NonStop Trends & Wins

AML, KYC, and Human Trafficking

I’ve been doing a lot of research recently based on an article I read online. It was discussing human trafficking and patterns in the transaction flow that could identify this activity. I was intrigued. I was quite surprised to learn that, depending on the poll, human trafficking was either the second or third largest revenue source for criminals. The first is drugs. Estimates are that over $150B is generated annually from human trafficking. In the United States, when the term comes up, my thoughts went to prostitution and then to forced labor. I was surprised to learn that worldwide forced labor accounts for a much larger percentage about 57% to 38%, of course depending on whose stats you read.

This article discussed just a few of the patterns that might suggest human trafficking but I was struck by the $150B number and the number of transactions that must flow through NonStop systems. If there are detectable patterns, this clearly seems to be a fight we should take on. With millions of people trapped in what is known as modern slavery, we must use whatever tools we have to eliminate this evil. I was encouraged to find so much going on from laws within various countries, regular reporting, and released information on the patterns of traffickers. On a sad note, this crime seems to be growing. It requires vulnerability. People become more vulnerable to enslavement when there is a sudden change in a person’s situation – such as the loss of a job or income, or the need to pay for expensive healthcare procedures or social rituals, such as weddings or funerals. We see people becoming more vulnerable when there is a sudden change in their environment – because of the eruption of an armed conflict, because of displacement due to a natural disaster, or more recently a worldwide pandemic. It grows when countries have lax laws or law enforcement doesn’t have the means or ability to combat it. Exploiters soon take advantage of the situation, but returning to NonStop transactions are the fingerprints for this crime. Fortunately, HPE also has some of the best Artificial Intelligence, Machine Learning, and Deep Learning (AI/ML/DL) systems available. NonStop can receive the transactions and then feed them to attached AI systems for analysis and pattern recognition. These systems can also detect new patterns. This is where the HPE technology known as swarm learning can come into play.

For me, one of the missing elements was digital information sharing between banks and law enforcement. Don’t misunderstand, there is a lot of sharing but not high-speed, digital real-time sharing because of privacy constraints. One of the key benefits of swarm learning is that it only shares weights and biases within the model. No customer or transaction information is shared. The model itself can be strengthened through sharing without sharing customer information. I’m hoping this might prove to be a breakthrough in combatting this crime. There are a lot of people that need to be convinced, but it’s a start and NonStop transactions are the key.

 

 

Author


  • Justin Simonds is a Master Technologist for the Americans Enterprise Solutions and Architecture group (ESA) under the mission- critical division of Hewlett Packard Enterprise. His focus is on emerging technologies, business intelligence for major accounts and strategic business development. He has worked on Internet of Things (IoT) initiatives and integration architectures for improving the reliability of IoT offerings. He has been involved in the AI/ML HPE initiatives around financial services and fraud analysis and was an early member of the Blockchain/MC-DLT strategy. He has written articles and whitepapers for internal publication on TCO/ROI, availability, business intelligence, Internet of Things, Blockchain and Converged Infrastructure. He has been published in Connect/Converge and Connection magazine. He is a featured speaker at HPE’s Technology Forum and at HPE’s Aspire and Bootcamp conferences and at industry conferences such as the XLDB Conference at Stanford, IIBA, ISACA and the Metropolitan Solutions Conference.