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Effective technology is the only solution to AML

Discover the four main ways that technology can help us to identify suspicious activity.

Napier AI
December 2, 2020

In 2018 there were 39.3 billion payments made in the UK, and it is estimated that this will rise to 43.3 billion by 2028. The sheer number of payments made means that now more than ever we need effective technology in transaction monitoring to detect suspicious activity.

Compliance analysts cannot afford to spend their time wading through endless volumes of data hoping to spot the high-risk red flags. It is not only an inefficient workflow, wasting huge amounts of manpower, but also proves to be very costly. The Nordic bank Nordea hired 1500 staff to deal with their transaction monitoring backlog, only to find the additional cost was unsustainable, meaning that they had to make huge job cuts and look to automating processes instead.

Effective and efficient transaction monitoring requires effective technology that works with highly-trained compliance specialists. Technology should not replace human decision making but should be implemented to make analysts’ jobs easier, bringing them smaller datasets to analyse and allowing them make more informed decisions.

There are four main ways that technology can help us to identify suspicious activity:

Reduce the number of false positives significantly

The biggest challenge faced by organisations using legacy technology, or technology that is not fit for purpose, is the high volumes of false positives produced when monitoring transactions. One of the issues in effectively reducing false positives, is to not negate the truly suspicious cases. This is where modern technology can have a powerful effect, as it can decrease false positive volumes by using more accurate name matching algorithms, better rules and artificial intelligence (AI), yet continue to flag up transactions that do require investigation.

Produce deeper insights

Graphical user interfaces and analytics give users the ability to drill down into each case and gain deeper insights into activities and transactions. Introducing AI into a transaction monitoring system also gives the analyst far deeper insights into the behaviour of customers in relation to their expected behaviour. This helps analysts distinguish which transactions are truly suspicious.

Create more efficient workflows

The two factors above already increase efficiency in transaction monitoring. However, technology can further increase efficiency, for example by using enhanced graphical analytics and reports; enabling task allocation and user workflow; and having an intuitive easy-to-use interface.

Integrate multiple solutions into one platform

Transaction monitoring on its own is no longer enough to be able to accurately detect suspicious behaviours. As criminals evolve their methods to become more sophisticated at laundering money, so grows the importance of having a full view of the customer. This view is built by drawing on data from KYC (Know Your Customer) identity and on-boarding checks, screening and monitoring, behaviour patterns, networks, intelligence data etc.  

Effective technology can combine these functions into one platform, so that analysts can easily and efficiently access the data they need to make quick, informed decisions.

How artificial intelligence enhances transaction monitoring

AI is an important and necessary weapon in the fight against money laundering, terrorist financing and other financial crimes. One of the biggest factors driving the demand of AI for AML is the fact that criminals themselves are operating using sophisticated technology, identifying the ever-changing weaknesses in the market and exploiting them.

There are various AI techniques that can be used to enhance current monitoring processes to identify potential suspicious activity. Technology companies, ourselves included, use robotic process automation , natural language processing and distributed artificial intelligence in AML solutions to increase the chances of detecting anomalous transactions and behaviours.

As more research and development goes into AI for AML, organisations can expect to see far more powerful techniques to aid analysts - including behavioural and predictive analytics, and AI advisors for AML.


As the number of payments made increases year on year, and the methods criminals use to launder money become increasingly sophisticated, the role of technology becomes ever more important in effective transaction monitoring. The advancements in A.I., for example robotic process automation, are key in the fight against money laundering, and as these are further developed, we will see effectiveness and efficiency continue to grow.

Identifying suspicious activity is no easy task, and the more we can utilise technology to help compliance analysts, the better. Effective technology by no means replaces compliance specialists, but should aid them in their decision making; reducing their workload to allow them to investigate more thoroughly and efficiently, meaning less suspicious activity goes undetected.

Transform your AML compliance with award winning technology

This article is an extract from our larger paper on Transaction Monitoring. If you would like to read more about how cutting-edge technology could benefit you, download Successful Transaction Monitoring: Overcoming Challenges Through Collaboration co-authored with Lysis, or feel free to request a demo to see how our systems can help.

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