Can you tell me about Napier and your roles and responsibilities there?
I am the Chief Data Scientist at Napier, where we specialise in financial crime compliance technology that’s transforming compliance for over two hundred financial institutions globally, including tier one banks, payment providers, FX, and crypto providers.
In my role I lead the data science team in the continual innovation, research and development of Napier’s Intelligent Compliance Platform (ICP), which applies next-generation technologies such as artificial intelligence to AML systems to boost operational efficiencies and minimise risk. I also am an advocate for explainability and accessibility in Artificial Intelligence (AI), and a large part of my role involves interpreting regulations and the suitability of Napier’s tech for our clients’ AML requirements.
How does Napier utilise AI in its operations?
Our primary focus is helping banks and financial institutions address money laundering and financial crime risks. AI plays a huge role in this as it can identify patterns within large sets of data – way beyond human capability, or that of legacy technologies – and then present the intelligence that it has learnt from looking at these patterns to make recommendations. This can be easily translated into the role of anti-money laundering (AML) investigations, making AI an important ally in the fight against financial crime.
Why do we need to consider AI when looking to combat financial crime?
You cannot underestimate the levels of criminal activity within the financial sector, and the ambition of criminals seeking to exploit it. Those who have prospered from illegal activity have a vast budget, access to sophisticated technology, and an appetite to continue profiting. Compare that to your average AML officer in a bank, constrained by red tape and legacy tech, and they are completely outgunned. The only way that you can begin to bridge this gap is through rapid digitalisation, especially the application of AI-enhanced technology to empower compliance officers.
How can explainable AI be applied in society, particularly in the anti-financial crime sector?
The strengths of AI lie in its ability to automate and effectively speed up large, complex - but well-defined - processes. Explainability in AI is important because, in order to trust AI, end-users need to be comfortable to not just understand a result but to believe and trust it.
For years, financial institutions have been reticent to use AI technologies, because they could not be understood. This made it difficult to interpret the outputs and build a case based on the AI-assigned score. Now, our work in developing explainable AI makes sophisticated anti-financial crime systems more accessible to non-data scientists.
What's important for anti-financial crime is that those reviewing the results of the AI - the human compliance professionals at a financial institution - can do so with trust, confidence and ease, which is why I advocate for explainability in AI, especially for anti-financial crime.
What can we expect from Napier and its use of AI-enabled technology in the future?
Napier aims to offer many more first-to-market and cutting-edge solutions to become the market leading, end-to-end AML and financial crime compliance software provider.
Organisations should begin to prioritise digitalisation and AI implementation now, to enable real-time assessments, more robust risk assessment of customers, and improved data-sharing capabilities – between private/public sectors as well as within organisations.
What we hope to see most of all is for compliance teams to be more empowered and effective, so we can collectively begin to increase the percentage of laundered money recovered from the appalling 1% figure to at least 2%.