Challenge:

Ongoing fines levied against financial institutions for failing to detect suspicious activity have demonstrated the importance of having a sound AML compliance program.  To maintain AML detection scenarios current with best practices, rule-tuning exercises have become a highly-valued capability at financial institutions. This tuning needs to be continuously applied over time to identify potential new risks or typologies not covered by the current process.  Institutions must investigate and action a growing number of alerts, including many that are investigated and subsequently deemed false-positives.  The investigation process is largely manual, time-consuming, and error-prone.

Solution:

The Pendo Platform can develop structured data sets from original source/unstructured documents to expedite the alert investigation process.  Further, this unstructured data can be utilized to enrich the structured data feeding the various transactional monitoring systems.

Value Created:

Leveraging unstructured data sources not previously available to transaction monitoring systems (TMS) will expand and enrich the corpus of sources available for analysis and expedite the investigation process.  As a result, institutions can demonstrate that they are actioning investigations in a timely manner, enhancing tuning capability and freeing-up financial crime investigators with more productive alerts to review.