Computers greatly simplify and speed up some aspects of human thinking processes. Artificial intelligence technology applications allow us to expand the complex operations performed manually or do it automatically. Also, artificial intelligence technologies are integrated with other computer-based information systems. The capabilities and applicability of computers are being increased rapidly.
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As a result of advanced transformation in information technologies, artificial intelligence can imitate human intelligence and develop and develop it with the information it collects to fulfill its tasks. Simultaneously, these machines appear in video games, suggestion engines, and systems such as smart assistants. Along with these, artificial intelligence also provides solutions in anti-money laundering and know your customer compliance activities.
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AI is incredibly valuable when performing repetitive tasks, saving valuable time, effort, and resources to focus on higher client-value tasks. AI technologies can create leapfrog automation opportunities across vast parts of client life cycle management (CLM) in areas that are currently labor-intensive, time-consuming, and error-prone. Artificial Intelligence is taking a significant part in the world, but how is it helping financial institutions meet their compliance challenges?
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Artificial Intelligence (AI) takes KYC (Know Your Customer) and AML compliance to the next level. AI isn’t just a technology — it is a collection of related technologies offering the potential to automate workflows and quickly analyze large volumes and different types of data. Some of the implied advantages of using Artificial Intelligence in KYC and AML are examined below.
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5 AI Solutions For AML And KYC Compliance
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1) Enhanced Due Diligence
Enhanced Due Diligence is a KYC process that provides a broader analysis of potential business partnerships and highlights risk that cannot be detected by Customer Due Diligence. EDD has lots of procedures, some of are; use a risk-based approach, tracking ongoing transactions, negative media, and negative control, visit on-site, prepare for more investigation strategy, develop an ongoing risk-based monitoring strategy
AI-enhanced EDD provides a much more comprehensive and holistic view of a new customer’s business relationships and financial activities, allowing financial institutions to make more informed choices about who they prefer to do business with.
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2) Ultimate Beneficial Ownership
The Ultimate Beneficial Owner defines the person who ultimately owns or controls a customer or the real person on whose behalf a transaction is being conducted. The lack of disclosure of UBOs paves the way for people to launder money through businesses. Therefore, countries should have an awareness of UBO in the fight against money laundering and terrorist financing. For companies, UBO’s are;
- people who have at least a 25% stake in the capital of the legal entity.
- people who have at least a 25% voting right in the general assembly.
- people who are beneficiaries of at least 25% of the capital of the legal entity.
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The identification and verification process for UBOs should be performed during account opening while updating KYC information when obtaining banking services/product forms. Policy, procedures, and processes must ask the account holder to declare the UBO, imposing an obligation on the account holder to update the Financial Institution if the declared UBO is changed.
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3) Transaction Monitoring
Financial Institutions can control billions of transactions by automating the transaction monitoring process. The Transaction Monitoring process is a requirement for businesses under AML obligations.
AML transaction monitoring controls typically generate high levels of false-positive alerts and critical operational workloads. The cost issue is further amplified by inefficiencies in the investigation process, creating a substantial divide among the efforts employed versus the impact of transaction monitoring controls. AI gives meaningful opportunities to significantly reduce operational cost with no detriment to effectiveness by introducing machine learning techniques at different stages of the transaction monitoring process.
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4) Managing Regulatory Change and Compliance
AI’s ability to detect patterns in a vast amount of text enables it to form an understanding of the ever-changing regulatory environment. Further, Natural Language Processing (NLP) can examine and classify documents, extracting beneficial information such as client identities, products, and processes that can be impacted by regulatory change through keeping the bank and the client up-to-date with regulatory changes.
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5) Improved Client Onboarding and Document Management Automation
Digital transformation, stringent regulatory requirements, and evolving customer expectations force financial services institutions to develop new client management strategies that can build better customer experience, increase revenues, and ensure regulatory compliance.
Client onboarding is becoming increasingly complex, with financial institutions spending excessive amounts of time and money manually processing checks. Automatic KYC verification leverages advanced AI and machine learning technologies to ensure that your clients face regulatory standards without a high dependency on internal resources. Onboarding new clients in a highly-regulated industry can be complicated. Fortunately, advances in technology enable financial institutions to implement automated solutions that offer a myriad of benefits at a much lower cost than traditional processes.
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Published on Sanction Scanner
