Know your customer, or KYC, refers to a broad set of anti money laundering regulatory guidelines that require financial services institutions to verify and certify their clients’ identities, business context, sources and uses of funds, and associated risks involved with maintaining business relationships. This industry framework is used to assess the suitability and related risks of each client business relationship. Historically, KYC has been associated with the “prevention” aspect of anti-money-laundering, or AML, practices. The idea is that if a bank can prevent a suspicious individual from opening an account, then the bank has done its part to limit the illicit movement of money through the financial system. But as technology and criminal behavior has evolved, KYC is now considered to be a continual process by which financial institutions review and evaluate client risk profiles and suitability for the business.
The lines have been blurring between companies that act as financial institutions and those that do not. For example, Venmo started as a cashless peer-to-peer payment provider. But as their strategy evolved to support and manage settlements and transaction clearing, the company fell under regulatory constraints requiring it to engage in KYC practices to help stem money laundering activities within the geographic jurisdictions in which it operates.
KYC is comprised of a set of regulatory guidelines that differ by jurisdiction (United States vs. the European Union, for example) and require financial institutions to conduct sufficient due diligence on clients to mitigate the risk of illicit money movement within the financial sector. KYC colloquially refers to the practice of verifying individuals’ and businesses’ identities as well as verifying that their funds originate from legitimate activities and not, for instance, criminal behavior.
To keep up with criminal behavior and increasingly stringent regulatory requirements, financial institutions must deploy ongoing KYC inspections of clients, taking advantage of all relevant data, including transaction activity, social media data, and news information. However, the increasing speed and scale of transactions and social data require a new technology approach. In addition to processing large quantities of data, financial institutions are finding that it is imperative for KYC officers to take advantage of new technologies like natural language processing, computer vision, and machine learning to enable AI-based insights that drive the most efficient actions and diligence.
The C3 AI Anti Money Laundering application provides a holistic review of client activity that supports ongoing KYC. The application improves compliance officer productivity with intelligent case recommendations, automated evidence packages, and advanced visualizations of key contextual case data, such as negative news, alerts, parties, accounts, transactions, counter-parties, and risk drivers. The application provides transparent, easy-to-interpret risk drivers for each risk score. Unlike rigid rules-based systems, C3 AI Anti Money Laundering models are easily configurable and flexible, enabling intelligent adjustment to changing regulations and criminal strategies. The application uses sophisticated machine learning techniques, including self-learning based on compliance officer output, to identify known and new typologies. Further, enhanced auditability features allow officers and regulators to follow the lineage of client behavior and funds from source to diligence reports.
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