Case Study: Credit Scoring Company achieves unified data across silos and more accurate credit scoring with TigerGraph

Credit Agency Connects Its Data Silos with TigerGraph

Credit Scoring Company, one of the three largest consumer credit reporting agencies with data on over 800 million consumers and more than 88 million businesses, faced a major challenge: conducting billions of credit checks annually across segmented, industry-specific data silos so that analyses for the same person in different lines of business (mobile, mortgage, utilities) weren’t linked. To solve this without disrupting existing systems, they selected TigerGraph’s graph analytics platform to create a unified data fabric and link customer records across silos.

TigerGraph implemented a graph-based data fabric (deployed for global rollout on GCP) that links a person’s credit checks across accounts and up to four degrees of separation, supporting required scale (up to 1,000 requests per second at peak). As a result, TigerGraph enabled more accurate credit score predictions and faster, more comprehensive risk assessments, reduced analysis time and effort, and unlocked the ability to create new data products by combining previously siloed information.