Loading repository data…
Loading repository data…
open-risk / repository
openLGD is a Python powered library for the statistical estimation of Credit Risk Loss Given Default models. It can be used both as standalone library and in a federated learning context where data remain in distinct (separate) servers
A transparent discovery signal based on current public GitHub metadata.
This score does not audit code, security, maintainers, documentation quality, or suitability. Verify the repository and its current documentation before adoption.
openLGD is a Python powered library for the statistical estimation of Credit Risk Loss (Also loss-given-default or LGD) models.
openLGD can be used both as standalone library or in a federated analysis context where data remain in distinct (separate) servers
NB: This is an early alpha release. openLGD is still in active development
openLGD aims to support the development of both expert based and statistical LGD Models
In standalone mode openLGD emulates a classic use case where, e.g., a financial institution or other credit provider aims to develop a risk quantification system on the basis of data it has in its possession. Use cases for the standalone mode are both as intended (standalone) LGD model framework system and as a validation framework for federated applications.
The standalone mode is illustrated via the script standalone_run.py
The federated mode essentially facilitates the development of a generic (pooled) LGD model that applies to a wide population (which is assumed homogeneous)
Going forward we'll use fabric and yaml to ease deployment. Check Fabfile for preliminary functionality
The complete dependency list in the requirements file
The demo Model Servers are python/flask based servers
The general structure of the simplified API is