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.
[0] Top-level US DanceDanceRevolution player.
For med frequency the compute budget is enough.
The result models are then fast enough for them to make trading decisions in less than a microsecond.
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. ;)
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.
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.