Case Study: a leading global insurance provider cuts underwriting time by 25% with DQLabs

Leading Global Insurance Provider cuts underwriting time by 25% with DQLabs

The customer, a leading global insurance provider, faced challenges with incomplete and inaccurate data that impacted predictive model accuracy. Data silos, schema drift, and delays in data availability were affecting critical operations like underwriting and fraud detection. To address this, they partnered with DQLabs to implement its data quality platform.

DQLabs provided a solution featuring business-defined data quality rules, automated issue management with JIRA integration, and a no-code visual rule builder for business users. This implementation resulted in a 25% reduction in underwriting cycle time, an 18% improvement in pricing precision, and a 40% faster regulatory reporting timeline. DQLabs also empowered the customer to triple self-service rule creation, reducing engineering support by 40%.