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When the data is wrong, it's people that fix problems.

FCRO Subsection: 
Nigel Morris-Cotterill

"Go back to the data." "The answer's in the data." "Data is the key".


Until it goes wrong.

The return of Mercedes-AMG Petronas Formula One Team to the sharp end of Formula One yesterday is interesting not because of the obvious hole the team's absence has left at the front, denying us even better racing, but because it shows that even the most professional team can end up in the weeds and have no idea why.

As George Russell said some weeks ago"we know there's a good car in there, we just can't find it".

At the heart of the problem was that the tech produced false positives. All the analysis and the eventual product was based on those false positives.

The wind tunnel accurately showed the airflow over the car but not under it. Once it ran outside, in real world conditions, the car was slow and, worse, it bounced up and down as air cushions built up and dissipated underneath it.

The response, as in so may areas, was "go back to the data" but the data remained bad and new data wasn't getting better: in techy terms there was no correlation between the data and the real world.

Worse: every change that the data suggested worked until it didn't. That only acted to increase the sense of confusion: as in many other things, inconsistency is the enemy of success.

In Barcelona over the past weekend, there was consistency. But that consistency doesn't mean that the problems are solved: it means that, seemingly, there is a direction of travel to get out of the weeds.

This is where tech "solutions" are often given more credit than they deserve.

It was people that worked out what was wrong and where improvements might be made. And it was people, Russell and Lewis Hamilton, that provided - in addition to visual data and information from on-board sensors - the operable intelligence that ultimately saw a consistent weekend.

But, as with all things, the first question is whether it's a sustainable and "projectable" course of action or whether it was track and conditions specific.

In short, there's a need to be sure that any improvement is not a false dawn.

And that's why it's a vital lesson: whatever tech you have in your Financial Crime RIsk and Compliance systems, ultimately, it's going to be the people that work it out, there will be false starts and hopes dashed but it is possible, even when you are lost without a compass, to find a way out and then build on that to achieve success

If you have the right people.

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