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Morris-Cotterill: Regulations and "AI" - the fundamental flaw.

Friday, 31 January, 2025 - 01:01

I've been reading about the demands that regulators place on financial institutions to adopt so-called "AI". Often, the regulators are pointing to individual failures in customer acquisition or continuing monitoring and making the leap to say that such failures are preventable if the financial institutions use "Artificial Intelligence".

They say that legacy tech doesn't work and that AI is, in effect, the saviour of an entire industry.

They are fundamentally wrong and in this demonstrate a fundamental lack of understanding of the tech and of the way that both KYC and monitoring work.

The failure isn't with the tech, it's with the people who program the tech and it's getting worse not better.

So-called "data scientists" are being churned out of colleges and universities with literally zero knowledge of the subjects they are designing algorithms for. They are not staying in post long enough to learn because there is a shortage and they can move every few weeks for more money. They do not, and do not have time, to engage with genuine experts in the subjects they are designing for.

Almost everyday a new "AI company is set up in financial crime, in cybersecurity or in some such where algorithms are an essential part of the product: but the algo-authors don't know what they are looking for beyond what they can learn in a few hours. And worse, what they design almost never properly integrates with what is already there.

Nigel Morris-Cotterill is at www.countermoneylaundering.com

So-called machine learning and generative computing cannot perform better than an approximation and often far worse, especially when the machine fabricates responses.

The fundamental need is for properly trained and experienced people working in financial institutions, given the authority to make difficult decisions. This is rarely binary and, however it is dressed up, all computerised decisions are binary.

Algorithms are good - if the people creating them are. Too often, they are not.

Many RegTech companies are based around the work of a single data scientist with a team of algo-authors. So only one person really understands the direction of the product.

These points are only a small part of the way that regulators are forcing financial institutions into a regime where future failures are inevitable.

Does algorithmic analysis have its place? Yes, of course it does and I support it. But it does not and cannot think and that fact needs to be recognised.

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