5 ms·

It's not surprising that a technology where "we don't really understand how it all works under the covers" is anathema to an industry where nearly everything mu

It's not surprising that a technology where "we don't really understand how it all works under the covers" is anathema to an industry where nearly everything must be auditable. In finance the reasoning behind a decision (e.g. to extend a loan, to do a deal, to find a business, etc.) is nearly as important as the decision itself, and "because the black box machine told us so" is not a sufficient explanation.

kmeisthax 2y ago
Also, HFT firms are more latency sensitive than iamchris4life[0]. No way in hell they're going to throw all their finance data through an autoregressive transformer model and an HTTP API when they're already spending $$$ on FPGAs to run their algorithms a few milliseconds faster. [0] Top-level US DanceDanceRevolution player.
- rfoo 2y ago
  But not everyone in the algorithmic trading game plays this "HFT firms running algorithm on FPGAs for tens / a few hundred nanoseconds advantage". For med frequency the compute budget is enough.
- bostik 2y ago
  HFT firms have been using ML and AI for years. They simply called those things with a different name: statistics. The result models are then fast enough for them to make trading decisions in less than a microsecond.
_the_inflator 2y ago
You are totally right. Information obligations and liability are the critical issues here. No more luring customers into financial constructs; really, no one understands, but the bank wins in the end. Informed decision-making is, by definition, boring. It appeals to the rational decision-making process. I think this can be a chance for banks to virtually stand out. Constraints are the breeding ground for innovations. ;)
pylua 2y ago
Since making a decision in itself is subjective, does it matter if ai makes a decision ? Two bankers may have two conclusions on the same data, or may have two different risk tolerances or strategies. As for audibility, all of the data is kept and archived. Ai is not deleting the data that is captured. I’m certain you could use an llm to generate convincing arguments either way based on an application. For rejections they should be manually reviewed in most cases to cover your liability.
- hn_throwaway_99 2y ago
  > Since making a decision in itself is subjective Not exactly, and that's the whole point. E.g. the whole reason things like credit scores exist is to provide an objective, calculable metric that determines if someone should be offered credit. And, critically, how that metric is generated follows some straightforward rules, so that it can be shown to be free of illegal biases. Obviously there are other decisions that aren't simply boiled down to a single number, but in general even those decisions that include some subjectivity try to provide clear, objective rationale as to why a decision was taken.
  - pylua 2y ago
    If things are so objective, what is the role of ai in this process ?

kmeisthax 2y ago

Also, HFT firms are more latency sensitive than iamchris4life[0]. No way in hell they're going to throw all their finance data through an autoregressive transformer model and an HTTP API when they're already spending $$$ on FPGAs to run their algorithms a few milliseconds faster. [0] Top-level US DanceDanceRevolution player.

rfoo 2y ago
But not everyone in the algorithmic trading game plays this "HFT firms running algorithm on FPGAs for tens / a few hundred nanoseconds advantage". For med frequency the compute budget is enough.
bostik 2y ago
HFT firms have been using ML and AI for years. They simply called those things with a different name: statistics. The result models are then fast enough for them to make trading decisions in less than a microsecond.

_the_inflator 2y ago

You are totally right. Information obligations and liability are the critical issues here. No more luring customers into financial constructs; really, no one understands, but the bank wins in the end. Informed decision-making is, by definition, boring. It appeals to the rational decision-making process. I think this can be a chance for banks to virtually stand out. Constraints are the breeding ground for innovations. ;)

pylua 2y ago

Since making a decision in itself is subjective, does it matter if ai makes a decision ? Two bankers may have two conclusions on the same data, or may have two different risk tolerances or strategies. As for audibility, all of the data is kept and archived. Ai is not deleting the data that is captured. I’m certain you could use an llm to generate convincing arguments either way based on an application. For rejections they should be manually reviewed in most cases to cover your liability.

hn_throwaway_99 2y ago
> Since making a decision in itself is subjective Not exactly, and that's the whole point. E.g. the whole reason things like credit scores exist is to provide an objective, calculable metric that determines if someone should be offered credit. And, critically, how that metric is generated follows some straightforward rules, so that it can be shown to be free of illegal biases. Obviously there are other decisions that aren't simply boiled down to a single number, but in general even those decisions that include some subjectivity try to provide clear, objective rationale as to why a decision was taken.
- pylua 2y ago
  If things are so objective, what is the role of ai in this process ?