (Btw. well off or not). But that is probably the case in any consumer facing job.
Re: ‘Simple’ AI can anticipate bank managers’ loan decisions to over 95% accuracy
#30Loan decision is relatively straightforward algorithmic process. I see no reason why AI is needed or wouldn't give similar answers.
Shouldn't the sentence be flipped in that case? I see no reason why expensive human is needed or wouldn't give similar answers.
Those days when you dress up, go to your local bank and the banker makes a decision based on their 'knowledge' about you, are long long gone. Loan applications are standardised and things like credit scores play big role. Things are probably a little bit different when we are talking 7-8 digit loans.