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White Paper

AI-Powered Solutions Help Close the Risk-Confidence Gap for AML/KYC Investigations

Examining data for customer screening during onboarding and periodically thereafter is a high-stakes, high-velocity process that too often overwhelms financial institutions. The sheer volume of data to be examined is complex, with hard-to classify fields, multilingual data, and data blind spots.

These escalating data volumes and increasing complexity merge to form the Risk-Confidence Gap, or the widening divide between the amounts and types of data FIs must process to comply with AML/KYC mandates, and the resources they have available to confidently analyze and act on that information. Exacerbating the Gap is FIs’ over-reliance on outdated screening technologies and rules-based processes that require significant human intervention.

Babel Street surveyed financial institutions of varying sizes to understand their compliance challenges around ID verification, development of customer risk assessments, initial sanctions screening, initial AML screening, and adverse media screening. In nearly all cases, these processes were inefficient and inaccurate.

Register for this white paper to learn how FIs can close the Risk Confidence with AI-powered technologies and methodologies for processing the data:

Download the white paper for free.

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