5 AI Advantages for AML and KYC Compliance

Meta Description: Artificial intelligence has taken the world by storm, and is considered as an invaluable asset for enabling businesses to meet regulatory obligations.

Due to advancement in information technologies, artificial intelligence, or AI for short, has the ability to imitate human intelligence, identify repetitive patterns and use the information it collects to fulfill tasks. AI-powered software are increasingly used today in video games, search engines, and software such as virtual assistants. In addition to these, artificial intelligence also provides solutions for AML (Anti-money Laundering) and KYC (Know Your Customer) compliance.

Why is Artificial Intelligence Necessary?

Artificial intelligence has proven to be invaluable for performing activities such as completing recurring business tasks, saving time, effort, and resources that allows organizations to focus on more customer-oriented tasks. With the help of AI technology, frauds such as identity theft, account takeovers and phishing attacks can be substantially reduced through enhanced security systems. Without a doubt, artificial intelligence plays a significant role in today’s technologically advanced world, but how is this technology assisting financial institutions in meeting KYC and AML compliance challenges?

AI takes regulatory compliance to the next level by offering companies the ability to automate business operations and rapidly analyze large volumes of customer data. Five advantages of using artificial intelligence in KYC and AML are listed below.

Enables Transaction Monitoring

Financial institutions are able to keep an eye on billions of transactions being made on a day-to-day basis by enhancing the transaction monitoring process through AI-powered AML screening or KYC solutions. As ongoing transaction monitoring is a requirement for AML compliance, AI-backed solutions are able to automate and streamline the entire process.

Previously, manual methods of transaction monitoring were considered laborious and typically led to numerous false-positive alerts and operational workloads. As traditional methods were more error-prone, it caused inefficiencies in the monitoring process. On the other hand, artificial intelligence enabled technologies have provided vast opportunities for significantly reducing operational costs while also ensuring high levels of accuracy at different stages of the transaction monitoring process.

Enhanced Due Diligence

Enhanced Due Diligence (EDD) provides a deeper analysis of potential high-risk businesses or customers, and is used to identify the risks that might have been left undetected through Customer Due Diligence (CDD).

EDD and CDD both are a part of the KYC process. EDD involves a higher level of identity verification by collecting the customer’s Personally Identifiable Information (PII) such as their full name, date of birth or address, and evaluating this information through a risk-based approach.

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A risk-based approach for EDD provides businesses with a better understanding of high-risk individuals by accurately identifying their risk level. By identifying exactly what risk the business or individual in question may pose, companies can easily weed out fraudsters before they cause any damage.

AI-enhanced CDD offers a holistic view of the existing or new customer base by closely monitoring their financial activities and collecting additional documents for automated verification, all of which enables institutions to make more informed decisions about who they prefer to form a business relationship with.

UBO Identification

Previously, verifying and validating a business entity was a tedious process for both the business entity and the financial institution. Clients were asked to provide official ID documents to the financial institution that was necessary for maintaining the ‘authority record” of the business. In the event a business entities required enhanced due diligence based on the level of risk associated with them, financial institutions would then implement further analyses, such as requesting for the company’s official registration form to verify the information submitted, identifying the UBO (Ultimate Beneficial Owners) and conducting a manual KYC check for verifying the identity of each ultimate beneficial owner.

For organizations, UBO’s are beneficiaries that have at least a 25% stake in the capital of a business. Today, with the help of automated KYC verification solutions, Ultimate Beneficial Owners are accurately identified with the help of artificial intelligence and deep learning algorithms that enable OCR (Optical Character Recognition) technology and NLP (Natural Language Processing). These technologies allow organizations to accurately identify, extract and analyze UBO details contained in official ID documents. This way, financial institutions can determine who they are dealing with and who to hold accountable in case of any suspicious business transaction.

Improved Customer Onboarding and Verification

The rising prominence of digital solutions, robust regulatory requirements, and evolving customer preferences force financial institutions to devise advanced client management strategies to provide better customer experiences, increase company revenues, and ensure regulatory compliance.

Customer onboarding has become increasingly complex, due to which financial institutions are spending excessive amounts of time and resources to replace manual verification checks. Automated KYC authentication leverages advanced artificial intelligence and deep learning algorithms to ensure that businesses meet regulatory standards without compromising on customer convenience. Onboarding new customers in a highly-regulated industry can become burdensome. Fortunately, digital solutions allow financial institutions to implement verification processes that offer a myriad of advantages at a much lower cost than manual processes.

Enhanced Data Analysis

Due to an ever-increasing number of regulatory requirements, information overload becomes a major issue. Through machine learning techniques and natural language processing (NLP), artificial intelligence has the ability to overcome this challenge by accurately analyzing unstructured data, screening business entities through global criminal watchlists, sanctions and PEP (Politically Exposed Persons) list, identifying legitimate customers from fraudsters, and authenticating ID documents within seconds.

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Another challenge businesses have to face is that of money laundering, where launderers employ sophisticated schemes to hide the true source of their illegally-obtained funds, making the dirty cash untraceable. Systems enhanced through artificial intelligence models are capable of uncovering such complex transactions. Through AML screening software, companies can better analyze customer’s transactions, initiate further investigation and enable them to file for Suspicious Activity Reports (SARs) — a process that is mandatory for AML compliance.

Key Takeaways

  • Artificial intelligence has proven to be invaluable innovation
  • AI takes regulatory compliance to the next level by offering companies the ability to automate business operations
  • AI technology enables business to conduct ongoing transaction monitoring, enhances customer due diligence, helps in the identification of UBOs, streamlines customer onboarding and verification and enables advanced data analysis

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