Low Default Portfolios (LDP)
Banks currently face significant challenges to build internal Probability of Default (PD) models for low default portfolios such as Large Corporates and Global Banks. In particular, scarcity of internal default data for these portfolios typically leads to inaccurate PD models with low predictive power.
Hence, banks often resort to building PD models based on external datasets. For example, they may procure third-party default data from vendors and use external ratings (provided by credit rating agencies) to build their internal PD models. Such methodologies often result in conservative PD estimates, which in turn lead to high regulatory capital charges.
RISE’s LDP solution addresses this industry wide problem by pooling internal default data across banks. Our solution therefore facilitates the development of more accurate and robust PD models for low default portfolios such as Large Corporates and Banks.
- Rich Data Pool
- Suite of Modelling Methodologies
- Continual Expansion and Update of Data
- Automated Model Documentation
- Centralised Modelling Infrastructure
- Ongoing Model Monitoring
Avoid Capital Add-Ons
- Optimised regulatory capital by using better PD models
- Reduced capital overlays and buffers
- Improved transaction pricing
- Better risk-return trade-offs
- Efficiencies by avoiding potential duplication
- Accelerated model redevelopment