Data Quality Anti-Money Laundering (Unique Archive)

Anti-Money Laundering Monitoring System
[La soluzione Irion] It immediately convinced us. So much so that we immediately went ahead even with a use outside of Data Quality […] that was the driving force.
Francesco Garbellini
Information Governance & Data Quality Manager

Requirements

Automated, continuous, traceable and reconstructible monitoring

Automation and efficiency

Fully automated process from data acquisition to outcome production

Input data storage with possibility of consulting it: Master Data, Movements (from sectoral data streams), Unified Storage Automated reconciliation Analysis of the results via special monitors

Flexibility and Traceability

Verification threshold parametrization and possibility to introduce new controls

Definition of matching rules between the ledgers and the Centralized Computer Archive Storage with the operations of data and metadata modification Highly traceable process with the possibility to reconstruct it over time

Autonomy

A simple and intuitive interface for the user to modify filters, keys, and matching rules

Quick implementation of new reconciliation chains (Master Data, Current Accounts, Securities, etc.)

Building a bridge between Business and IT

Solution

Data Quality and Anti-Money Laundering with Irion EDM

Capabilities

Some of the Irion EDM features used: Metadata Driven Engine, Execution Datastore Human Task Interface Rule User Lab Automatic Rule Documentation

Results obtained

Rapid grounding of the solution (the project lasted about 6 months) Storage in a repository of the results of the processing and the calculation logics used

Possibility to consult the contents of these repositories via user interface Management and, if necessary, modification of the reconciliation rules via a simple and intuitive user interface

Presence of a series of monitors for users to perform even complex analyses of the reconciliation outcomes Reduction in the cost of inevitable recycling and tuning of controls in progress

Challenges

Flexible, high-performance and automatic system

Data Integration Transformation
Fully automated acquisition, transformation, integration and filtering of input data
Data Warehousing Data Quality
Creation of historical archive for consultation —– Execution of standard technical controls generated automatically on input flows Execution of reconciliations between sectoral and AUI flows, based on matching keys definable via rule editor
Data Aggregation and Reporting
Availability of a series of monitors for consultation and analysis of reconciliation outcomes, discards of records not due
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