ML Works helped a leading insurance company
revamp its screening process
As a strategy leader for a leading insurance company in the US, George wanted to ensure that the screening process for insurance applicants was as transparent as possible. To meet the regulatory and compliance needs, he wanted the ML models to be bias-free.
ML Works helped create a smart applicant screening process
Machine learning models, though data-intensive, are highly-regulated in the insurance sector. ML Works helped George follow the protocols of the industry with its three dynamic modules and improve his firm’s insurance screening process.
- Drift Detection: As the applicants’ persona changes, the pre-trained models result in irregular predictions. ML Works ensured proactive identification of data drift and stopped the problem at the source.
- XAI: ML Works explained the risk/no risk reasons for each applicant, which allowed George to make strategic decisions.
- Bias Detection: Algorithmic bias usually mimics social bias. However, ML Works ensured models were bias-free from direct bias (brought in by demography) and indirect bias (due to correlated variables), which helped George confirm that the models pass the compliance test with flying colors.
- Higher visibility in the output.
- Accurate and current models in production.
- Compliant unbiased models.
- Transparent insurance screening process.