When most bankers think of money launderers, they generally envision sophisticated international operations, complete with secretive offshore banks located in dodgy, corrupt foreign tax havens. While this certainly is one of the principal activities that money launderer engage in for their clients, many of the operations are also conducted locally, closer to home, and they are far from glamorous. I am talking about domestic money laundering. through cash-intensive businesses.
Here's how it works:
1. You find a cooperating (meaning greedy) business owner of a company that accepts a large percentage of their sales in cash for one reason or another; such as tradition, corporate culture, issues specific to that industry. Companies with serious cash flow issues are also good targets.
2. The company then is funneled, periodically and consistently, your criminal cash, which is added to the daily receipts and booked just like the real sales. The corrupt company owners receive cash for their participation.
3. You dummy up sales records to match the additional payments. You might even work out something with a supplier to create false deliveries from your wholesaler to support those new "sales' or you falsify document purchases, so that incoming products are sufficient to back up outgoing sales.
4. A representative of the criminal client signs on as sales rep, on straight commission, and receives substantial income, which is all duly reported to the IRS, and taxes paid, legitimizing his income.
5. Alternatively, You designate a criminal client to be a partner in the venture, and he takes out substantial profits quarterly, pays his taxes, and has clean money at the end.
6. Run the operation for a number of years, and then have the business shut down, after both the legitimate owner and your criminal clients have accomplished their financial goals. You might even have a fire, or a theft or destruction of business records to conceal the evidence from future investigations.
Now, however, using an Artificial Intelligence platform, with machine learning, a review of what previously are confusing and disjointed records can result in the display of a pattern that will alert investigators or compliance staff to evidence that that they have tumbled upon a laundering enterprise embedded within an operating, legitimate cash-intensive business.
The machine learning feature will cobble together what to the untrained eye is normal unconnected data, and develop patterns from the data that are not recognizable to an investigator, or will uncover data that show activities inconsistent with that type of trade or business. A result will be extracted and synthesized from the data by the program, indicating money laundering.
Here's how it works:
1. You find a cooperating (meaning greedy) business owner of a company that accepts a large percentage of their sales in cash for one reason or another; such as tradition, corporate culture, issues specific to that industry. Companies with serious cash flow issues are also good targets.
2. The company then is funneled, periodically and consistently, your criminal cash, which is added to the daily receipts and booked just like the real sales. The corrupt company owners receive cash for their participation.
3. You dummy up sales records to match the additional payments. You might even work out something with a supplier to create false deliveries from your wholesaler to support those new "sales' or you falsify document purchases, so that incoming products are sufficient to back up outgoing sales.
4. A representative of the criminal client signs on as sales rep, on straight commission, and receives substantial income, which is all duly reported to the IRS, and taxes paid, legitimizing his income.
5. Alternatively, You designate a criminal client to be a partner in the venture, and he takes out substantial profits quarterly, pays his taxes, and has clean money at the end.
6. Run the operation for a number of years, and then have the business shut down, after both the legitimate owner and your criminal clients have accomplished their financial goals. You might even have a fire, or a theft or destruction of business records to conceal the evidence from future investigations.
Now, however, using an Artificial Intelligence platform, with machine learning, a review of what previously are confusing and disjointed records can result in the display of a pattern that will alert investigators or compliance staff to evidence that that they have tumbled upon a laundering enterprise embedded within an operating, legitimate cash-intensive business.
The machine learning feature will cobble together what to the untrained eye is normal unconnected data, and develop patterns from the data that are not recognizable to an investigator, or will uncover data that show activities inconsistent with that type of trade or business. A result will be extracted and synthesized from the data by the program, indicating money laundering.
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