What is Anti-Money Laundering?

Anti-Money Laundering (AML) consists of technologies and procedures to prevent the financial crime of disguising ‘dirty money’ into legitimate money. Money laundering is a financial crime, financial institution would need abide by legal requirements to closely inspect and report any suspicious activities.

How Anti-Money Laundering works?

Before conducting AML, financial institutions need to fully understand how such crimes can happen. 

There are three stages when completing Money Laundering:

  1. Placement: These illegitimate money are often placed in cash-based businesses and breaking up large transactions into smaller transactions under the reporting amount.
  2. Layering: Criminals would hide the trail to the illegitimate money so that it’d be difficult for investigators to track the transaction. This includes converting the funds into another form and disguise the ownership of the money.
  3. Integration: This is when the illegitimate money is turned into ‘clean money’, where it appears as legitimate personal or business transactions and re-enter the economy.

Financial institutions need to follow measures and comply to regulation requirements:

  1. Know-Your-Customer (KYC) / Customer identification: Thorough identification and verification of customers is needed to prove legitimacy. A more in-depth documentation is required.
  2. Detect and report suspicious activities: There are published AML guidelines made by regulatory agencies, financial institutions would need to monitor activities such as suspicious cash deposits or withdrawals.
  3. Regulatory report: This report is made when there is any large currency transaction that occurs above the threshold.

An AML program needs to use data and analytics to track any unusual activities, including inspection of customers, transactions and other related behaviours. With the Cognitive Automation, artificial intelligence technologies can help financial institutions automate a wide range of manual processes. This will save many hours of human labour while reducing and preventing financial crimes.

How Bank Moves 5x Faster with Cognitive Automation: A Case Study – Trade Finance | Corporate Banking

How can Gleematic help?

Gleematic’s Cognitive Automation technology can help financial institution to effectively identify suspicious financial activities while automating data related processes. Gleematic bot can used to collect customer’s information through various sources for verification. Processes such as sending out emails to staffs and clients, request necessary KYC documentation, client screening, as well as transaction monitoring can all be automated. Gleematic can effectively monitor and assess client’s risk level while automating tedious data collection process with high accuracy.

Read more about our AML Case study: Cognitive Automation
for Anti-Money-Laundering

Written by: Reiko Anjani