The Challenge
Lack of a unified view of Loan and Mortgage data across borrower, property.
Data received from multiple agencies via various channels and of different formats.
Manual processing of data. Time to insights is too high.
The current state impedes efficient operations and due diligence processes.
What did Technologia do
Deployed end-to-end data management architecture using Azure Cloud Platform.
Developed complex data processing pipelines using Azure Data Bricks and Azure Data Factory to collate multi-source data.
Developed a Data Lakehouse architecture using Azure Data Bricks.
Applications built to support and ease operational and approval workflow using Power Apps.
Dashboards built on Power BI to provide insights.
ML Models built using Azure ML studio to predict the risk of mortgages.

The Results
- Better prediction of Mortgage risk resulted in minimizing losses to the extent of 5-10%.
- Better data management and automation resulted in a huge reduction of manual efforts and increased efficiency of due-diligence process by 10%.