Standardize company names to identify exposure aggregations and policy clash to build unique customer insights
Insurers can have thousands of company name variations across their underwriting data. Yet standardized company names are essential to building a complete picture of insureds and avoiding over-exposure to loss events.
Match incoming names to a comprehensive list such as Capital IQ
Create a harmonized view of insureds, including parent company
Augment with financial intelligence data to build unique insights
Build a set of approved mappings with Machine Learning tools
Challenges
- Disparate company names across multiple source datasets mean aggregations can remain hidden
- Company name reference lists run to tens of millions of records, but matching to them needs to be automated and efficient
- Human review and editing of automated matching results is critical for data quality
