Alacra Concordance is an Entity Identifier Mapping service enabling financial institutions and other organizations to more effectively manage their customer, prospect and counterparty information.

Concordance is a four-step process:

1. Data analysis and cleansing

2. Matching of customer records to the Alacra masterfile

3. Appending of publicly available and proprietary identifiers

4. Ongoing maintenance including automatic updates for corporate actions and other events

Data Analysis and Cleansing
Customer files are analyzed and scrubbed to eliminate duplicate records within and across data sources, normalize varying data structures and validate information.

Match
Using a sophisticated matching engine, customer records are matched to the Alacra masterfile of public companies, private companies, municipal issuers, special purpose vehicles, sovereigns and other issuers. High-scoring matches are automatically added to the client master company file. Low-scoring or non-matches are manually reviewed by Alacra analysts who reconcile and add to the master company file.

Data Analysis and Cleansing
Public and proprietary keys are appended to each record. Public keys may include such identifiers as ticker, CUSIP, ISIN, SEDOL, CIK and UK registration numbers, as well as industry classifications such as GICS, NAICS and SIC codes. Proprietary keys are available from more than 50 publishers including Moody's, Fitch, S&P, Market RED, DUNS, Reuters, Thomson, Factiva and more. Legal entity information and additional data elements such as current credit rating or ultimate parent information may be appended as needed.

Maintenance
Using daily inflows from our vast array of content sources, Alacra provides seamless updates to clients. Corporate actions and events are tracked and distributed through daily or intra-day updates to the Master Company File. Summary reports of corporate events, including links to source documents, are available as required. Customer files are analyzed and scrubbed to eliminate duplicate records within and across data sources, normalize varying data structures and validate information.