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Technological Promises, Criminal Realities

Napier CEO, Julian Dixon, chatted to Oliver Bullough, journalist and author of the best-selling Moneyland, at the FinCrime World Forum earlier this week.

Napier AI
March 25, 2021

Napier CEO, Julian Dixon, chatted to Oliver Bullough, journalist and author of the best-selling Moneyland, at the FinCrime World Forum earlier this week.

The session was used to delve into big questions about why tackling money laundering is so difficult and unsuccessful, and how AI can potentially be the solution.

Here are some of the key takeaways from their reflections on the challenges and realities of fighting financial crime in today’s world.

Why are we not seeing improvements in our battle against money laundering?

Financial crime hasn’t always been taken that seriously

Financial crime has been around for as long as money and crime itself, but it’s taken two milestones in recent history for it to rise to the top as an issue to be addressed. Firstly, there was the financial crisis of 2008, and secondly, the 9/11 terrorist attacks.

As Oliver pointed out, the very fact that we don’t accurately know how much money is being laundered reflects that money laundering hasn’t historically been taken as seriously as it should.      

Criminals know how to work the system

Money launderers understand how banking systems work and have evolved methods and sophistication to exploit weaknesses. They are great, for example, at getting through the onboarding process. They know that once onboarded, there’s every chance their activity will slip through cracks as time goes on.

Of course, this reveals a fundamental flaw in KYC and activity monitoring. Onboarding takes a snapshot of the client at a particular point in time, and monitoring is often too infrequent to be useful.

That’s why Napier decided to focus on continuous KYC with its Client Activity Review (CAR) solution. CAR takes into account up-to-date customer information to provide a holistic view of the customer and ongoing, meaningful behavioural analytics.

Client Activity Review
Find out how to build a holistic view of your clients in our eBook
Client Activity Review: The Missing Link Between AML and KYC.

The Regtech industry is still in its infancy

The effectiveness of legacy technology in identifying suspicious activity is very limited; probably less than 1% of all money laundered is currently being detected.

At the same time, Regtech companies like Napier, are still in their infancy. Napier is only five years old and bank buying cycles are long. Removing old systems is a huge task and it will take time and leadership to initiate such programmes.

Once deployed, any new system will take more time to train and optimise. Artificial intelligence provides a solution for detecting money laundering, but it isn’t a quick fix or panacea.    


How can artificial intelligence improve the detection of money laundering?

Artificial intelligence strengthens compliance teams

Artificial intelligence can do what would otherwise take tens of thousands of people. It adds invisible hands to compliance departments so data can be analysed in different ways. For example, artificial intelligence can effortlessly compare an account against peers and detect any temporal changes.

Artificial intelligence detects innovative criminal behaviour

Criminals are highly motivated to find new ways to launder money. And while rules are an important tool in the toolbox for detecting suspicious activity, they can only detect what we already know about money laundering.

This is where artificial intelligence really comes into itself, since it is able to detect the unknown unknowns: new suspicious behaviour that slips past the rules. Artificial intelligence looks at all data and detects the anomalous transactions that humans can’t see.

How can we improve our fight against financial crime?

Develop useable artificial intelligence

Financial institutions need anti money laundering systems that are accessible to all. The challenge at Napier is taking very complex things and making them easy and empowering to use. We democratise artificial intelligence so clients can change their rules and settings without the expertise and support of a data scientist. Usability brings the cost of use right down, so systems become so much more accessible to all.

Encourage widespread artificial intelligence adoption

Artificial intelligence needs to be adopted by all involved in financial crime, including financial institutions, crime agencies and the regulators.

Regulators are starting to look much more closely at the benefits artificial intelligence can bring, and Napier welcomes any conversations around how they can adopt new technology. Ultimately, this is a race against criminals who are technologically enabled with infinite budgets. Tech is the biggest weapon to find crime and prosecute it. This is a journey we all need to take together.

Make modern tech mandatory

Rather than just advising firms should use modern tech, regulators need to introduce a programme that mandates its use to fight financial crime.

Regulators should also focus on those banks that repeatedly fail to comply. It’s important that these banks are brought up to speed with modern tech.

Importantly though, new tech needs to be deployed correctly. A very good system put in badly is worse than a not so good system put in correctly.

Share information and intelligence

Ultimately, there needs to be more information and intelligence sharing to increase the detection of criminal activity. SARs are a great example of the dysfunctional silos: once a SAR is filed, there is never any feedback on the outcome. This is a shame because such feedback would be really helpful for optimising monitoring activities.

Watch the replay of their incredible discssion here

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