Regulators Are Killing The Banking Industry. Artificial Intelligence Can Save It. – Government, Public Sector – United States – Mondaq News Alerts

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Money laundering is the oxygen that criminal networks breathe tosurvive. And in doing so, they'll creatively bypass regulatorybarriers that are both watered down and arrive years-too-late. Theimplementation of the EU's 5th Money LaunderingDirective (5MLD) is the latest in a global march of regulatoryguidelines that attempt to play catch-up with increasingly adeptmoney launderers and the criminals they support. Since the GlobalFinancial Crisis, regulations like 5MLD attempt to tighten thenoose around money laundering funnels with stricter definitions ofclient risk and lowering the threshold for the application ofenhanced due diligence.

But for many financial institutions, providing a higher level ofinvestigation on their Clients is not a means to an end, but an endin itself, as long as it narrowly satisfies that compliancecheckbox of "doing more."

For some financial institutions, applying these checks, even inthe narrowest terms, can backfire easily, and waste key businessopportunities. Screening solutions are most commonly applied methodfor high risk clients, but offer little protection against bothfalse positives or black and white interpretations of whatconstitutes a risky hit.

For example, a legitimate businessman in South Africa can berejected by a bank because he was appointed by Malta as an honorarycouncil, thereby earning himself a profile on a risk database. Buta local municipal official in Taipei accused by local media ofaccepting bribes from construction companies can get away scot-freeunder those same checks, and put the financial institution atrisk.

It's no wonder that criminals of all shapes and sizes resortto sophisticated networks of front-men and shell companies to cleandirty money, beating out the screening processes they know will beused by banks and other financial institutions on the beneficiariesof new accounts.

Take the whopping 200 billion-plus money laundering scandal thatcontinues to rock Europe's Nordic banks. There, dirty cash fromRussia found its way into the EU's most reputable bankinginstitutions via a handful of insider bank employees and severaldozen front-men.

Eventually, it took investigative journalists and lawenforcement in numerous countries to detect these schemes. In doingso, they demonstrated a dangerous paradigm; that today, we expectbankers and other financial professionals to carry outlaw-enforcement level investigations to shield against dirty cash,but have few answers for how they are supposed to get the trainingand tools to do so all in a manner that doesn't changetheir pro-business DNA.

By implementing Artificial Intelligence and other newtechnologies, it's up to the private sector to providepractical solutions that translate crude regulatory directives intoactionable defensive measures, while remaining sensitive to thecommercial goals of those using them.

According to numerous surveys, and circulars put out byregulators themselves, static screening databases are no longersufficient, as money launderers are able to easily bypass them,while powerful, corrupt businessmen and politicians use legalaction to simply remove themselves from these lists. To properlyidentify risk in today's world, huge amounts of data must beretrieved and analyzed from local news, social media, corporateregistries found in the "deep" web of sources not indexedby Google and other search engines even the dark net.

Even the most cunning investigators cannot possibly processthese huge amounts of data, even if they know where to find it. Butby deploying artificial intelligence to detect negative sentiments,analyze networks, and identify anomalies, researchers at financialinstitutions can focus on matching the intelligence insights theyreceive with their own risk policies.

Failure to adapt and implement artificial intelligence in aworld where clients look for the fastest, smoothest onboardingprocess will result in loss of business to the competition, greaterrisk in clients being accepted, or both.

Governments and regulators shouldn't reinvent the wheel, butin each jurisdiction they should actively promote and encourage thedevelopment of artificial intelligence in the financial sector. IfFinancial Institutions are going to be placed on the front lines inthe fight against money laundering, they should have the righttools to win.

Daniel Nisman is the Head of Financial InvestigationsSolutions at Cobwebs Technologies. He is a career financial crimeintelligence analyst and AML specialist.

The content of this article is intended to provide a generalguide to the subject matter. Specialist advice should be soughtabout your specific circumstances.

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