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Insurance BrokerageSourced

Case Study: MRH Trowe saves 4,000 hours and EUR135,416 a year by automating insurance data with Matillion

MRH Trowe Case StudySourced & dated by Case Study Desk
Key facts · TL;DR
Company
MRH Trowe
Industry
Insurance Brokerage
Challenge
Automate manual, document-heavy insurance data processing across divisions.
Headline result
4,000 labor hours and EUR135,416 saved annually, with document processing cut from minutes to seconds

Key results

4,000 hrs
labor saved per year
EUR135,416
annual labor cost saved
minutes to seconds
document processing time

The challenge

MRH Trowe, a German insurance broker, handled large volumes of insurance documents through manual, time-consuming processing. The team needed a unified data model across insurance divisions and higher data quality without the manual labor.

The solution

MRH Trowe built no-code data automation on the Matillion Data Productivity Cloud, combined with Snowflake's Document AI, to extract and process document data and apply quality gates. This established a single, unified data model across insurance divisions.

With this solution, we're pioneering a unified data model for all insurance divisions, enhancing data quality through effective quality gates.

MP
Malte Polley
Team Leader, Data Analytics and AI, MRH Trowe

The results, in context

MRH Trowe reported saving 4,000 hours of labor and EUR135,416 in labor costs annually. Per-document processing time dropped from minutes to seconds, while data quality improved through automated quality gates.

Products used

Matillion Matillion Data Productivity Cloud