A landmark ruling in the Dutch courts has paved the way for the use of artificial intelligence (AI) in anti-money laundering (AML) strategies, potentially changing the landscape for fintech and regtech globally.
A ruling found that the Dutch central bank, De Nederlandsche Bank (DNB), was wrong to have banned digital challenger bank, bunq, from using AI to conduct its anti-money laundering (AML) risk monitoring.
DNB claimed bunq was failing to properly comply with AML legislation – which requires banks to create risk profiles of their customers and monitor transactions – claiming that AI was not an effective way to execute this process due to not being able to adequately evidence logic and demonstrate rigor used in the process.
Bunq then sued DNB – and was successful in its case.
The ruling found DNB was wrong to enforce the use of manual processes for banks. However, the court also found that bunq had not done sufficient work to establish its customers’ source of wealth, including those from politically exposed persons (PEPs) for instance. However, the court found insufficient substantiation for the instances of suggested non-compliance.
bunq said in a press statement after its win, the direct result of this ruling, “…paves the way for progress that will make banking safer for everyone. It enables broader cooperation between the financial industry and online players, as effectively tackling fraud can only be done if these work together.” Fraud detection at traditional banks, said the bank’s representative, “…kept relying on questionnaires that boiled down to asking people ‘Are you a fraudster?’”, with the implication that this approach was ineffective.
Despite evolving preventative techniques, financial crime is on the rise. Therefore, ever more sophisticated tools are needed. Employing and training AI algorithms that use a history of human decision-making, combining them with global data sources to identify risk, is an effective and increasingly popular way of managing due diligence and monitoring risk profiles associated with counterparties.
Criminals are already using AI and machine learning to commit financial fraud. Now machine learning is enabling financial services companies to monitor customer risk in near real-time by unifying large datasets, patterns of fraudulent behavior, and human decision-making to identify risk and automatically trigger enhanced due diligence.
The bunq decision opens the door to freedom of innovation in the regulatory technology and banking sectors, which could lead to greater protection against fraud and always-on approaches to KYC.
The Netherlands has robust AML and counter-financing of terrorism (CFT) frameworks, and a strong focus on regulatory compliance. Non-compliance can be met with severe penalties and reputational damage. There have been several examples in recent years of Dutch banks receiving fines totaling hundreds of millions of euros after AML compliance failings.
Dutch law implementing AML directives allows financial institutions to take their own risk-based approach to KYC and risk monitoring, using their own processes and controls. The new ruling means financial institutions in the Netherlands will now have more legal certainty in their decisions to use AI solutions as part of their fight against financial crime and AML compliance.
AI is already helping companies meet regulatory requirements, manage customer data, and stay on top of changing regulation. The International Monetary Fund (IMF) reports that many supervisory authorities are actively exploring the use of AI in their risk-based supervision processes.
The European Central Bank is using AI-enabled machine reading of its “fit and proper” questionnaire to identify problems, as well as to search for information in supervisory review decisions.
And the IMF also reports that the Bank of Thailand is using AI to analyze board meeting minutes of financial institutions, often used by supervisors to assess the board’s regulatory compliance.
The Dutch case proves traditional ways of performing KYC, AML, and compliance are no longer the only ways. Using AI as part of a compliance process enables financial institutions to perform automated checks efficiently and identify changing risk factors in near real-time. AI can read, understand, and categorize risk data quickly, as well as applying laws and other policy rules an institution needs to abide by.
Automating compliance in this way means human judgement can be used more effectively elsewhere in the risk monitoring process.
Throughout the bank’s history, its engineers have built risk-based methods of know your customer compliance, and incorporated advanced technology based on AI to combat fraud.
The current regulatory landscape is complex and ever-evolving, along with increasingly digital-only businesses and operating models. This means compliance solutions are also evolving. Moody’s Analytics KYC offers flexible and configurable digital solutions for KYC and risk monitoring, leveraging workflow automation, leading global data sources, and the power of AI to transform risk and compliance.
If you would like to find out more about how we can digitally transform your risk and compliance processes to make them more efficient, please get in touch – we would love to hear from you.