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Enforcing sanctions against Russia

SANCTIONS – CHALLENGES – SOLUTIONS

In only 5 days Putin achieved remarkable unprecedent results:

He healed the world from COVID-19.

He proved (again) the relativity theory (COVID-19 impact on business? Recently looks like a bad joke).

He united the world (most of it).

He brought Ukraine closer to its membership in the EU.

He made Switzerland break its long history of neutrality toward armed conflicts and adopt EU sanctions against Russia.

He made Finland and Sweden, neutral EU members, to help Ukraine with weapons and funding, and to apply for NATO membership.

In 2022 the war comes to Europe, bringing devastation, suffering and deaths. A lot is being reported and written about it during the last week. We are not war experts, nor political commentators. So, we’ll just leave these fields in their mighty hands.

We are here to talk about practicalities: about how the world can make these sanctions real? How can it apply the sanctions to the right individuals or companies and avoid collateral damage, i.e., unintended but very possible discrimination of people whose names and identical or similar to those listed in the sanction lists?

The problem: overview

Today, most of the existing AML solutions on the market lead to inherent bias, based on or associated with the name.
These solutions are based on N-grams, Levenshtein and similar technologies and, therefore, it is enough for them to find a sequence of N characters in a raw to produce a “match.” Even 3 or 4 consecutive letters will trigger an alert.
The problem is that every Vladimir, Alexander or Sergei will be alerted as possible sanctioned individual. Yet, this name is common and do not in any way or manner indicate any criminal associations. In the other words, it is impossible to relay to one section of a name (structured from first, middle, and last names) as a sufficient identifier.

Most of individuals sanctioned by the US, UK and EU come from Russian origin, so that most of the names typical for Russia have entered numerous sanction lists. Which means, that dozens of thousands of alerts will be triggered, creating False Alerts, and will then be required to be processed manually, which is literally impossible, considering the amounts of newly sanctioned persons.
The problem is aggravated by the fact that lots of Ukrainian citizens, as well as Russians who try to catch the last train to flee the drowning (dictator)Ship, move to other parts of the world, opening bank accounts, transferring their funds, and carrying out various banking operations. A huge wave of back-and-forth transactions are being carried out between different banking systems all over the world.
All the involved banks (and it’s practically all the banks, globally) need to somehow work in unison, unify data, and ensure that the imposed sanctions are being carried out not only on paper.
And this is not all.
Banks use different technological platforms for their operations, databases, AML screening solutions. Even different branches of the same bank, especially if these branches are dispersed globally, may use different systems.

The solution

Utilizing its unique phonetic fingerprint technology along with other proprietary algorithms, Fincom provides an ultimate solution for GRC, customer management, onboarding, anti-discrimination, bank account verification, confirmation of payee, transactions screening and more!

Fincom’s platform:

  • Considerably reduces the number of alerts
  • Major reduction in the rate of False Positives (over 50%)
  • Ensures accurate name matching against Sanction and PEP lists, including complex structured names and variety of languages and transliterations.
  • Match names in 40 different languages, including Russian, Chinese, Ukrainian and others, in their original or transliterated spelling, taking into account spelling mistakes and variations
  • Meets updated requirements for Realtime Name Screening verification in payments and other transactions.
  • Resolves name-based discrimination typical for current AML systems (rule-based and others). Anti-discrimination tools are essential for resolving discrimination in payments and onboarding KYC.
  • Bank Account Verification or Confirmation of Payee – ensuring that intended payment beneficiary is the real owner of the bank account, not listed in sanctions lists. Reduces transaction errors, fraud, and closing a major loophole in AML ensuring that sanctioned person is not a co-owner of a bank account.
  • Provides anonymous search across database silos – an ability to search data sources, while not breaching privacy and GDPR/CCPA regulations.
  • Data Sharing between banks: enabling banks and other financial institutions better combat movements of illicit proceeds by secure name & information sharing (314b)
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