Setting the Standard for Ethical, Transparent, and Secure Data Practices in AML

Executive Summary

Strise revolutionise AML compliance by turning fragmented data into actionable insights through our AML Automation Cloud. At the core of our solution is a steadfast commitment to ethical data practices, compliance with regulations, and transparent processes for vendor evaluation and data quality assurance. This paper outlines how Strise responsibly handles and assesses data to deliver exceptional value to customers while maintaining the highest standards of security and compliance.

Read More:

https://www.strise.ai/aml-automation-cloud-white-paper

Introduction

Tackling AML’s Data Challenges

In AML, the problem is twofold: fragmented datasets and inefficient workflows. Financial institutions often struggle to unify and verify critical information, creating bottlenecks and risks in compliance processes.

Strise addresses these challenges with advanced graph models, transparent use of AI, and robust vendor assessments. By consolidating disparate data sources into a unified, continuously updated model, we enable our customers to achieve compliance efficiently and accurately.

What sets Strise apart

Strise has chosen an architecture where data ingestion and data processing happens before AML case handlers conduct the regulatory required due diligence assessments, screening and ongoing monitoring of their customers. All Strise customers subscribe to the same source of truth for publicly available and traceable data in a multi tenant cloud environment.

Advantages of pre-processing

Strise’s extensive pre-processing ensures powerful capabilities for due diligence assessments, screening, and monitoring. The advantages are best described through concrete cases that occurs across the customer portfolio. One significant advantage of this approach is the ability to handle ownership changes dynamically:

• Dynamic Ownership Changes: When a company undergoes a transaction of ultimate ownership between periodic reviews, and the new owner is a Politically Exposed Person (PEP), Strise automatically screens the new owner against PEP lists, sanctions programs, and adverse media. Users are alerted if the change impacts the client’s risk scoring.
• Conflict Resolution: Strise actively identifies ownership conflicts that arise when manually edited data conflicts with updates from shareholder registers. Users can:
  • Retain the manually edited data for continuity, or
  • Replace it with the latest information from the shareholder register.
• Data Integrity: Strise always retains the original version of the data to allow for reversion if necessary. This ensures the integrity of the source data while enabling flexible editing.

By addressing gaps in continuously updated datasets and combining automated checks with user-friendly collaboration tools, Strise ensures that AML teams can respond to changing information quickly and accurately without compromising compliance.