Compliances

Technology and Data Analytics to Enhance AML Compliance

Anti-money laundering (AML) refers to the laws, regulations and processes, the compliance of which is required by the business to stop financial crime. Criminals use money laundering in an attempt to conceal illicit funds such as income from drug dealing, human trafficking and terrorist financing. Businesses that move money must comply with AML regulations with an effective AML compliance program.

Traditionally, AML compliance has been an expensive, tedious and burdensome process for banks and other financial services. But with the introduction of big data and new technologies using artificial intelligence, this process can be streamlined and more effective than ever. Data analytics combined with machine learning permit businesses to fine-tune transaction monitoring rules and enable tracking of more suspicious activity and reduction of false positives. The advanced case management tools make investigation and reporting easier than ever. The present article shall discuss the role of technology and data analytics to enhance AML Compliance. 

Understanding Technology and Data Analytics

One of the most prevalent approaches in technology and data analytics to enhance AML Compliance is Big Data. It refers to the large volumes of information that are too vast to process by traditional means. By using big data analytics, businesses can trace patterns followed by extracting valuable insights from these data sets. For example, it can increase operational efficiency by identifying and fixing recurring issues.

Big data is ubiquitous in business, and a variety of data sources are available for answering questions in an instant. This means that risk assessment can be performed in real-time, i.e. right at the time of the creation of an account by the users. It transforms what used to be a manual task and enables automation of risk management and advanced reporting.

Reasons for the Growth of Technology and Data Analytics to Enhance AML Compliance

The reasons for the growth of Technology and Data Analytics to Enhance AML Compliance are discussed below –

• Engagement in the Digital Space

Since the introduction and evolution of technology, customers have been turning towards digital solutions rapidly due to such solutions offering a good deal of user security; and convenience. Businesses also tend to develop such systems best aligning with their end-user needs. Companies adopting digital-only systems have a greater chance of meeting the goals of their business, as per a study by Adobe. The introduction of artificial intelligence (AI) and financial technology services is one such development that has transformed the corporate sector and customer interaction in the digital space.  

• The Need for the Protection of Financial Systems

Banking on the technology trends isn’t only businesses but also cybercriminals exploiting the legal, financial system through the use of sophisticated ways, thereby making it increasingly essential for companies to invest in better Know Your Customer (KYC) practices in order to prevent instances of identity theft which can, in turn, reduce financial crime is reduced. 

The willingness of customers for opening accounts or performing transactions with businesses on a daily basis calls for a robust infrastructure for the identity verification of potential clients. In this respect, regulatory technology purpose-built on customer risk profiling and intelligent transaction monitoring has become the need of the hour. 

• Supervision Compliance Standards

Due to the surge in online user engagement and heightened privacy and enterprise data breaches, global regulators have stepped up to enforce more stringent compliance obligations. Now, the entities operating in the financial and corporate sectors are required to develop a risk-based AML approach for the purpose of meeting the regulatory requirements. 

Regulatory watchdogs like FATF and FinCEN ensure the conformity of the financial industry with Anti Money Laundering compliance laws, as the non-compliance with these standards often results in the imposition of hefty fines and penalties, which can lead to the incurrence of financial loss as well as a declined market reputation.  

Role of Technology and Data Analytics in Enhancing AML Compliance

The ability of Technology and Data Analytics to access an unprecedented amount of data, often in real-time, has led to the creation of new business opportunities and has become a driving force of the information revolution.

In the financial sector, technology and data analytics can be utilised for regulatory issues, especially for anti-money laundering (AML) purposes. AML authorities now use such technologies for controlling and monitoring tasks. Companies in the financial sector cannot afford to miss out on these opportunities to remain competitive. Therefore Technology and Data Analytics can enhance AML compliance in the following ways-

Effective Due Diligence 

Earlier, business clients, irrespective of being partner entities or potential customers, associate ties with certain organisations. They must take part in KYC and Customer Due Diligence procedures. These practices are aimed towards the reduction of the possibility of criminal identities opening accounts with legitimate businesses for money laundering. Often, businesses take too long to onboard new customers, and the KYC process isn’t time and resource-efficient. 

Recently, the inclusion of Technology and Data Analytics in customer identification systems is turning the tables in favour of enterprises. Using these intelligent tools, data-gathering methods can be significantly optimised, especially for banks that take up to weeks for gathering customer data from numerous sources. By using  AI-based algorithms, the large amount of data can then be minimised by the selection of only information relevant for KYC¹ verification.  Apart from this, Technology and Data Analytics can enhance AML Compliance through effective due diligence in the following ways.

• Optimised Risk assessment of Potential Clients
• Effective AML Screening through precise data
• Filtering out negative information in EDD checks
• Detection of suspicious activity and its timely reporting
• Reduction in the false positives in customer due diligence

Monitoring High-risk Transactions

A transaction monitoring system is essential to any AML compliance program. An intelligent data-driven solution can help in analysing customer transactions followed by categorising them as suspicious or legitimate on the basis of certain threshold values. This automates the process of the generation of Suspicious Activity Reports (SARs) that are sent to financial regulators.

These act as a fine measure in tackling monetary crime and possible terrorism financing. AML transaction monitoring software utilises data analysis and machine learning tools for the reduction of the no. of false positives to flag and report unusual high-risk transactions, thereby eliminating the requirement for manual and tedious checks.    

Adverse Media & Sanction Screening

Big data methods offer a robust mechanism to filter out unnecessary and redundant information when it comes to Enhanced Due Diligence, thereby allowing enterprises and financial institutions to acquire data from different sanction lists, extract essential information from them, and conduct AML screening checks on high-risk clients. This often begins with a risk assessment of the client where they assign a particular score on the basis of the no. f matches in those certain watch lists.

If the customer frequently makes large transactions or belongs to adverse media screening, a high-risk country, PEP compliance checks and other Watchlist screening checks are vital. Big data analytics tools enable organisations to connect data points by using pattern recognition models for performing risk-based customer profiling, ultimately leading to effective compliance with AML and KYC laws and regulations.    

Compliance with KYC and AML Laws

In an attempt to prevent money laundering, financial entities face a lot of stringent regulatory criteria. These checks, at times, are impossible for manual verification experts to conduct on their own. Considering the regulatory burden, Using Technology and Data Analytics is a viable solution which suitably addresses compliance obligations. Enterprises are now using these intelligent solutions to meet AML requirements and save them valuable time by performing reliable and time-efficient KYC of customers in light of compliance standards.

Conclusion

Undoubtedly the financial sector is in a changing phase that will be shaped by stricter regulatory requirements and decisively transformed by technological progress. Digitalisation has now found its way into all business areas of the financial institutions’ cosmos and will fundamentally change today’s conventional organisational structures of financial institutions.

In the spectrum of compliance activities, in addition to the digitisation or automation of audit activities, the evaluation of huge data populations through technology and data analytics plays an increasingly important role in tracking activities, showing developments, and thus making regulatory risks visible.

Frequently Asked Questions

Read Our Article: Knowing the Legalities of Anti Money Laundering Compliance in India

1. https://en.wikipedia.org/wiki/KYC