Financial Crime Prevention: Minimize Risk, Maximize Security

Correspondent banking is an essential part of modern finance and refers to the relationship between two banks in different countries where one bank (the correspondent bank) provides services on behalf of the other bank (the client bank). This promotes and simplifies international trade by enabling cross-border payment services in different jurisdictions.

However, correspondent banks are particularly vulnerable to abuse by criminal networks for money laundering and terrorist financing. This type of financial crime poses a significant risk to the integrity and stability of the global financial system. Criminals often use the complex structures of international banking relationships and transactions to conceal illegal funds and channel them into the legal financial system. According to estimates, around 100 billion euros are laundered in Germany every year. Last year alone, around 32,600 money laundering offenses were recorded by the police. This marks the third consecutive year that the number has risen, reaching a new high.

To effectively combat this threat, on May 31, 2024, the European Parliament adopted the 6th EU Money Laundering Directive on May 31, 2024. This strengthens the national rules and control systems of the member states to prevent the use of the financial system for money laundering and terrorist financing more effectively. In particular, it tightens the requirements for banks and other financial institutions to ensure that they take comprehensive measures to prevent and combat money laundering.

The German Money Laundering Act (GwG) plays a central role in this regard. It obliges banks and financial institutions to carry out strict checks and reporting requirements in order to identify and report potential money laundering activities at an early stage. Failure to comply with these regulations can have serious consequences. Banks that violate money laundering regulations can be subject to significant penalties, including both financial sanctions and legal action.

To ensure the integrity of their business operations and protect themselves against money laundering, banks must take a variety of measures. These include cooperation with authorities, internal and external audits, Know Your Customer (KYC) measures and timely and periodic monitoring of correspondent bank payments through an automated system.

The implementation of anti-money laundering (AML) programs with the support of artificial intelligence (AI) is one of the most advanced and efficient methods of combating money laundering. 

Compliance solution Smaragd for money laundering prevention

GFT's Smaragd provides a cutting-edge solution for regulatory compliance, combating financial crime and preventing money laundering for banks, insurance companies and other businesses.

The use of Smaragd supports obliged entities within the meaning of the GwG in ensuring compliance with regard to the prevention of money laundering and terrorist financing. Smaragd covers the international standards for combating money laundering and terrorist financing.

The simple rule administration and case processing ensure the reliable identification of conspicuous money movements and thus minimize the risks for the company. The use of artificial intelligence guarantees high quality results and significantly reduces costs for the specialist departments.

Transaction Monitoring: Smaragd offers risk-based monitoring of the correspondent banks involved. The compliance solution identifies suspicious transactions, behavior patterns, and customer relationships to prevent money laundering and terrorist financing. All parties involved in a foreign transaction are identified, and the transactions are examined for patterns that could indicate money laundering. Anomalies are detected daily to implement risk-based legal due diligence obligations. Flexible rule administration ensures compliance with international standards. In alert management, anomalies are analyzed in a configurable workflow with audit-proof documentation. Optionally, suspicious reports can be generated as XML reports via a goAML component and uploaded to the FIU portal.

Onboard simulation system: The integrated simulation system enables the autonomous and flexible optimization of the set of rules. Changes to rules and parameters can be tested using real data to estimate the expected number of cases.

Artificial intelligence:  Machine learning reduces false positives, improves the quality of alerts and reduces manual effort in processing, while regulatory requirements are met.