Artificial Intelligence
Mar 08, 2021

Five reasons why automated data extraction in insurance underwriting is a big deal

A common problem statement for many commercial lines carriers is: how can they respond more quickly and efficiently to incoming requests from agents and brokers for quote submissions, endorsements, and renewals? The insurance industry is plagued with the inability to meet broker and buyer expectations because of heavy volumes, manual handling, multiple complex documents, and fragmented and legacy systems. For many carriers, up to 50% of incoming email quote submissions remain unopened. A far-from-ideal customer experience.

But there is a solution. The availability of artificial intelligence-based tools that can extract and digitize both structured and unstructured data from multiple sources (such as emails, Word documents, Excel spreadsheets, and PDFs) has changed everything. Like most innovations, change comes slowly at first, but insurers are really starting to embrace automated data extraction and the benefits it brings.

There are multiple ways to make the business case for this investment. For me, No. 1 may be obvious, but the other four are much more interesting.

  1. Efficiency and integration. Automating manual processes deliver efficiencies that lower operating costs. What may have taken 10 people to handle the intake process for a given number of quotes may only require 3 people with automated data extraction support. And extracting all the data elements from incoming documents at the same time creates further downstream efficiencies. The information needed for various underwriting support systems can often be extracted without the need for further manual handling. Note: there will always be a minimum level of human intervention required to quickly handle exceptions that the extraction tool can't reconcile. These efficiencies from reducing labor costs typically dominate the business case and the decision to automate
  2. Speed and accuracy. What if the time to respond to a quote or renewal request could be reduced by several days? And what if each quote had fewer errors requiring rework? Faster (and more accurate) quotes increase the likelihood that it will convert to a policy. Speed and accuracy deliver a competitive advantage that leads to growth through a bigger slice of the market and increased customer retention
  3. Risk selection. Automatically digitizing incoming information unlocks the ability for real-time triage. If an insurer is currently processing only 50% of incoming quote requests, profitable business is probably left sitting in the archived (and unopened) mailbox. Automated data extraction will enable triage and decision tools to evaluate or score 100% of quotes to make sure the underwriters are prioritizing and optimizing all opportunities. Enabling the underwriters to prioritize risks that are most likely to convert and most likely to produce the highest lifetime value is critical for success
  4. Analytics. Data scientists, analysts, actuaries, and product managers all depend on accurate data. Digitizing via automated extraction provides a rich set of information that can be analyzed in multiple downstream applications. On top of this, automated data extraction will unlock the data from all incoming submissions – not just those quoted on. From a product management standpoint, the data from all these submissions will reveal opportunities for future marketing, pricing, and product development opportunities
  5. Growth. Automated data extraction for quotes, endorsements, and renewals is essentially a growth story. Faster, more accurate quotes and renewals support growth. More efficient operations funds innovation and growth. Better risk selection and triage drives sharper risk selection and growth. Richer datasets for analytics help identify future growth opportunities

About the author

John  Cantwell

John Cantwell

Global Service Line Leader, Insurance Underwriting

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