Vendors
日本語
search
  2. //
  3. Reports & insights
  4. //
  5. Transforming AML Investigation with AI: Righting the Automation Imbalance in Compliance Operations

Transforming AML Investigation with AI: Righting the Automation Imbalance in Compliance Operations

Create a vendor selection project
Click to express your interest in this report
Indication of coverage against your requirements
A subscription is required to activate this feature. Contact us for more info.
Celent have reviewed this profile and believe it to be accurate.
We are waiting for the vendor to publish their solution profile. Contact us or request the RFX.
Projects allow you to export Registered Vendor details and survey responses for analysis outside of Marsh CND. Please refer to the Marsh CND User Guide for detailed instructions.
Download Registered Vendor Survey responses as PDF
Contact vendor directly with specific questions (ie. pricing, capacity, etc)
31 January 2022
Neil Katkov

Abstract

Anti-money laundering (AML) compliance has become a significant operational challenge that legacy technology alone cannot solve. Artificial intelligence (AI) technologies can reduce the burden and strengthen compliance by increasing efficiency, enhancing accuracy, and improving consistency in AML operations.

Automated upstream systems generate large numbers of alerts—dominated by false positive alerts—that human analysts must carefully review and decision. This has driven financial institutions to build up armies of investigators, driving AML costs skyward.

Throwing bodies at the false positives problem is not a sustainable solution. Fortunately, artificial intelligence (AI) technologies are now available that can automate much of the compliance investigation workflow typically performed by humans. This frees up analysts to focus on value-added investigation instead of routine, labor-intensive tasks.

Client Access