What’s New in Alessa’s AML Compliance Solution (version 5.4)
- How goAML functionality will enable compliance in more jurisdictions
- Why automated regulatory reporting is a must for overworked compliance departments
- How batch file attachments enable compliance teams to have all supporting documentation for investigations in one place
- About improvements to FinCEN reporting that will ensure faster reporting
- To screen potential customers against sanctions lists and generate a risk score during the onboarding stage
- How workflow decision learning will make your system smarter
- About the new search feature that allows organizations to look for potential red flags, like items in dual-use goods lists
Here is a quick summary of what is discussed in the webinar:
goAML and Other Regulatory Reporting Features
Given the increasing adoption of goAML—an integrated database and intelligence system that collects, analyzes, reports and manages potential money laundering and terrorist financing incidents—the solution now supports goAML reporting.
It automatically identifies and populates goAML regulatory reports from its data analytics engine, validates the information and manages report submissions using its flexible workflow and case management capabilities. It’s a seamless and makes compliance for many jurisdictions faster and easier.
Regulatory Reporting Enhancements
The solution now offers automated file attachments, including transaction history, emails, scanned docs, and more.
For example, if you’re a money services business (MSB) and submit a suspicious transaction report (STR), you’re required to submit 30 days of transaction history around that customer. That is now fully automated, with the solution attaching and including those files with your submission.
Version 5.4 of the solution offers a new Google-style enterprise search that’s not just searching cases, alerts and regulatory reports, but also other sources of data such as export control lists.
Fuzzy matching has been dialed down in order to generate fewer, more focused results. However, the solution can be configured to increase fuzzy matching if desired.
Real-Time Onboarding Due Diligence
Customers can now be screened in real-time to gauge risk levels, reducing the number of post-customer acquisition investigations, detecting issues earlier, and blocking high-risk customers from being onboarded. The solution then sends an alert to the compliance team that indicates why the customer was blocked. The compliance team can then investigate to confirm or override the decision.
Workflow Decision Learning
If a transaction is exactly the same as a previous one, why must it go to compliance each time to make the same decision? The solution can be configured to learn how alerts have been transitioned in the past and then reapply those decisions to future alerts.
This feature is highly configurable, and offers the option to break decisions. The more decisions you make in the application, the better it gets at learning what decisions to make and apply going forward.
Advanced Analytics Models
A rules-based solution is no longer enough to detect fraud and other financial crimes. In recognition of this, our solution fuses rules-based analytics with anomaly detection and predictive analytics using methods such as clustering, data/text mining, machine learning and network analysis, to detect suspicious activity sooner and more accurately.