Unlock Unprecedented Policy Delivery Speeds

Automation and AI-driven data extraction improve the speed of new insurance request issuance for a large P&C insurer

Case Summary

The client, a leading commercial property and casualty insurer, wanted to reduce the manual intervention needed to manage extensive documentation requirements. SLK automated the data extraction in unstructured documents and strategically included humans in the process pathway to improve accuracy. This led to a faster turnaround time, reduced person-hours, and improved efficiency.

The Challenge

The client was faced with a new process for handling commercial and personal insurance applications that required extensive documentation. On average, about 40 pages per policy required human intervention. Such a high volume of paperwork meant a high lead time for policy issuance spanning multiple days to weeks.
This led to long client wait times and impacted net promoter scores. As one of the world’s largest insurers, the client’s priority was to ensure 100% customer satisfaction with top-quality products and

The insurer wanted to speed up the policy issuance by utilizing technology to streamline and standardize the processes and reduce human effort and time consumption. The conventional go-to-technologies such as OCR and RPA couldn’t be used as they suffer in accuracy while extracting from unstructured documents.
Moreover, a strategic inclusion of human intervention was indispensable to the process. They were looking for a partner that could provide end-to-end support on automation to drive efficiencies.

The Solution

The client decided to partner with SLK to find a solution to this problem. The SLK team evaluated the problem statement and created a strategy using the power of machine learning and automation for resolution. We deployed novel extraction techniques using NLP/OCR/computer-based vision-based geometry and synonyms from structured and unstructured application forms, including email submissions and attachments. In addition, an artificial intelligence-based classification harmonized with industry-standard taxonomy was implemented for document and version changes. Lastly, the Human in The Loop capability was used for exception processing and approval.

Business Impact

> 90%



Improvement in efficiency


Submissions automated

15 Min

Processing time to extract 145 parameters

SLK’s Solution Delivered Quick Results:

SLK’s AI-based automation made data extraction effortless for the client and improved efficiency.
  • Quick turnaround times by streamlining, standardizing, and automating resulted in reduced client wait times
  • End-to-end automation translated to operational efficiencies and improved conversion ratio and net
    promoter score
  • A high-end AI-driven solution reduced the need for human intervention and rationalized the new business
    request intake