By FINTECH Books Contributor, Ben Lis
Merging regulatory compliance data is a challenge when the data sources do not share a common id. Solutions to this problem have typically required large amounts of manual processing. Entity resolution solves this problem with little or no manual processing. You can use it to solve problems you couldn’t solve before.
Entity resolution uses techniques from machine learning (ML), natural language processing (NLP) and fuzzy matching to solve the problem of merging data with no common id. Used judiciously, entity resolution delivers on the holy grail of AI in RegTech: greater efficiency and lower costs.
This is a primer on entity resolution. It uses a real-world example to provide the reader an understanding of what entity resolution is, where it is best applied and how it works. It requires no knowledge of AI to follow, but it does assume the reader has a basic understanding of IT concepts.