What challenges did Swiss Re face before AI implementation?

Reporting for the Property & Casualty Reinsurance division was labor-intensive and too slow because the hard-coded system could not deliver insights fast enough. The legacy solution could not handle Swiss Re's data volumes and report changes were delayed by infrequent release cycles.

What was the impact of the AI solution?

The team reduced the load chain by 5 hours and achieved almost 40 percent faster loading than the on-premises system. Swiss Re can develop a dashboard for a whole unit in three to five days instead of months. The new environment handles over 250 base tables and more than 600 million rows. The solution improved self-service analytics and enabled wider adoption across adjacent teams.

Rank#3,309of 3,449

Source

MicrosoftEvidence: Medium50/100

Swiss Reinsurance: Enhancing Insurance Analytics and Reporting with Microsoft Azure and Power BI

Use case typeData platform modernizationUpdated Jan 1, 2024

Swiss Re built an in-house analytics and business intelligence solution called Cockpit and then modernized it with Microsoft Azure and Power BI to deliver a single source of truth for Property & Casualty Reinsurance reporting. The new platform centralizes data, supports self-service analytics, and processes structured, unstructured, and semi-structured data through Azure services.

Organization: Swiss Re
Industry: Insurance
Location: Switzerland
Published: January 2024

Reported outcomes

600,000,000 rows

processed data volumeOther quantified impact

−40%data load time5 hoursload chain time90%dashboard development time250 tablesbase table count

Strategic outcomes

Other strategic outcomeEnabled business users to perform advanced analytics independentlyCost efficiencyReduced operational costs through pay-for-use cloud servicesScale & capacityExpanded the model across adjacent teams

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Data load time: 40% decrease

Microsoft Customer StoriesJan 1, 2024Customer storyExplicit claimMedium evidence strength

almost 40 percent faster than loading the same amount of data with the on-premises system

Normalized claim

Load chain time: 5 hours decrease

Microsoft Customer StoriesJan 1, 2024Customer storyExplicit claimMedium evidence strength

With Synapse, the load chain was reduced by 5 hours

Normalized claim

Dashboard development time: 90%

Microsoft Customer StoriesJan 1, 2024Customer storyInferred claimMedium evidence strength

We can develop a dashboard for a whole unit in three to five days, compared to months with the old process

Normalized claim

Processed data volume: 600,000,000 rows increase

Microsoft Customer StoriesJan 1, 2024Customer storyExplicit claimMedium evidence strength

more than 600 million rows

Normalized claim

Base table count: 250 tables increase

Microsoft Customer StoriesJan 1, 2024Customer storyExplicit claimMedium evidence strength

currently totals over 250 base tables

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: Swiss Re
Provider: Microsoft
Maturity: Unknown
Linked source: Microsoft Customer Stories

No explicit deployment-stage evidence found.

Customer identity supportedSource describes one deploymentMaturity evidence evaluated

Primary read

Use case focus

Showing 2 of 2

1Data platform modernization
2Operational analytics

Reporting for the Property & Casualty Reinsurance division was labor-intensive and too slow because the hard-coded system could not deliver insights fast enough.
The legacy solution could not handle Swiss Re's data volumes and report changes were delayed by infrequent release cycles.

Swiss Re combined Power BI with Azure Synapse Analytics to create a scalable reporting platform.
The architecture uses Azure Data Factory, Azure Data Lake Storage, Azure Databricks, Azure Synapse Analytics, Azure Analysis Services, and Power BI Premium to ingest, clean, transform, and distribute data for reporting and analytics.
The company also established a data governance framework and security approvals for exposing reinsurance data in Azure.

Technologies

Azure Synapse Analytics Azure Data Factory Azure Data Lake Storage Azure Databricks Power BI Premium Power BI Embedded Azure Analysis Services

The team reduced the load chain by 5 hours and achieved almost 40 percent faster loading than the on-premises system.
Swiss Re can develop a dashboard for a whole unit in three to five days instead of months.
The new environment handles over 250 base tables and more than 600 million rows.
The solution improved self-service analytics and enabled wider adoption across adjacent teams.

Architecture

Data was migrated to Azure, where Azure Data Factory and Azure Data Lake Storage bring together structured, unstructured, and semi-structured data. Azure Databricks cleans and transforms data, Azure Synapse Analytics and Azure Analysis Services provide the warehousing and compute environment, and processed data is pushed into Power BI Premium datasets for reporting and embedded analytics. The deployment includes security and data governance approvals.

Sources & evidence1

Evidence: Medium50/100Evidence strength