Mitigating Model Drift in Developing Economies Using Synthetic Data and Outliers

Ilyas Varshavskiy, Bonu Boboeva, Shuhrat Khalilbekov +4

Machine Learning models in finance are highly susceptible to model drift, where predictive performance declines as data distributions shift. This issue is especially acute in devel…