Data can be ingested in any form, i.e. pdf, email, excel sheets, etc. This flexibility to converted unstructured data to structured format helps in analysis as well as storing data for future use.
The underwriting engine, analyses all the incoming applications and begins flags areas of concern based on historical information. Our significant domain knowledge helps provide supervised learning for machine to identify these hot spots.
Proposals meeting underwriting criteria are processed and the other ones are sent to underwriters for further investigation with reasons.
In a competitive industry, being able to process information quickly has significant advantages in generating additional revenue for clients. Also with ability to store data it helps in developing new products in future for clients.
With reduced time spent underwriting, there is more volume handled leading to increase in productivity, thereby reducing cost per policy.
With quick turnarounds and reliable pricing due to histrocial information, customer experience is substantially enhanced.