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Data integration and cleansing for better IFRS 9 models
Banking
Business
Corporate
+ 2.000 employees
Type of solution
IFRS 9 data consolidation and cleaning
+ 70%
of usable data for advanced IFRS 9 models
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.
Technologies used
Azure Data Lake · Databricks · SQL · Python
Impact
Improvement in data quality and traceability for IFRS 9. Reduction of manual processes and greater alignment between technical and business teams.
Related services
The capabilities that made this project possible.
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