Kenneth Rijock

Kenneth Rijock

Thursday, August 17, 2017

SOCIAL MEDIA RESOURCES INSURE SUCCESS IN INSIDER TRADING INVESTIGATIONS


Let's assume the following: that I am one of thirty partners in a New York City law firm involved in representing Fortune 500 corporate clients in mergers and acquisitions. All of us are privy to confidential information that will affect the market prices of our clients' stocks. The SEC and FINRA have seen serious profits taken multiple times, all in advance of major events. If one of us supplying inside information to a conspirator, who is illegally trading and profiting from it,who are they, and who am I ? 

Criminal investigators seeking to determine if investors engaged in illegal insider trading of publicly traded securities often have difficulties linking individuals who possess non-public information, with confederates who have traded upon that information. Even armed with the identities of investors who made extraordinary profits based upon the subsequent release of positive business news, investigators often cannot uncover the necessary connections. The result is that many "Tippees" who have profited from their crimes are never charged. It was impossible to track them back to the source who divulged the inside information.

Enter into the equation a research tool* that enables the investigator to diagram and inspect not only indirect relationships, but relationships separated by more than one degree. These are connections that are so remote that conventional inquiries will never link them up. This result is accomplished through the use of artificial intelligence software algorithms which scan available social media sources, a feat that would literally take years to accomplish manually.

Therefore, returning to our initial fact pattern, user generated graphs and charts now created by those ai/deep learning algorithms, uncover and display two of my personal indirect connections, which appeared totally disconnected to effectively deny investigators access to conspirators. Using this software program myself, the culprits were identified as a former co-worker from my first job as an assistant district attorney, and that conspirator's onetime university roommate, from twenty years ago.These individuals who would most likely never be found through conventional means, would be identified, and linked to me, due solely to an asset that represents the application of technology to big data social media information.
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* Note to readers: if you are not familiar with this social media resource, kindly email me privately at miamicompliance@gmail.com  and I will furnish that information to you.







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