Identity Resolution is a data management process that checks, validates and appends information across devices and digital footprints using a unique matching process to create a single, data-rich profile for a person or business. It resolves customer data duplications and inconsistencies using both data management techniques and trusted reference data in tandem.
Many organisations want to achieve a clean, accurate and consolidated view of consumers and businesses with whom they transact. Whether in the private or public sector (and whether we call these identities customers, prospects, suppliers, students, alumni or citizens) disparate data silos, data quality and imprecise matching can create a major headache in creating that view. Identity Resolution is a unique approach from Experian that combines our data, your data and our technology to give you confidence that your single view of identities will best serve whatever purposes you put it to. Moreover, it puts you in control of the process and offers complete transparency as to how matching decisions have been made.
Download Identity Resolution Product SheetConnect, profile and map data sources
Validate data
Add pinned consumer and commercial data sources
Create, monitor and apply match rules
Resolve duplicates
Evergreen data
Fuzzy matching
Workflow automation
The digitisation of the customer experience, and its inherent implications for fraud and security breaches, is leading to organisations taking a fresh look at what they mean by ‘customer.’ Identity Resolution is the key to knowing who your customers are in a way that is fuller and more holistic than previous approaches.
The solution uses rules-based fuzzy-matching to aid transparency of the matching process across complex data sets. Using supervised machine learning you can train the system to automatically generate new rule sets for one or many use cases.
Pinning data is matched against you own data sets and the results are ingested into Data Studio as a data set for interrogation, further matching exercises and reporting
Potential duplicates are clustered and full control is given as to how rules can be built to either select or build a best, or golden, record
We have native connectors to applications (eg CRM) and big data sources as well as high-speed JDBC connections to relational sources.