USING AI TO EXTRACT EVERY DROP OF INFORMATION ABOUT THAT SHELL COMPANY

Obtaining detailed information about a shell company can be extremely difficult. Your file frequently has only a paucity of documents, save what you can get from the local Secretary of State organizational papers, and annual reports, which can be only a single page of frontmen's names. It is definitely a challenge to do a deep dive on one, even if you ramp your query to the level of enhanced due diligence.

Those of us in compliance all know what the problems are, when examining a shell company:

(1)You cannot identify or confirm beneficial ownership. There is simply insufficient information available anywhere.

(2) Regarding its payments, it makes generally contain insufficient information, making the purpose, or the type of goods and services it allegedly covers, unknown.

(3) Then address is either a convenience address, such as that of the lawyer or registered agent, or in a financial services firm where hundreds are listed.

(4) Payments and transfers are often for rounded off amounts, not the exact dollars-and-cents type, which is customary in the sale of goods and services, which can include taxes and miscellaneous fees and costs.

(5) A huge amount of transfers from a single company, to a large number of beneficiaries, which. can mean that they are later aggregated into one large amount.

(6) payments made to entities in jurisdictions with poor regulatory control, and those assessed as high risk.

(7) There's no functioning business office, no operational telephone, or specific location.

(8) Transactions appear to have no legitimate purpose the ordinary course of business.

(9) Transactions are not logical, given the purported and stated type of business.

Traditional systems just are not capable of reaching into the massive amount of information that's available, and pulling out unrelated slices of data about the shell company you are desperate to rule out as a potential money laundering or financial crime facilitator. You are at a dead end, with not enough data to conclude that the shell company is legitimate, or actually a clever vehicle, and front, for economic crime. You cannot mitigate shell company risk with the systems you have.

Now, using a platform with artificial intelligence, which has not only a broad reach, past anything your legacy systems can handle, but the ability to take the unconnected pieces of the puzzle, and reach out even further, building on them, to find additional information, which is collated and assembled so that the connections between them can be seen, allowing the user to now see a profile containing transactions that are weaved together to form a pattern, no matter how obtuse, showing a relationship, even though it may have been deliberately constructed to be difficult or impossible to assemble. 

Your findings would never have been possible with legacy systems, because they simply cannot mine what is close to an infinite amount of information, and come back to you with what you were seeking all along; proof of a clever money laundering operation, employing a shell company that the laundryman believed was safe from your inquiries, because of the intentionally wide scope of his transactions. Therefore, AI has made the impossible possible; It found all those unconnected loose ends.