Legal Entity Data Management
Many financial firms have a requirement for a central store where they can master their client and entity data. This data is then used to feed other operational processes such as KYC and Credit throughout the firm.
To respond to this requirement iMeta has developed Legal Entity Manager (LEM), a module of the iMeta CLM platform.
iMeta LEM enables firms to create a golden copy of their entity data, complete with lineage and audit. The system allows data to be aggregated from both internal and external sources according to configurable rules. This aggregated data can be validated automatically using data quality rules. Any exceptions can be sent for remediation or approval based on business rules. Using the configurable human workflow, exceptions can be automatically routed to the relevant team, reducing the lag in having access to accurate and up to date data for key business activities. Any changes to sourced or aggregated data can be quality checked automatically by the system and where appropriate routed to operators for approval. A full audit trail of completed tasks and amendments will be recorded. Finally, the system has a fully customer configurable data model, so new and custom data attributes can be quickly added when required.
To reduce manual effort and increase operational efficiency, iMeta LEM comes with a choice of supported APIs for industry recognised data sources; such as LexisNexis® Bridger Insight® XG, TR Verified Entity Data as a Service, Bureau Van Dijk and Dunn and Bradstreet. Additionally, the platform presents a clean standards-based integration façade to enable rapid integration with internal systems.
iMeta Legal Entity Manager can be used to provide validated entity and hierarchy data and documents to other in-house entity master platforms, or it can be used as the master itself. It also supports data provenance and lineage initiatives, as the audit trail includes information about the original source and value of incoming data, as well as transformation rules applied.