Project Overview

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.


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