Money laundering accounts for anywhere between 2 and 5% of global GDP, which is between $800 billion and $2 trillion each year.
The figure has risen in recent years, with financial crime surging by more than 50% in 2022. This resulted in fines totaling $5bn due to anti-money laundering (AML) infractions and “know your customer” (KYC) failings.
During the preceding decade, fines totalled $36 billion. It’s clear to see that the problem is growing.
In most regions, anti-money laundering laws emerged to prevent this type of fraud. Regulations mandate that businesses screen new customers to identify suspicious behaviour.
In an effort to maintain onboarding compliance, many businesses are turning to automated AML and KYC software. AI has driven up the accuracy levels of this software over the past few years, as we’ll explore in this article.
What Are AML and KYC Checks?
AML, KYC, and KYB (Know Your Business) checks are a vital part of onboarding. New customers or clients provide their details and upload ID documents for verification through a secure portal.
Automated AML software is used in any industry that manages financial transactions, including:
Over the years, fraudsters developed sophisticated ways to trick AML systems and sign up with fake accounts. In recent years, the explosion of AI technology means that businesses are gaining the upper hand over fraudsters.
How AI Is Revolutionising AML and KYC
AI is causing a seismic shift in the accuracy of screening tech, onboarding compliance, and due diligence.
When we talk about AI in this context, we mean machine learning. Machine learning is a system of algorithms that learn to spot patterns in data, then flag anomalies or generate insights.
1. Reading text and images
The days of an analyst trying to make sense of a blurry passport photo are coming to an end. AI engines are getting much better at identifying not only the details of an image but also whether it is genuine or fake.
Indeed, AI models are now able to spot deep fakes – images generated by other AI models. It’s a game of cat and mouse as fraudsters try to find new ways of beating the system, but detection tech is currently taking the lead.
At ArriTech, our latest AI-driven AML, KYC, and KYB tools are 99.9% accurate. This means you reach regulatory compliance and increase the likelihood of avoiding hefty fines.
Generative AI models, such as the large language model GPT-4, also show potential for spotting contextual patterns. For instance, an unusual cross-border transaction that doesn't fit the typical profile of the account holder might be risk-assessed by the AI model and flagged for further investigation.
2. Reducing false positives
One of the most transformative aspects of using AI in onboarding compliance is its capacity to reduce false positives in customer screening processes.
Traditionally, AML systems were plagued by high rates of false alerts, which put a strain on the people conducting manual investigations. AI-powered systems improve precision by more accurately distinguishing between legitimate transactions and those that warrant further scrutiny.
Benefits of reducing false positives with AI
- Efficiency: AI allows compliance teams to focus their efforts on genuinely suspicious activities. This saves time and reduces operational costs.
- Accuracy: Enhanced algorithms analyse additional layers of data, differentiating more easily between normal and anomalous behaviour. ArriTech’s industry-leading onboarding compliance software is 99.9% accurate.
- Customer Experience: Legitimate transactions face fewer disruptions, leading to smoother customer experience.
- Regulatory Compliance: Accurate AI-driven tools help businesses comply more closely with AML regulations and avoid penalties related to inadequate controls.
Maintaining an improved compliance posture is a priority for any business involved in financial transactions. It improves their reputation and means they can hold onto their operational licence.
Book a demo today to see how our all-in-one solutions can save you time and resources.
