Client needed an PoC model built on the available data to model probability of a breach for the specific company. Deliverables:
- Predictive models to estimate probability of data breach, possible amount of losses
- Implied risk densities for the companies in given subgroup
- Cramer-Lundberg actuarial model to account for probability of default for the actuarial company given its initial funding and hedge portfolio of clients.
Technology stack:
R, h2o, randomforest, actuarial, libraries for estimating implied distributions, xgBoost, regressions.