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Data integration and cleansing for better IFRS 9 models
Banking
Challenge
Financial institution with multiple sources of information and IFRS 9 requirements. The data was scattered, with inconsistencies and manual processes that affected traceability and reliability.
Solution
Integration and cleansing pipelines were implemented on Azure Data Lake, using Databricks for distributed processing. Data was standardized and validated, aligning business, risk, and analytics with regulatory requirements.
Impact
Improvement in data quality and traceability for IFRS 9. Reduction of manual processes and greater alignment between technical and business teams.
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