Automated Data Modelling and Reporting

Challenge: A life insurance client relied on a monolithic 120-sheet Excel model for core calculations. Because the data lacked a unified structure, audits required manual lookups across dozens of variations, turning monthly reporting into a high-friction bottleneck.

Action:I decoupled the logic from the presentation by redesigning the model’s data architecture. Using the Pandas framework, I engineered an automated ETL pipeline that normalized the workbook’s disparate data points into a structured reporting stream.

Result:The transition from manual lookups to an automated architecture reduced reporting time and provided a "Source of Truth" for audits. The client can now address complex customer reporting needs in minutes rather than days.

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