Case StudyReinsurance

Global Reinsurance Company:
3-4 Weeks → 30 Minutes

How we automated a complex geospatial analysis workflow at enterprise scale, achieving 99%+ time reduction and enabling 20x capacity increase.

3 month engagement

2 engineers + client team

Databricks + Azure

Before and after transformation: cluttered analyst workspace with maps and spreadsheets becomes clean automated dashboard

RESULTS SUMMARY

Time Reduction

99%+

3-4 weeks → 30 minutes

Cost Savings

90%+

Compute + licensing

Scale Increase

20×

2-3 → 50+ countries/year

Not theory. Not estimates. Real production system processing 50+ countries annually at a top-5 global reinsurer.

The Challenge

A global reinsurance company conducted geospatial analysis for catastrophe risk assessment across multiple countries. Each country analysis required 3-4 weeks of full-time analyst work end-to-end.

PROBLEM 1: DISCONNECTED TOOL SEQUENCES

ArcGIS Desktop → Excel → Manual QA → ArcGIS → Report compilation. Each transition required manual data export, reformatting, and re-import.

PROBLEM 2: EXTENSIVE DATA WRANGLING

80%+ of time spent on repetitive data preparation: downloading, clipping, reprojecting, joining, cleaning. Only 20% on actual analysis.

PROBLEM 3: MANUAL QUALITY CHECKS

Analysts manually validated outputs by visual inspection and spot-checking. Errors discovered late in the process required starting over.

PROBLEM 4: SCALING BOTTLENECK

Processing 2-3 countries per year manually. Expanding to 50 countries would require hiring 17× more analysts—financially impossible.

The company faced a strategic decision: either accept limited portfolio coverage or find a way to automate the analysis workflow.

Before vs. After Automation

Side-by-side comparison of the manual vs. automated workflow

Manual Process

Time per country3-4 weeks

Annual throughput2-3 countries

Process type100% manual

Tool integrationDisconnected

Automated Pipeline

Time per country30 minutes

Annual throughput50+ countries

Process typeFully automated

Tool integrationEnd-to-end pipeline

Data engineer working at standing desk with Databricks notebook and Azure architecture on curved monitors

Our Solution

We rebuilt the entire workflow as a cloud-native automated pipeline on Databricks with Azure infrastructure.

TECHNICAL ARCHITECTURE

Cloud Platform

Scalable compute and storage infrastructure

Databricks · Azure Blob Storage · Azure Functions

Python Automation

Geospatial data processing and analysis

GeoPandas · Rasterio · Dask · NumPy

Data Formats

Cloud-native formats for performance and scalability

GeoParquet · Cloud Optimized GeoTIFF · STAC Catalog

Orchestration

Automated execution and integration

Databricks Workflows · REST API · Event-driven triggers

KEY IMPLEMENTATION DECISIONS

Vectorized Processing with GeoPandas

Replaced cursor-based ArcPy operations with vectorized GeoPandas operations. This single change delivered 10-100× speedup for spatial operations.

Cloud-Native Data Formats

Used GeoParquet for vector data and Cloud Optimized GeoTIFFs for raster data. Enabled parallel I/O and eliminated serialisation bottlenecks.

Automated Quality Validation

Built QA checks directly into the pipeline: geometry validation, completeness checks, statistical outlier detection. Errors flagged immediately.

One-Button Operation

Created simple REST API. Stakeholders enter country code, click "Run." Pipeline handles everything. Results delivered via email in 30 minutes.

What We Delivered

Production-ready automated pipeline deployed to Azure

Complete Python codebase with documentation

Infrastructure as code (Terraform) for reproducible deployments

CI/CD pipeline with automated testing

Monitoring and alerting setup

Team training and knowledge transfer documentation

Runbooks for operations and troubleshooting

Business Impact

PORTFOLIO EXPANSION WITHOUT HEADCOUNT

The company can now expand geospatial risk analysis to 50+ countries annually without hiring additional analysts. Previously, this would have required 17× more staff—an impossible budget ask.

ANALYSTS FOCUS ON HIGH-VALUE WORK

Freed from repetitive data wrangling, analysts now spend their time on strategic analysis, model improvements, and insights generation—work that actually requires human expertise and judgment.

FASTER STAKEHOLDER RESPONSE

Business stakeholders receive results in 30 minutes instead of waiting weeks. This enables faster decision-making for underwriting, portfolio management, and market entry analysis.

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TECHNICAL DEEP-DIVE

Cloud-Native Geospatial Formats

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MIGRATION GUIDE

ArcPy to GeoPandas Migration

The complete translation guide for enterprise GIS teams.

STRATEGY

When to Migrate from Esri

Honest analysis of when migration makes sense (and when it doesn't).

Global Reinsurance Company:3-4 Weeks → 30 Minutes