The FCPA BLog | Artificial Intelligence | By: Dan Adamson | Thursday, June 1, 2017 at 9:08AM:
Just 15 years ago, due diligence researchers might spend hours retrieving documents from courthouses and sifting through microfiche at libraries. As recently as 2010, they could go through six to 12 months of training just to learn how to create a “level 1” report.
Today, technology can handle those tasks in minutes or seconds, and researchers might wonder about their future in an industry that seems ready to replace humans with machines.
But machines can’t replace humans, and the industry shouldn’t try. The better approach is to combine humans with machines, augmenting human intelligence, not replacing it.
The chess world learned this lesson after humans and machines traded the title of world’s greatest chess player in the 1980s and 1990s in contests that were billed as the ultimate “man versus machine” competition.
Then it discovered that a decent human player assisted by a computer performs better than either a grandmaster or a supercomputer playing alone. Today, the World Chess Champion who famously lost to a computer in 1997, Garry Kasparov, writes of learning to love intelligent machines by seeing them not as rivals but as a boon that provides opportunities to extend human capabilities.
In current state-of-the-art due diligence, the computer begins research the same way a human would: by making a positive identification. With just a few basic biographical details, software matches an entity with an official profile in a government or national identifier database that includes the subject’s name, current and past addresses, work history, and social security number.
The machine can then use secondary sources to whittle down the possibilities, cross-referencing open intelligence sites and premium sources (as subscriptions allow). It can execute searches multiple permutations of a name, retrieving, for example, results for Glaxo Smith Kline, GlaxoSmithKline, and GSK.
With artificial intelligence, machines can go beyond just aggregating data to help compliance teams extract the right information out of millions of available pages, interpret it correctly and process it quickly. Today’s technology can understand different human languages, follow leads and create concise, auditable reports within minutes to highlight potential issues while eliminating the vast majority of false positives.
Banks in particular need these capabilities. With more than $1 trillion of illicit financing moving through the financial system each year, an average of 200 regulatory changes to track globally each day, and fines for noncompliance that have cost $321 billion since 2008, banks urgently need the capabilities that AI adds to due diligence.
But technology can’t do everything. No machine today can gain true insight into the complexities of what any human being is thinking or has thought. IBM’s Watson doesn’t learn while it’s in a chess game and start reacting and changing its algorithms, despite what its marketers tell you. And self-driving cars don’t learn to think for themselves and start rolling through stop signs as a way to get better gas mileage. Machines can’t think creatively and won’t any time soon, so today’s solutions still need humans to make the ultimate call.
Teamed up, humans and machines can quickly sift through a complex web of interrelated sources to find the right balance between comprehensive, forensic analysis and practical, cost-effective results.
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