Presentation Type
Event
Student
No
Track
Finance/Insurance Application
Abstract
FICO® Scores assess default likelihood under “normal” conditions. Additional risk emanates from economic variability and manifests itself in changes to the score distribution as well as changes to the Odds-to-Score relationship. In this session we will examine credit bureau data from the Great Recession in the United States as compared to a stable economic period. We’ll share a framework that provides new and actionable insights into consumers’ sensitivities to such economic fluctuations such as:
-
Application of counterfactual analysis, machine learning, and scorecards, to rank-order consumers’ sensitivities
-
Consumer segmentation by economic sensitivities
-
Sensitivity profiling reveals interesting differences between the most and the least sensitive consumers
-
How you can put “economic shock absorbers” under your lending strategies
-
Improving the accuracy of portfolio simulations under varying economic conditions
Start Date
2-5-2019 10:00 AM
End Date
2-5-2019 10:50 AM
FICO® Scores Through the Economic Cycle and Understanding Consumer Sensitivities to Economic Fluctuations
Dakota Room 250 A/C
FICO® Scores assess default likelihood under “normal” conditions. Additional risk emanates from economic variability and manifests itself in changes to the score distribution as well as changes to the Odds-to-Score relationship. In this session we will examine credit bureau data from the Great Recession in the United States as compared to a stable economic period. We’ll share a framework that provides new and actionable insights into consumers’ sensitivities to such economic fluctuations such as:
-
Application of counterfactual analysis, machine learning, and scorecards, to rank-order consumers’ sensitivities
-
Consumer segmentation by economic sensitivities
-
Sensitivity profiling reveals interesting differences between the most and the least sensitive consumers
-
How you can put “economic shock absorbers” under your lending strategies
-
Improving the accuracy of portfolio simulations under varying economic conditions