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Modeling Dollar Amounts in Regression Setting

After switching the role from the credit risk to the operational risk in 2015, I spent countless weekend hours in the Starbucks researching on how to model operational losses in the regression setting in light of the heightened scrutiny. 557 more words

Statistical Models

Additional Thoughts on Estimating LGD with Proportional Odds Model

In my previous post (https://statcompute.wordpress.com/2018/01/28/modeling-lgd-with-proportional-odds-model), I’ve discussed how to use Proportional Odds Models in the LGD model development. In particular, I specifically mentioned that we would estimate a sub-model, which can be Gamma or Simplex regression, to project the conditional mean for LGD values in the (0, 1) range. 760 more words

Statistical Models

Modeling LGD with Proportional Odds Model

The LGD model is an important component in the expected loss calculation. In https://statcompute.wordpress.com/2015/11/01/quasi-binomial-model-in-sas, I discussed how to model LGD with the quasi-binomial regression that is simple and makes no distributional assumption. 521 more words

Statistical Models

BoE Stress Testing to evaluate impact of Fintech Innovation on Banks

BoE stress testing framework has been a tool that the central bank and regulators have used to keep the banks honest since the recession. Stress testing driven by CCAR in the US, EBA and BoE in Europe and UK respectively is used to assess if banks have the required capital to withstand extreme market moves. 493 more words

Consumer Banking

Reflections from the CCAR Summit

This past October, three members of the CCRE team, Veronica Benavides, Lisa Gordon, and Erica Licht attended and presented at the 2017 Courageous Conversations About Race Summit… 825 more words

Race

Monotonic WoE Binning for LGD Models

While the monotonic binning algorithm has been widely used in scorecard and PD model (Probability of Default) developments, the similar idea can be generalized to LGD (Loss Given Default) models. 674 more words

Statistical Models

Model Non-Negative Numeric Outcomes with Zeros

As mentioned in the previous post (https://statcompute.wordpress.com/2017/06/29/model-operational-loss-directly-with-tweedie-glm/), we often need to model non-negative numeric outcomes with zeros in the operational loss model development. Tweedie GLM provides a convenient interface to model non-negative losses directly by assuming that aggregated losses are the Poisson sum of Gamma outcomes, which however might not be well supported empirically from the data generation standpoint. 769 more words

Statistical Models