Big Data Can Fight Money Laundering And Terrrorism


Knowledge of Cognitive Computing is Essential

It is important for data scientists to get the right information at the right time to overcome cybersecurity breaches for various regulatory agencies. The challenge lies in correctly interpreting the analytics when all kinds of data come in from different sources.

In this regard, the combination of Artificial Intelligence and Cognitive Computing is geared to add muscle power to various intel agencies and state authorities, globally. It is important for them to remain relevant and provide security to personal data.

Various regulators, financial institutions, service providers can bank on AI and other machine learning tools to fight crime, especially money laundering and hacking legitimate accounts. Only recently HSBC has started using advanced data analytics to detect internal frauds and check on money laundering individuals. ‘Dirty money’ or blood money is a real problem and solutions are required to keep it in check.

Check out some ways how the systems are buffered against illegal uses like money laundering by terrorists or gambling outlets. Analyzing the text, is the greatest knowledge that bring results. Perhaps, this could be something you are looking at to protect your enterprise from wrong elements.

Can we leave it all to computers, alone?


Human intervention is required at the right time!

One of the basic concepts derived from artificial intelligence is letting the computer take decisions. But is this enough for protection of data in the long run for sustained monitoring and safety? Currently, computer agents are created with specific algorithms which use neural networks, machine learning and analysis derived by available statistics. For the ‘computer agent’ to come up with relevant results, it should be fed with several algorithms over a period of time. It eventually ‘learns’ what to do to arrive at a desirable result.

Just look at the way Alexa/Siri/ voice assistants by Google function.

They show a pattern that forms when a human being uses them. The algorithms form a cognitive structure to get desired results. This is cognitive computing which is used to solve issues and takes a systematic approach based on the previous behavior. Thus, in a way, it is akin to human behavior or responses. With a previous track record as a base, analyzing emerging text and interpreting it is important.

New tools offer improved results as they have better vocabularies. The content (from big data) can be detected through dedicated networks, tapping and also mapping. Any nefarious activity will be registered within a specific location as it is monitored.

Such activity by potential criminals can be under a watch, so that security services are not compromised. Human intervention can come at the right time with cognitive computing tools. The dark net in cyberspace exhibits typical behavioral patterns. Criminals have become intelligent too. They have understood the transactional monitoring systems of banks.

They know how to circumvent the security loop and continue to do dirty business via these channels, including casinos where money is frequently moving from one account to the other. Artificial intelligence has a major contribution in this case as it helps human intervention and alerts authorities.

Is casino a regular suspicious ground for regulatory agencies?

It depends on the payment flows!

Why have we taken the example of a casino to understand how Artificial Intelligence and Cognitive Computing work? Consider this- about 2.2 million transactions are done by a global financial company. Most criminal activity is done through this channel!

Dirty money exchanges hand through multiple routes and are rarely detected thus posing a security risk for agencies. If a casino were to buy an AI software or platform to release funds, there is nothing illegitimate about it. But what could trigger a panic or exposure to risks in leaking data? If a huge amount of data is discovered during the payment flow, it could be a red mark.

The transactions may or may not be legal. It could also be a tax fraud by the computer manufacturer. Or the activities and transactions in the casino are suspicious. Also, The computer will produce algorithms for agencies to know the truth. It will use its cognitive think pattern to give the desired results. But, again, human intervention at the right time is crucial to stop irregular payment flows.

Final Point of view:

Even in a business enterprise, red flagging is common when financial frauds are detected. Tools that use AI and cognitive processes prove to be useful deterrents. Thus, If you are in business and require technology tools to avoid cyber criminals from attacking the systems, re-read the above blog.

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