In finance and insurance today there is a huge amount of time-series data that one needs to use in order to stay competitive. It is the perfect match with our focus on uncertainty estimation, as we can extract a lot of learnings from very small amounts of data while at the same time scale to very large datasets.
The applications are almost endless
- Predict the probability of something happening at a point in time
- Decompose the drivers of a KPI
- Understand the impact of the drivers, and the uncertainty surrounding their impact.