'Don’t learn to code, learn to automate,' said the coder Erik Dietrich.
Clive Thompson, a tech journalist who is a contributing writer for the New York Times Magazine and a columnist for Wired quoted Dietrich in his guest post Ten Lessons I Learned While Teaching Myself to Code.
Thompson went on to say “... computers are amazing at doing dull, repetitive tasks. They’re also great at being precise. Since we humans are terrible at doing dull tasks and quite bad at being precise, this makes us a match made in heaven.”
Although Thompson’s article focuses on the benefits of learning to code, there is a certain truth in this match made in heaven.
From chatbots and digital assistants to facial recognition or biometric scanners, computers are not just taking on dull, repetitive tasks. As we know, computers and technology already play an enormous part of our daily lives, doing the things we are either terrible at, or unable to do.
The AI for Business special report published in The Times examines how artificial intelligence (AI) will continue to influence businesses and operations around the globe, while also impacting our everyday lives in ways some of us are not even aware.
For instance, unlocking your phone. This is something most of us do first thing every morning. But did you know the that the simple act of looking at a smartphone to unlock it relies on AI?
Challenges in implementing AI
The challenge for businesses however has been that over the past few years, where admittedly the prevalence and use of AI has grown, there is still a lot of uncertainty about the true value of it and how to implement it successfully. So much so, that perhaps a lot of businesses have come to question whether the benefits of AI outweigh the challenges.
And that is fair question. There are a lot of challenges to overcome.
At Napier, we know that AI has huge potential benefits for transaction monitoring. But we also understand that it isn’t an overnight project. That’s why the way we introduce new systems is as important as the new systems themselves.
We believe the key rests in a gradual, well thought out introduction, which allows for systems and staff to adapt and evolve together. Old systems cannot be replaced overnight. There will be a lot of work to do, but the end result will be a far more effective and efficient transaction monitoring system.
Making AI accessible to compliance analysts
In our piece published in the AI for Business special report we touch on how important it is to make AI accessible to staff so that AI is easy to understand and act upon.
It is inefficient to have to rely on calling in super-skilled analysts such as data scientists and coders (typically at great cost too) to have to make sense of the AI. We make it our business to have AI insights delivered in plain English to help analysts work smarter.
Finally, we make the case for AI coming into its own in the fight against financial crime, as it can help reduce the cost of compliance and deliver insights in a fraction of the time a human can - enhancing an analyst's capabilities rather than replacing them.
Taking Thompson’s claim that computers are amazing at doing dull, repetitive tasks a step further, Luca Primerano our Chief AI Officer says:
“An AI engine can look at the transactional activities of customers much better than a human. It’s a completely independent set of lenses that can go through billions of transactions across multiple dimensions to detect anomalies, something that would take humans years to complete at great cost.”
Read the Times AI for Business special report.
If you would like to learn more about our products, like transaction monitoring; or how AI can help your transform your AML capabilities, please contact us for a demo.
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