Case Study: Leading Global Information Solution Company achieves 7% accuracy improvement and scalable, faster duplicate detection with Happiest Minds

Deduplication using text mining for a leading Global Information Solution Company

A leading U.S.-based consumer credit reporting agency serving 800 million individuals and 88 million businesses engaged Happiest Minds to address poor search/match accuracy and identify the same person across multiple channels. The client needed a scalable solution to handle rapidly growing data volumes and transactions while reducing duplicate records and improving overall search performance.

Happiest Minds built a new data‑driven Search & Match system using text mining, big data (Hadoop/MPP), LSH in a distributed environment and customized Elasticsearch indexing, delivered in phased releases. The solution scaled horizontally on commodity hardware, integrated as a plug‑in with legacy systems, and produced measurable gains — about 7% improved accuracy, fewer false positives/negatives, a self‑learning analytics model, and reduced licensing and third‑party maintenance costs.