Anshul Arora presented Matrix-ifs' RPA solution which talked about - Integrating AML, Fraud and Cyber-security Investigations - Eliminate Manual Time Consuming Tasks Using Automation - Proactive Investigations - System Triggering using AI and Machine Learning Trends

1. AutomateyourAML/FIU
Robotics Process Automation

2. About
Matrix-
IFS
Market
Leader
End-to-End
Solutions
Innovative
Ecosystem
Cost
Effective
Specialized
Expertise
Global
Footprint
Vast
Experience
Projects
2

3. Anshul Arora
Director,
Head of DeliveryCenter
Matrix-IFS
Background
Program Manager, Architect and
Specialist
Experience
11 years. Over 100+ projects in
Compliance,
AML, Trade Surveillance & Fraud
Expertise
Analysis, services & solutions on
multiple
platforms
Education
Degree in Computer Science and
Engineering
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4. You will
Learn:
RPA: Only proven self-funding
project!
How RPA can enhance my Operations team
throughput
How and where to start your
journey
Problems RPA solves for “Fin Crime”
operations
Best options to approach automation
implementation
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5. Problem
Definition:
Industry
Trends
75% – 90% false positives
in Fraud & AML monitoring
80/20 new generation
problems
Data gathering, data sorting,
charting & external systems
dependencyInconsistencies, no standards,
auditing gaps (accessing external
systems)
‘‘Over half the time our investigators
spend on an alert is simple data
gathering.”
- Matrix-IFS Client – Top 10 US Retail Bank
Decentralized systems
Manual tasks and calculations
High turnover – training
overheads
Non-technical operations
Key known contributors:
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6. Lackof standards
Inabilityto supervise standards
Staff turnover&training overhead
Waste of talent
Manual reporting
No decision standards
No audit
Humanerrors Operations
Challenges
People
Processes
Products
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7. Typical
Operations
Process
(Today)
Alert
Cases
Detection System Processes
Internal Data
Sys
Address Data
KYC Data
Social Data
Historical Data
Reports
Fraud Data
Data Valid
Systems
Google
Suspect Lists
System Queries
Excel
Pivots/Macro
Internal Data
Base
RFI Systems
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8. Introduction:
What is RPA?
(1) https://www.cio.com/article/3236451/business-process-management/what-is-rpa-robotic-process-
automation-explained.html
CIO(1):
“RPA is an
application of
technology aimed
at automating
business
processes.”
IRPAAI(2):
“Robotic process
automation (RPA) is the
use of software with
artificial intelligence
(AI) and machine learning
capabilities to handle
high-volume, repeatable
tasks that previously
required humans to
perform…”
(2) https://irpaai.com/what-is-robotic-process-automation/ 8

9. RPA
Application
s (Generic) Insurance Manufacturing BPO
Healthcare FinanceBanking
Many companies provide automation solutions, incl
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10. Why RPA Makes Sense in FIU
FIUoperations similarities:
Predefineddecisionpoints
Predefinedinvestigationworkflow
Triggeredwhenlaunderingscheme suspectedand/orconfirmed
Heavymanualinteractionwiththesystem
AMLalertvolumesarehigherthaneverbefore
RPA
Implementation
Criteria
Tasks decision points
documented
Triggeredat a
particular event
Performed
Manually
Repetitive
tasks
High-volume
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11. Opportunitie
s of RPA in
FIU
…andmanymoreidentifiedduringassessmentphase
Automation
in FIU
External
RFI
Systems
Internal
DB
Systems
One-Stop
Ecosystem
Customer
Historical
Information
Auto
SAR
e-Filing
KYC
Verification
Cognitive
Suggestion
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12. How RPA
is Perceived
Reduceoperationsmanualtasks(RPA)
On-Screenactionvs.Off-Screenaction:
ACTIVE: In the front end,helping yourusers
when then need.
PASSIVE: Working in background anddoing the actions reducing
the risks, automatically closing the alerts
Cutalertvolumes (FalsePositives)
Reduceinvestigation intensity
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13. Path to RPA in
Operations
ScalableRPA
• Providing BOT interfaces
• Information-sharing BOTs
CognitiveRPA
• BOTs getting SMARTER
• BOTs suggestions
• BOTs deliver quality analysis
• Compliance ‘Dream Vision’
TacticalRPA • Scripting & Macros of SOP
• Smart data representation
Predecessor
• Automated data collection
• Data availability
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14. BOTsdevelopment
framework
Pre-builtcommon
externaldata integration
connectors
Integration layer
ratherthan UI
Requires core product
knowledge &support
VendorSolution
Onesize fits all
RPA
Solutio
n
vs.
Service
BuildsBOTsusing core
technologies framework
VendorService
Bespokeconfigurations
Coversintegration &
interfacelayers
Smooth future case
managementupgrades
Usescommon languages
(Java, XML etc.)
Customization to
complement the product
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15. “Investigators focus on
Investigations”
Happy BSA Officer, 2017
 One Screen
 Standardize
d Efficient
 Simple
 Automated
Enhanced Operations Process - New State
Aler
t
Detection
System Processes
Cases
Internal Data
Sys
Address Data
KYC Data
Social Data
Historical Data
Reports
Fraud Data
Data Valid
Systems
Google
Suspect Lists
System Queries
Excel
Pivots/Macro
Internal Data
Base
RFI Systems
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16. A Vision: Strategic Alert Dashboards
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17. RPA
Case Study
The Only
Self-funding
Project
Factors Measure
Case processed per day 250
Factors Measure
Alert Investigation Time
Case Investigation Time
Total # of Investigators – Alert
Total # of Investigators – Case
30 minutes
48 minutes
25
25
Alerts processed per day 400
BEFORE
RPA
Total Cases per
day
Total Alerts per
day
0 200 400 600 800 1000 1200 1400
After RPA Before RPA
RPA Factors RPA Measure
Alert Investigation Time
Case Investigation Time
Total # of Investigators – Alert
Total # of Investigators – Case
10 minutes
15 minutes
25
25
RPA Factors RPA Measure
Alerts processed per day
Case processed per day
1,200
800
AFTER
RPA
Client : US Commercial bank
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18. RPA
Benefit
s
Fast
Operations
Processes
Less
Training
Overhead for
new employees
Increased
Team
Efficienc
y
Fully
Audited
Optimized
Accuracy
BOTs don’t make
mistakes
Cost
Savings
Lower
Risk
Scalable
RPA
per business
needs
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19. Matrix-IFS
RPA
methodology
and approach
Show value andrepeat
Launch
Monitor
Repeat
III
Launch
Monitor
Repeat
RPA pilotintoproduction
RPA pilotimplementation
Assess
Measure
Identify
Evaluate
I
&review current operations model
Time consumed by each task
Identify the opportunities of RPA
Assess
Measure
Identify
Evaluate Calculate ROI
II
Prove
Build
Align stakeholders; value in initial scope
Roadmap toget toTOMby ROI
Prove
Build
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20. Take-aways
from
Today’s
Session
START YOUR JOURNEY TODAY!
All firmshave a varyingdegree
ofoperations inefficiencies
Operations inefficiencies runacross all
Financial Crime
AreML andAIsolutions forthe
operations teams?
RPA: Only proven self-funding project!
How to build RPA vision for yourFIU
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21. Thanks!Questions?
Anshul.Arora@Matrix-IFS.com 21