- Money laundering can be escaped via a collection of rules, processes, and technologies known as Anti-Money Laundering (AML).
- Money laundering is split into three phases (placing, layering, and integration), with various controls in place to find strange behavior related to laundering.
- Knowing your consumers, software filtering, and imposing holding periods are all anti-money laundering procedures.
The security world is evolving every day to keep businesses fraud and stress-free. The inadvertent use of the banking system for money laundering activities is a major challenge faced by the financial services industry.
Min Zhu, Deputy Managing Director of the IMF, “Effective anti-money laundering and combating the financing of terrorism regimes are essential to protect the integrity of markets and the global financial framework as they help mitigate the factors that facilitate financial abuse.”
To many people, money laundering appears to be a crime that occurs only in crooked businesses or TV shows. Unfortunately, this type of financial fraud is all too widespread and can wreak havoc on small firms, particularly fintech and financial services that allow consumers to transfer money.
Money laundering refers to the process of converting illegal sources to legal sources. Bad actors launder money to earn revenue from crime because they are legally acceptable before they can be used. It helps terrorists and criminals fund illicit activities, threatens global security, and dampens global economies. Money laundering can land major troubles like hefty fines, criminal charges, damage to reputation, and negative publicity about compliance and lapses among other things. This is the reason why industries remain concerned about money laundering.
As per the resources, money laundering accounts for about 2% to 5% of the global Gross Domestic Product (GDP) – i.e., about USD 2 trillion. Money laundering has significant repercussions on the global economy.
The above figures make it clear as to why money laundering has become a very important financial issue that authorities are trying to stop. Anti Money Laundering (AML) is a worldwide term to prevent money laundering and includes policies, laws, and regulations to prevent financial crime.
Plenty of new measures have been introduced to counter money laundering, and indeed many Governments have established comprehensive Anti-Money Laundering (AML) regimes but they do not come as smoothly as they should. Regulatory authorities introduced the Anti-Money Laundering (AML) regulations and Counter-Terrorist Financing (CTF) policies to identify and prevent such activities.
To identify potential money laundering instances and to address compliance requirements organizations must have in-depth knowledge about how the crime works.
What is AML?
Anti-Money Laundering or AML is a set of measures performed by institutions to comply with legal requirements that help combat the laundering of money and other financial crimes.
In short, the process of converting money from illegal sources to legal sources.
Rising trends in the AML space are as follows –
- Adoption of analytics for fraud detection, linkage detection, and detection of rouge activities.
- Concentration on digital payment-related issues.
- Acceptance of enterprise-level approaches.
- Use of third-party services such as KYC compliance and transaction monitoring.
What is an AML compliance program?
An AML compliance program integrates everything a firm does to meet the compliance norms –
- Built-in internal operations regulations.
- User-processing and vetting policies.
- Accounts monitoring and detection.
- Reporting of money laundering incidents.
The major goal of an AML compliance program is to eliminate, detect, and respond to intrinsic and residual money laundering, fraud-related risks, and terrorist financing.
To construct a robust AML compliance program, one needs to stay safe from non-compliance fees and need to follow quite a few requirements.
Let’s discuss this in detail.
How can businesses remain AML compliant?
All Anti-Money Laundering compliance programs strive to expose internal fraud, money laundering, tax evasion, and terrorist financing within the company. We have listed the three most critical dos that can help you attain these objectives.
· A compliance officer in the team
The procedure we are discussing is not easy to manage and needs trained personnel with knowledge and experience to keep the business in close compliance with the fluctuating regulations and laws.
Compliance must be the moral responsibility of every team member across all organizational structures. The workforce must comprise high skills and be qualified to report and formulate their suspicions.
· Efficient reporting
A robust reporting system helps to provide data about a money-laundering activity to the relevant authorities.
· Being alert of high-risk consumers
Organizations must assess their consumer’s risk profiles and process them accordingly, applying consumer due diligence and enhanced due diligence.
Factors that impact AML compliance
Before developing a compliance program, an enterprise must first analyze and characterize the risks involved and legal obligations.
- The dangers of money laundering that the company faces.
- Respectful local and international laws, as well as penalties for non-compliance.
- Internal company operations that’s questionable.
Organizations should develop strong proposals to enhance the concept of AML compliance practices. It will make the process simpler and prevent negotiation.
How to design an AML program
- Detect suspicious activities.
- Risk assessment.
- Internal practices.
- Make due diligence your focus point.
- Assign roles and responsibilities wisely.
- Report suspicious activities.
- Guide employees to spot and correctly react to Money Laundering (ML) and Terrorist Financing (TF) activities.
- Prevention of criminal attempts.
- Independent audits.
Role of Machine Learning in AML
Machine Learning (ML) is reinventing how fiscal networks work, thanks to significant advances in data science. ML has lots of potential in the banking sector, particularly when it comes to spotting hidden trends and questionable money-laundering operations.
ML helps recognize money laundering typologies, behavioral transitions in consumers, suspicious and strange transactions, transactions of consumers belonging to similar groups, geography, and age, and help reduce false positives.
It also aids in analyzing comparable transactions for focal entities and the correlation of suspicious signals in regulatory reports.
Money launderers will continue to develop new ways to use banks for unlawful purposes. The most challenging component to implementing an effective AML policy is detecting laundering activity in a timely manner. Several innovative technology-based methods and applications (artificial intelligence solutions, machine learning solutions, etc.) are already available to detect, trace, and prevent money laundering.
Though these technological techniques will not fully eliminate money laundering, they will greatly reduce it, and financial institutions should look into using them sooner rather than later.
Stay tuned with us for more information on Anti-Money Laundering (AML) and technology!