Beyond Transaction Monitoring: Minimise Risks Effectively with These Four Factors

1. July 2021 / in Knowledge

Criminals are becoming increasingly sophisticated in their methods to disguise and hide the origin of proceeds from crime. At the same time, regulators are placing explicit requirements on the institutions they oversee. Banks and other obligated parties must identify, prevent, monitor and disclose suspicious cases.

Transaction monitoring has been the preferred tool for preventing money laundering and terrorist financing over the years. What else can money laundering officers and compliance departments do to minimise risks in a quick and effective manner? How can banks and AML officers make the monitoring process more seamless and efficient?

1. Beyond Working Silos

To ensure successful company-wide risk management, you should definitely keep certain things in mind. Breaking down anti-money laundering working silos is a crucial endeavour. Too often, there’s little awareness within individual teams of what is happening elsewhere in the organisation. In this context, communication is paramount! The most important thing, therefore, is to ensure that communication flows seamlessly between teams and that everyone is involved in the process.

From a fraud prevention perspective, effective communication channels between functions are critical to guarantee compliance with regulatory requirements, while also ensuring that changes are workable and actionable. A common deficiency here is the way regulations and resulting process changes are communicated between compliance and operations teams.

Communication with regulators is another avenue that deserves company-wide attention. Excellent communication between transaction monitoring, know your customer teams, sanctions and fraud experts, and business managers responsible for customer relations is also critical to the effectiveness of monitoring.

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2.Targeted Handling of High-Quality Data

The basis for compliance and fraud management is a solid database. However, validating, maintaining and updating Big Data and transforming it into Smart Data entails an enormous amount of work. To effectively protect themselves and their institution, managers must collect, link, and process information from a variety of internal and external sources.

The way in which many financial institutions’ systems are set up makes collecting customer data, transaction data and information about customer and business partners virtually impossible to scale. This is compounded by the number of external sources that need to be searched and the manual effort required to analyse and apply the results.

The relevant data should be enriched with information from different banking systems, cleansed of unnecessary or duplicate information and presented in a clear, usable form. Automated technology solutions for fraud detection automatically compile a consolidated view of the relevant information, enabling banks to identify correlations in their customer data, minimise risks and reduce costs.

As part of strategic partnerships with FinTechs, banks can use machine learning to aggregate (see also API Banking), conduct more concrete searches on and leverage banking data to quickly identify anomalies. By utilising new technologies (rules engine, machine learning and AI-based solutions), risk analysis measures can become automated and more targeted.

Intelligent use of data takes risk management to the next level. Do you know how Open Banking strikes a balance between anti-money laundering and customer experience in onboarding?

3. Expand Internal Know-How and Work in a Goal-Oriented Manner

Effective anti-money laundering requires organisation and targeted measures. However, many monitorings lack structure, which is often reflected in different documentation and inconsistent conclusions.

On the one hand, a consistent monitoring approach requires detailed instructions that can be followed by all parties involved. On the other hand, measures adapted to the specific use case that can be carried out quickly and easily can supplement or refine transaction monitoring and optimize risk management. The targeted query of risk characteristics such as the source of funds minimises the risk of money laundering. This contributes to goal-driven monitoring, complete documentation and detailed justification of the decisions made.

4. Use Open Banking Tools to Combat Money Laundering

The pressure to digitalise and the demise of bank branches were already evident at every point in the financial system before the dawn of the coronavirus pandemic. In times when all personal customer contact is eliminated, however, anti-money laundering is virtually exclusively dependent on digital tools. This poses a significant challenge for an area that is primarily about customer knowledge.

Getting to know your customers happens online now. By adhering to the know your customer principle, you can still effectively prevent fraud and money laundering.

AML and fraud management with Open Banking data enables commissioners to select and execute the method that contributes most quickly and effectively to their risk management. Real-time, automated fraud detection extracts all relevant data (both internal and external) and compiles it in a precise overview. You can use intelligent analysis methods to detect and prevent fraudulent transactions as well as validate suspicious accounts.

Assessing risk situations in real time is critical, especially during a crisis. Open Banking tools for anti-money laundering access up-to-date account data to ensure fast and accurate evaluation of relevant risk factors. This way, up-to-date risk assessments are always possible in a robust, seamless manner.


Schlagworte: Knowledge

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