Challenge
A large, multi-national bank operates Anti-Money Laundering (AML) compliance programs to identify and report money-laundering and other suspicious activity across its 15 million global customers.
The bank faces significant challenges with the efficiency and effectiveness of its compliance programs. Bank investigators handle a growing number of false-positive alerts, which negatively affect case investigation quality and team productivity, and make it difficult to prioritize and identify true, high-risk money laundering activities.
Moreover, the data required to detect suspicious activities are segregated across several disparate systems, including Know Your Customer (KYC), transaction monitoring, external watchlist screening and several others, resulting in a highly manual investigation process.
Approach
The bank leadership tried a new approach – C3 AI® Anti-Money Laundering – to reduce false positives and increase alert quality to identify actual suspicious activity. C3 AI Anti-Money Laundering leverages advanced, proven, typology-driven risk analytics as inputs to sophisticated and interpretable machine learning algorithms.
Embedding the C3 AI Anti-Money Laundering application within its existing business processes, the bank increased team efficiency and improved prioritization of money laundering and other suspicious activity. Further, the bank can utilize the entity-centric, workflow-enabled application to improve case investigation consistency and streamline regulatory reporting.
Solution Architecture
Proven results in weeks, not years
Get insights into C3 AI’s capabilities, enterprise AI best practices, and highest-value use cases.
Gain insights into the C3 AI Platform's capabilities, its model-driven architecture, and test it against your company's sample data set.
Identify a high-impact business problem and collaborate with the C3 AI team to rapidly build an AI application that solves it.
Scale and deploy a tested C3 AI application into production. Incorporate user feedback and optimize algorithms to drive maximum economic value.