Artificial Intelligence (AI), for AML, can mine large volumes of data for risk-relevant facts. It enables financial institutions to simplify identifying illicit client relationships, beneficiaries, and links to criminal or terrorist activity during the onboarding phase.

FREMONT, CA: Financial regulations globally are cracking down on banks. As Anti Money Laundering and know your customer (KYC) procedures are getting stricter, hefty fines are being imposed on those found to be in breach of the same. Recent studies have discovered that banks across the globe have been charged with a total of USD 26 billion in monetary penalties in Anti Money Laundering (AML) and sanctions violations over the last ten years. As banks and financial institutions continue to search for digital transformation initiatives to streamline and simplify the customer onboarding process and reduce the risk associated with fraud, many are looking to exploit emerging technologies' potential.

Artificial Intelligence (AI), for AML, can mine large volumes of data for risk-relevant facts. It enables financial institutions to simplify identifying illicit client relationships, beneficiaries, and links to criminal or terrorist activity during the onboarding phase. AI can prove essential when performing repetitive tasks, saving valuable time, effort, and numerous resources that can be refocused on higher client-value tasks. The technology includes various components such as Natural Language Processing (NLP) and Machine Learning (ML), which can together create leapfrog automation opportunities across large parts of client life cycle management (CLM) in areas that are currently labor-intensive, time-consuming, and error-prone.

Here are some of the key ways AI can help AML, KYC, and client onboarding process.

Risk Assessment and Due Diligence

AI can automate the creation and updating of the client risk profile and match this against the classification process, ensuring continued compliance throughout the client life cycle. Also, it can make the process of identifying high-risk clients even easier for enhanced due diligence processes. This creates an association framework that improves the whole process of documenting, analyzing, and storing client information.

Automated Anti Money Laundering

Recent studies on AML reveal that false positives are one of the most challenging for bank compliance teams. Underpinning the alert generation process with AI can result in a fewer number of false positives. While they are a significant part of the AML compliance process, alerts are not enough to support an effective and thorough investigation process. AI can improve the accuracy during the identification of false positives and leverage previously performed steps in the alert investigation process to formulate a recommended next steps approach.