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Trends in Security Information
The HSD Trendmonitor is designed to provide access to relevant content on various subjects in the safety and security domain, to identify relevant developments and to connect knowledge and organisations. The safety and security domain encompasses a vast number of subjects. Four relevant taxonomies (type of threat or opportunity, victim, source of threat and domain of application) have been constructed in order to visualize all of these subjects. The taxonomies and related category descriptions have been carefully composed according to other taxonomies, European and international standards and our own expertise.
In order to identify safety and security related trends, relevant reports and HSD news articles are continuously scanned, analysed and classified by hand according to the four taxonomies. This results in a wide array of observations, which we call ‘Trend Snippets’. Multiple Trend Snippets combined can provide insights into safety and security trends. The size of the circles shows the relative weight of the topic, the filters can be used to further select the most relevant content for you. If you have an addition, question or remark, drop us a line at info@securitydelta.nl.
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Money laundering
Money laundering is the process by which illegally obtained cash or money is moved through financial systems in such a way that it becomes legal or appears to be from a legitimate source. Money laundering can for example be used by criminals in the drug industry to process their illegally obtained cash through various companies, organizations, shops or real estate, after which the money is seen as legal. Since the proceeds that are laundered are related to criminal activities that are not part of the economy, money laundering can cause a distortion in the real economy by affecting processes such as investments, competition and trade.
Anti-money laundering (AML) generally refers to the rules, regulations and measures that are in place by various organisations and institutions to counter the process of money laundering. For example, many financial institutions, such as banks, are required to monitor and report suspicious financial transactions. If large sums of money are transferred at once, this can be an indication that money has been laundered. By monitoring financial transactions, the (illegal) source of money can be tracked and traced. Financial institutions also use black lists provided by government to flag transactions. The use of data analytics and Artificial Intelligence attribute to the rise of new AML mechanisms.
Related keywords: wire transactions, illegally acquired cash, dirty money, smurfing, terrorism financing, criminal financing, phony businesses, fake companies, ‘follow the money’, money mules, Know Your Customer (KYC), foreign banks.
Money laundering is the process by which illegally obtained cash or money is moved through financial systems in such a way that it becomes legal or appears to be from a legitimate source. Money laundering can for example be used by criminals in the drug industry to process their illegally obtained cash through various companies, organizations, shops or real estate, after which the money is seen as legal. Since the proceeds that are laundered are related to criminal activities that are not part of the economy, money laundering can cause a distortion in the real economy by affecting processes such as investments, competition and trade.
Anti-money laundering (AML) generally refers to the rules, regulations and measures that are in place by various organisations and institutions to counter the process of money laundering. For example, many financial institutions, such as banks, are required to monitor and report suspicious financial transactions. If large sums of money are transferred at once, this can be an indication that money has been laundered. By monitoring financial transactions, the (illegal) source of money can be tracked and traced. Financial institutions also use black lists provided by government to flag transactions. The use of data analytics and Artificial Intelligence attribute to the rise of new AML mechanisms.
Related keywords: wire transactions, illegally acquired cash, dirty money, smurfing, terrorism financing, criminal financing, phony businesses, fake companies, ‘follow the money’, money mules, Know Your Customer (KYC), foreign banks.
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