power of data and technology in aml compliance · 2020-07-30 · power of data and technology in...

Power of Data and Technology

in AML Compliance

Chua Choon Hong

Head of compliance solutions, APAC

Agenda

1. Regulatory Landscape in APAC

2. New Trend

3. Harnessing Power of Data and Technology

Regulatory landscape

in APAC1

Regulations

FATF Recommendations MAS Notice 626

India PLMA

USA BSA and Patriot Act

Cost of Compliance

Key Challenges FI face in AML

Lack of accurate available data…

Ultimate beneficial ownership data not available or

updated...

High percentage of false positives…

Risk scenario and models are not granular enough for a

large diverse client base…

High cost of compliance…

Larger teams are required to review the large quantity of alerts

generated… Late STR often leads to fines by regulators…

Changes to client data is too rapid, the quantum

of change is huge

Trade Finance

Responsibility for Compliance

• KYC on client

• CDD on vessel, country of origin, destination, dual-use

goods, port of call, all parties involved

• Key is to differentiate what is expected and is actual

New Trend2

New Technology Trend

Digital banking

Virtual banking

Block Chain Platform

AMLEfficiency

Speed

Effectiveness

Using Machine Learning on data to

fine tune better quality alerts

Using Robotic Process Automation

to automate and speed up mundane

information retrieval process

Using Artificial Intelligence to

aid decision making process

Making Better Decisions

Align for efficiency & risk appetite

DataPeople

Technology

How can we use data and technology to help people make better

and faster decisions?

Business demand for smarter “RegTech”

Harnessing Power of

Data and Technology 3

Power of Data & Technology

Client

Onboarding

• RPA can be programmed to fetch reference data from BvD for

faster turnaround in client onboarding process

Core

banking

• Enriched profile: Using BvD data to enrich baseline profile AML Analytics

Engine

• Legacy client data with missing or inaccurate data can be

compared with BvD data during ETL

AI and ML• Using ML on BvD data to train the risk models for better quality

alerts

Investigation

• Using RPA API to fetch BvD data to assist alert investigation

Increasing the Depth and Breadth of data

Build dynamic CDD risk profile of your clientsRisk-base approach and ultimate beneficial owners

Risk Factors affecting risk profile

• Industry profile

• Shareholder ownership PEP status

• Directors and contacts

• Stake in subsidiaries in high risk jurisdiction

• Negative news

Deep insights

• Visual analytics for investigation

• Follow money trail of accounts and

account holders

• Enhance investigation with

holistic view of ownership

network

Bangladeshi Heist

Deeper discovery into beneficiary

company and its details

Summary

Harness data to power your AML program

| bvdinfo.com