Tracking policies nearing expiry across multiple business lines is critical for:
- Ensuring timely renewals
- Avoiding revenue leakage
- Maintaining compliance and client retention
However, challenges included:
- Multiple fragmented data sources (policy systems, underwriting platforms)
- Complex renewal logic (latest transaction, cancellations, endorsements)
- Manual report preparation across departments
- Inconsistent formatting and delayed delivery of renewal extracts
This resulted in operational inefficiencies, delayed insights, and increased risk of missed renewals.
Designed and implemented an end-to-end automated renewal reporting pipeline that:
- Identifies policies expiring within a defined time window (e.g., 90β120 days)
- Consolidates data across multiple underwriting systems
- Applies complex business rules to determine valid renewal candidates
- Automates report generation, formatting, and delivery
The solution integrates SQL-based data engineering + Power Automate orchestration + Excel automation to deliver production-ready renewal reports.
- Multiple Policy Systems (Underwriting Platforms) β
- SQL Data Extraction (Stored Procedures) β
- Data Transformation (CTEs + Joins + Business Logic) β
- Staging Tables (Centralized Dataset) β
- Scheduled SQL Jobs (Automated Refresh) β
- Power Automate Flows (Orchestration Layer) β
- Excel Generation & Formatting (Office Scripts) β
- Automated Distribution (Email & SharePoint)
Built modular stored procedures to:
- Extract policy data across systems
- Filter renewal windows dynamically
- Apply transaction-level logic (new business, renewal, cancellation, endorsement)
- Structure output for downstream reporting
Common Table Expressions (CTEs) for:
- Premium aggregation
- Address and enrichment joins
- Policy-level transformations
Complex joins across:
- Policy data
- Client/address datasets
- Broker and salesperson mappings
- External enrichment datasets
Business logic handling:
- Latest transaction selection using effective dates
- Conditional premium calculations
- Multi-source data alignment
SQL jobs configured to:
- Execute stored procedures at defined intervals
- Refresh renewal datasets automatically
- Ensure data availability before report generation
π This ensures zero manual intervention in data preparation
- Scheduled flows (time-based triggers across regions)
- Dataset queries to fetch processed renewal data
- Loop-based processing for large datasets
- Conditional logic for handling empty or partial datasets
- Trigger β Query dataset β Process rows β Generate file
- Controlled execution for multiple business lines (parallel workflows)
- Data chunking using loop variables to handle volume constraints
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Automated Excel file creation
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Dynamic CSV/table generation
Office Scripts used for:
- Formatting data output
- Structuring final extracts
- Standardizing presentation across teams
Multi-report generation per business unit
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β Dynamic Renewal Window Logic Automatically identifies policies within upcoming expiry ranges
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β Latest Transaction Handling Ensures the most relevant policy record is selected
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β Multi-Source Data Integration Combines data from underwriting, policy, and enrichment systems
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β Scalable Data Processing Loop-based chunking prevents failures with large datasets
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β End-to-End Automation Eliminates manual intervention from extraction β delivery
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β Improved Renewal Visibility Early identification of expiring policies across portfolios
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β Revenue Protection Reduced risk of missed renewals and contract lapses
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β Operational Efficiency Fully automated workflow replaces manual reporting efforts
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β Standardization of Reporting Consistent structure across multiple business lines
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β Faster Decision-Making Timely availability of renewal data for underwriting teams
- SQL Server β Data extraction & transformation
- T-SQL (CTEs, Joins, Stored Procedures) β Business logic implementation
- Power Automate β Workflow orchestration
- Office Scripts β Excel transformation & formatting
- Excel / CSV Outputs β Final reporting artefacts
π Data Privacy & Confidentiality This repository contains a sanitized version of the implementation: No client-specific identifiers or system names included Business rules generalized for demonstration purposes Structure preserved while ensuring confidentiality
- End-to-end automation pipeline (data β report β delivery)
- Strong SQL + workflow orchestration integration
- Real-world insurance analytics use case
- Focus on scalability, accuracy, and operational efficiency
This project demonstrates the ability to design production-grade data pipelines that directly support business-critical workflows, combining data engineering, automation, and analytics into a single scalable solution.