HOW TO USE AI TO TACKLE CRISIS KYC Capably matching names and other personally identifiable information (PII) is critical to any effective compliance screening system: failure puts reputation, finances, and ethics on the line. Unfortunately, globalization coupled with the economic impact of the pandemic is testing screening systems like never before. As applications pour in, these systems are being asked to process key identity data in a huge variety of languages at unprecedented volumes. If these critical systems can’t keep up, everyone loses. But no one has to. In Smart Matching for Screening, AI vet Steve Cohen will provide you with a clear roadmap for enhancing your screening systems with AI and NLP so you can cut false positives, reduce risk, and find bad actors during this crisis. STEVE COHEN, DECLAN TREZISE Basis Technology

1. How to Use AI to Tackle Crisis KYC.
Steve Cohen
COO
Declan Trezise
Director, Applied Engineering
May 13, 2020
SMART MATCHING FOR SCREENING

2. BASIS TECHNOLOGY
EVERY DAY WE ENABLE.
140MWATCHLIST CHECKS.
EVERY MONTH WE SUPPLY TOOLS TO.
40,000DIGITAL INVESTIGATORS.
WE HAVE.
25+YEARS EXPERIENCE.
We engineer a safer & more productive world by building proven AI solutions for
analyzing text, connecting data silos, & discovering digital evidence.
ABOUT BASIS TECHNOLOGY
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BOSTON IN 2013.
Suspect.
detained.
Driver breaks.
free.
Gunfight,.
officer down.
Carjacked.
MIT officer shot.
Attack site.
Basis HQ.

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Image Source: Bombing: CNN

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Spring 2011
Alert Created
for “Tsarnaev”
!
Oct 2011
Alert Created
for
“Tsarnayev”
Jan 2012
JFK -> Moscow
Detain failure due.
to FPs overload.
Spring 2012
Tsarnaev in Jihad Training
“Tsarnayev” Alert Expires
Jul 2012
Int-> JFK
Detain failure due.
to False Negative.
Jan 2013
Tsarnaev Buys Two Pressure
cookers in “Terrorism” Dept.
at Square One Macy’s
Apr 2013
Boston Marathon
Bombing Takes Place
!
5
TIMELINE TO TRAGEDY

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Tamerlan
Tsarnayev
Rule-Based.
Name Matching.
300 Casualties.
Tamerlan
Tsarnaev
NO MATCH
Тамерлан
Царнаев
Image Source: Bombing: CNN
SIMPLE FAILURE, HUGE CONSEQUENCES
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Tamerlan
Tsarnayev
ML-Based Matching.
Tamerlan
Tsarnaev
MATCH
✔
Image Source: Bombing: The Boston Globe
AI-BASED NLP WOULD HAVE CHANGED HISTORY
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BRINGING
INTELLIGENCE-GRADE AI.
TO FINANCIAL SERVICES

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PROBLEMS
● Business
● Technical
SOLUTIONS
● Tech demo
● Deploying AI
Q & A
FINANCIAL SERVICES.

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Sources: The Fed, Research & Markets, The UN
TAKEAWAY.
HUGE GROWTH IN NON CASH
PAYMENTS
TAKEAWAY.
GLOBAL MOBILE PAYMENT
MARKET EXPLODING
TAKEAWAY.
CLIENT DIVERSITY
CONTINUES TO GROW
RAPID PACE OF CHANGE IN FINANCE AND KYC
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TAKEAWAY.
US HAS LOST 33M JOBS
TAKEAWAY.
GLOBAL STIMULUS
RESPONSE COULD TOP
$10T
TAKEAWAY.
FINANCIAL CRIME SURGING
DURING CRISIS
Sources: Fortune, CFR, NYTimes
PANDEMIC: A KYC CRISIS IN 3 PICTURES
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MISTAKES .ARE INEVITABLE.

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PROBLEMS.

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$55,000 x 3000 =
~$165M.
COST.
$145,000,000 x 58 =
~$8B.
RISK.
PAINFUL MATH
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THE ROOT PROBLEM
- Greg Pinn, AML expert
"Reducing false positives from .the name screening process.
is the #1 problem in compliance screening, which is key to
the AML process altogether.”

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Human-Generated
complexity
Computer-Generated
complexity
TECH PROBLEMS.
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[Nicknames]. [Abbreviations]. [Misspellings].
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HUMAN GENERATED COMPLEXITY

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[Messy Data]. [Name Mixup].
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COMPUTER-GENERATED COMPLEXITY

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Steve Cohen. Steve Cohen. Steve Cohen.
Steve Cohen. Steve Cohen. Steve Cohen.

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SOLUTION.

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TECHNICAL .DEMO.

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“.Reduce false positives on screening 25%. and you
could save an institution tens of millions of dollars.
.That's a game-changer..”
- Greg Pinn, AML expert

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ASK YOUR QUESTIONS USING CHAT
.Q&A.

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REACH OUT!.
declan@basistech.com.
Declan Trezise
stevec@basistech.com.
Steve Cohen
LEARN MORE:
www.rosette.com/capability