Financial institutions are required to monitor and detect suspicious activity, yet many programs are ineffective. Why? There are many reasons: Lack of data, inaccurate detection models, poorly optimised systems or ineffective use of technology, which leads to high levels of false positives. That means true suspicious activity is difficult to identify or missed completely.

Typical transaction monitoring programs are based on rules, but as financial crimes become more advanced, increasing the flexibility in these rules-based systems is vital. Financial institutions need more sophisticated tools that can anticipate the actions of criminals and better detect new, complex financial crime typologies. Using tools such as artificial intelligence (AI), machine learning, behavioural analytics, and network analytics to identify criminal activity elevates accuracy.

Simultaneously, systems are still plagued with incorrect or duplicate data, resulting in poorly defined segmentation, inaccurate monitoring, and inefficient investigations due to limited visibility. With poor data, financial institutions are unable to truly understand their risks and or accurately monitor customers for suspicious behaviour.

Not overcoming these challenges leads to substandard transaction monitoring. As a critical factor in all financial crime compliance programs, transaction monitoring solutions need to be modernised, ensuring illicit activity is identified quickly and accurately.

Sign up for this Finextra webinar, in association with Nice Actimize, to join the panel of industry experts as they discuss the following areas:

• What are transaction monitoring challenges financial institutions face around data quality, inefficient systems, false positives, and suspicious activity detection?
• What updates do AML programs need to detect suspicious activity more accurately?
• What role does technology, such as data enrichment, AI or machine learning, and behavioural analytics play in addressing current challenges?
• Where should financial institutions start to have the biggest impact on their AML program’s efficiency and effectiveness?
• What does the future of transaction monitoring look like?