Financial institutions face a challenge with scattered loan data—inconsistent formats from various systems necessitate slow, manual transformation. This diverts staff attention, forcing them to spend more time on mandatory regulatory reporting than on leveraging those insights for monetary gain.
deeploans is an open-source framework that solves this problem. It enables any team to build scalable loan data pipelines, automate ETL processes, and unlock accurate loan portfolio analytics and reporting.
Designed for both data engineers and analytical teams, deeploans transforms raw loan data into standardized, analytics-ready formats. This creates a strong foundation for credit risk modeling tools, regulatory reporting, and advanced analytics across European banking systems.
Benefits For End Users
- 10X savings in reporting
Enable advanced analytics
Higher data quality
Save time
Remove data silos
Scalable infrastructure
Governable
No vendor lock-in
Case Study:
Better credit risk with deeploans
We used deeploans to fine-tune transformers models that beat standard logistic regression-based models.
Below is reported the average increase in accuracy for credit scoring, probability of default and loss given default metrics.
Are You Into Data Science?
The deeploans typically sits in the back of your application. The demo application below showcases how to leverage deeploans to connect your data products with your favourite business intelligence or machine learning environment.
Partnership Opportunity
What we are looking for:
- Funding for Development
- Design Partnership
- Marketing Partnership
What we provide in return:
- Implementation and Support
- Influence Over Features
- Free Usage
Explore and Contribute
