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How today's machine learning systems would spot another FX or Libor scandal
Author: Ian Allison
 |  Published: December 16, 2016
 | 

Tim Estes, CEO, Digital Reasoning, has been invited to talk at IBT's forthcoming data science in capital markets event.

Machine learning surveillance techniques used to spot unfair or collusive activity at firms have advanced far beyond searching lists for risky words, and now make myriad connections based on a wide range of behaviour and interactions.

Tim Estes, CEO, Digital Reasoning, which provides advanced compliance tools of this sort, says that to trick the surveillance software would mean avoiding every system – email, chat rooms etc – and not doing anything behaviourally that would create a signal either.

"If you think about it, it's very hard to be someone that you are not all the time consistently. We have a word for those people – they are called sociopaths," said Estes.

Digital Reasoning is a cognitive computing company focused on applications that leverage human communication data. Beyond the finance sector, where they work with Goldman Sachs and NASDAQ, the company provides large scale health service applications and services some prestigious government contracts (Digital Reasoning runs the largest anti-child sex trafficking system in terms of tools for law enforcement in the US). Banking and finance is one of its fastest growing areas, particularly in light of recent price fixing scandals orchestrated between traders at banks and financial institutions.

Digital Reasoning has honed its technology in the wake of things like the forex scandal uncovered in 2013, where senior currency traders operated in secretive groups and in some cases used coded terminology to carry out manipulation in chat rooms.

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