Published on Aug 2, 2019
Updated on Oct 16, 2019
For any operational effort across large organizations, a significant amount of time and resources are spent manually inputting data into downstream systems. These processes more specifically affect insurance practices that are deeply reliant on back-office processes. The bulk of the insurance workforce is condensed into operations and support functions (e.g. policy issuance and servicing). Here, data is typically unstructured and locked away in heaps of paper-based documents, emails, scanned images, excel worksheets, pdf, and word reports.
Typically in insurance, at least 90% of unstructured documents are manually processed, while an ‘Insurance Policy Administration System’ is on average between 15–20 years old — forcing them at times to lag behind their financial services peers.
To make the most out of the massive quanta of inbound data stored in siloed systems, firms have recently begun to take a serious look at streamlining data migration using AI-based tools. The burgeoning reality is that