How do the data analytics and predictive models work?
The models consider over 200 variables. Many Clients tend to have a high number of favorable factors so we’re able to approve them quickly without the need for labs. Other Clients may have favorable factors but we need more information to approve them.
When this happens, the model tells us we need additional labs or information. The variables they consider are both medical and non-medical so while some Clients appear in perfect health, there may be non-medical factors that trigger the need for labs.
Some examples of variables that we look at are:
- family history
- medical history
- date arrived in Canada
- tobacco history