Federal Flood Insurance Provider Reduced Reporting Costs by 25%

Our client is one of the largest providers of federal flood insurance policies under the National Flood Insurance Program (NFIP).

They manage complex risk data across thousands of geographies, working with multiple underwriting companies (referred to as “slips”) to assess, price, and issue insurance policies.

The data volume and granularity from national-level metrics to zip-code-level insights made analytics a critical part of their operations.

The client’s goal was to implement a robust, cloud-based analytics platform that could:

• Centralize and populate policy data into a scalable data warehouse.

• Deliver drillable map-based dashboards for underwriting and risk analysis.

• Eliminate reliance on manual consulting reports for decision-making.

They needed a solution that provided real-time insights across multiple levels: total, company, state, and zip code.

Despite having the data, the client lacked the internal DevOps bandwidth to build an end-to-end analytics system. The core challenges were:

Their existing systems weren’t optimized for Azure, limiting scalability and integration.

Policy data came in raw text files and required significant manual effort to process and analyze.

They needed interactive dashboards that could break down premium and policy data by geography and company, which was not feasible with their current setup.

Reporting had to be outsourced, leading to delays and high costs for every update or insight request.

Muoro deployed remote DevOps engineers to deliver a scalable, cost-effective solution using modern cloud and BI tools.

We worked closely with the client's internal stakeholders to define:

• The data transformation goals

• The drill-down logic and dashboard interactivity needs

• Integration constraints across existing systems

Our DevOps team built the full pipeline from ingestion to visualization:

• ETL pipeline using Azure Data Factory to convert raw text files into structured formats

• Data stored in Azure SQL Data Warehouse for high-performance querying

• Dashboards built using Power BI, showing risk maps, policy counts, and premiums with full drill-down functionality

• Map visualizations shaded by zip code and company-specific overlays

Muoro completed the entire lifecycle—from planning to deployment—in just four months. The client was given full access, training, and documentation to scale the solution further internally.

Here’s the complete tech stack that powered the transformation:

1. Azure Data Factory – Automated the ETL workflow from raw files to database ingestion

2. Azure Blob Storage – Temporary storage for incoming data before processing

3. Azure SQL Data Warehouse – Centralized storage for structured policy, premium, and risk data

Power BI – Built interactive, role-specific dashboards with advanced drill-down and heatmap features

We delivered what we promised.

Enabled map-based dashboards that let users filter by company, region, or zip code, improving clarity and speed in decision-making.

With real-time reporting, underwriters and analysts reduced evaluation time significantly.

Eliminated recurring consultancy fees by internalizing analytics and reporting workflows.

From ingestion pipelines to final dashboards, Muoro’s remote DevOps engineers deliver everything within a tight timeline.

The client gained:

• End-to-end reporting system powered by scalable cloud infrastructure

• Reduced reliance on manual processes and third-party vendors

• Full control over analytics with drill-down insights at their fingertips

If you're still doing manual ETL or waiting on slow report cycles, Muoro can help.

We provide dedicated DevOps engineers and data experts who build scalable pipelines and dashboards aligned with your goals.

Let’s talk.