This blog has from time to time discussed issues around the defensive portion of financial services industry (Banking, Payment Processing, and Insurance etc). Anti Money Laundering (AML) is a critical area where institutions need to protect themselves and their customers from malicious activity. This post summarizes eight key blogs on the topic of AML published at VamsiTalksTech.com. It aims to serve as a handy guide for business and technology audiences tasked with implementing complex AML projects.
Image Credit – FIBA Anti-Money Laundering Compliance Conference
Introduction
Money laundering has emerged as an umbrella crime which facilitates public corruption, drug trafficking, tax evasion, terrorism financing etc. Banks and other financial institutions are expected to conduct business in a manner that protects their countries of operations and consumers from security risks such as laundering, terrorist financing, and corruption (the ML/TF risks). Given the global reach of financial products, a variety of regulatory authorities is concerned about money laundering. Technology has become key to meeting the regulatory expectations as well as reducing costs in these onerous programs. As the below graphic from PwC [1] demonstrates this is one of the most pressing issues facing financial services industry.
The above infographic from PwC provides a handy visual guide to the state of global AML programs.
The Six Critical Gaps in Global AML Programs…
From an industry standpoint, the highest priority issues that are being pointed out by regulators include the following –
- Institutions failing to develop AML frameworks that are unique to the risks run by organizations given their product and geographic mix
- Failure to develop real-time insights into business transactions and assigning them elevated risks based on their elements
- Developing AML models that draw from the widest possible sources of data – both internal and external – to understand a true picture of the business
- Demonstrating a consistent approach across geographies
- Leveraging the latest developments in analytics including Machine Learning to enable the automation of AML programs
- Lack of appropriate business governance & change management in setting, monitoring and managing AML compliance programs, policies and procedures
With this background in mind, the complete list of AML blogs on VamsiTalksTech is included below.
# 1 – Why Banks should Digitize their Operations and how this will help their AML programs –
Digitization implies a mix of business models predicated on agile systems, rapid & iterative development and more importantly – a Data First strategy. These have significant impacts on AML programs as well in addition to helping increase market share.
# 2 – Why Data Silos are a huge challenge in many cross organization projects such as AML –
Organizational Data Silos inhibit the effectiveness of AML programs as compliance officers cannot gain a single view of a customer or single view of a suspicious transaction or view the social graph in critical areas such as trade finance. This blog discusses the Silo anti-pattern and ways to mitigate silos from proliferating.
Cybersecurity – The biggest threat to the Digital Economy..(1/4)
# 3 – The Major Workstreams Around AML Programs
The headline is self-explanatory but we discuss the five major work streams on global AML projects – Customer Due Diligence, Entity Analysis, Downstream Analytics, Ongoing Monitoring and Investigation Lifecycle.
Deter Financial Crime by Creating an Effective Anti Money Laundering (AML) Program…(1/2)
# 4 – Predictive Analytics Across the AML workstreams –
Here we examine how Predictive Analytics can be applied across all of the five work streams.
How Big Data & Predictive Analytics transform AML Compliance in Banking & Payments..(2/2)
# 5 – The Business Need for Big Data in AML programs –
This post discusses the most important developments in building AML systems using Big Data Technology-
# 6 – A Detailed Look at how Enterprises can use Big Data and Advanced Analytics to reduce AML costs –
How to leverage Big Data and Advanced Analytics to detect a range of suspicious transactions and actors.
Big Data – Banking’s New Weapon In War Against Financial Crime..(1/2)
# 7 – Reference Architecture for AML –
We discuss a Big Data enabled Reference Architecture of an enterprise-wide AML program.
Big Data – Banking’s New Weapon In War Against Financial Crime..(2/2)
Conclusion
According to Pricewaterhouse Coopers, the estimates of global money laundering flows were between 2-5% of global GDP [1] in 2016 – however, only 1% of these transactions were caught. Certainly, the global financial industry has a long way to go before they effectively stop these nefarious actors but there should be no mistaking that technology is a huge part of the answer.
References –
- Pricewaterhouse Coopers 2016 AML Survey http://www.pwc.com/gx/en/services/advisory/forensics/economic-crime-survey/anti-money-laundering.html