CLIENT SUCCESS

Automating Claims Data Processing for a National Insurance Provider

80% reduction in manual work. Data available in 30 minutes instead of 24 hours. 20+ hours saved every week.

EXECUTIVE TAKEAWAY

A national insurance provider relied on manual downloading and processing of claims data from email attachments. The process was slow, error-prone, and unsustainable as email volumes grew. Data that should have been available in minutes was taking up to 24 hours — delaying reporting pipelines and slowing fraud detection.

01
The Challenge
Manual downloading & processing of email attachments
Delays in reporting pipeline
Data quality issues
Unsustainable process with increasing email volumes
02
Our Approach
Microsoft Fabric-based architecture
Automated workflow for email processing
Python notebook with Graph API integration
Data pipeline with scheduled execution
03
The Outcome
80%
Reduction in manual work
30min
Data availability — down from 24 hours
20+
Hours saved weekly

Manual intervention in file handling was eliminated entirely. Claims data became available in real time, data accuracy improved through automated validation, and the operation gained the scalability to handle growing volumes without adding headcount.

Murkez Perspective

Manual data processing isn't just inefficient — it's a liability. Every hour of delay is an hour where fraud goes undetected, decisions are made on stale data, and people are doing work a well-designed system should handle automatically.

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