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Preventing Money Laundering

Our Commitment to Financial Integrity take seriously and are committed to maintaining a safe and secure financial system. On this page, you will find information on our policies and procedures for detecting and preventing money laundering activities.


Solution in Identify user

The system analyzes large amounts of data from various sources and applies sophisticated matching techniques to identify potential matches between names and accounts. This process helps to detect any suspicious activities, such as transactions made under false identities or using stolen identities.

Internacional Watchlists

Sanctions lists

Politically exposed persons (PEP) lists

Name translator

Name translation capabilities to ensure accuracy across different languages and writing systems. This helps to prevent errors and ensure that the system can detect matches even when the names are written or spelled differently in different languages.

Iyad Nazmi Salih Khalil
Ayyad Nazmi Salih Khalil
إياد نظمي صالح خليل
吉田 茂
Yoshida Shigeru

NLP Name Match scores

Using natural language processing (NLP) techniques to analyze and score text data, such as customer profiles, transaction records, and other financial documents, for potential indicators of money laundering activity. The NLP algorithms are trained to identify and extract key features and patterns from the data, such as suspicious keywords, phrases, or syntax, which may indicate illicit financial activity.

Ayyad Nazmi Salem Khalil
إياد نظمي صالح خليل

Celebrities and Public exposed

By monitoring watchlists, celebrity and public figure transactions, and potential explosion-related activity, financial institutions can help to prevent money laundering and other illegal activities and ensure compliance with AML laws and regulations.