https://www.insurerbrain.com/w/index.php?action=history&feed=atom&title=Definition%3AClaims_automationDefinition:Claims automation - Revision history2026-06-13T15:50:30ZRevision history for this page on the wikiMediaWiki 1.43.8https://www.insurerbrain.com/w/index.php?title=Definition:Claims_automation&diff=6586&oldid=prevPlumBot: Bot: Creating new article from JSON2026-03-09T16:21:53Z<p>Bot: Creating new article from JSON</p>
<p><b>New page</b></p><div>🤖 '''Claims automation''' is the use of technology — including [[Definition:Artificial intelligence (AI) | artificial intelligence]], [[Definition:Machine learning (ML) | machine learning]], [[Definition:Robotic process automation (RPA) | robotic process automation]], and rules-based engines — to handle part or all of the [[Definition:Claims management | claims management]] lifecycle without manual intervention. Tasks that traditionally required human [[Definition:Claims adjuster | adjusters]] or administrative staff, such as [[Definition:First notice of loss (FNOL) | first notice of loss]] intake, document verification, [[Definition:Damage assessment | damage assessment]], and [[Definition:Claims settlement | settlement]] calculations, can now be executed in seconds by automated systems. The approach has become a cornerstone of [[Definition:Insurtech | insurtech]] innovation, reshaping how [[Definition:Insurance carrier | carriers]] and [[Definition:Third-party administrator (TPA) | third-party administrators]] deliver service to [[Definition:Policyholder | policyholders]].<br />
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🔄 At its core, an automated claims pipeline ingests structured and unstructured data — photos, repair estimates, medical records, [[Definition:Policy | policy]] documents — and routes each [[Definition:Claim | claim]] through a decision framework. Straightforward claims that meet predefined criteria can be approved and paid through [[Definition:Straight-through processing (STP) | straight-through processing]], while more complex or high-value cases are flagged for human review. [[Definition:Natural language processing (NLP) | Natural language processing]] helps extract relevant details from correspondence, and [[Definition:Predictive analytics | predictive analytics]] models score claims for potential [[Definition:Fraud | fraud]], enabling the system to triage work intelligently rather than treating every submission identically.<br />
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📈 The payoff extends well beyond speed. Automated workflows dramatically reduce [[Definition:Claims leakage | claims leakage]] — the hidden costs from overpayments, duplicated effort, and processing errors — while delivering a faster, more transparent experience that strengthens [[Definition:Customer retention | customer retention]]. Insurers that invest in claims automation also gain richer data, which feeds back into [[Definition:Underwriting | underwriting]] and [[Definition:Pricing model | pricing models]], creating a virtuous cycle of operational improvement. In a market where policyholders increasingly expect real-time digital interactions, the ability to settle a claim in minutes rather than weeks is rapidly shifting from competitive advantage to baseline expectation.<br />
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'''Related concepts'''<br />
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* [[Definition:Straight-through processing (STP)]]<br />
* [[Definition:Robotic process automation (RPA)]]<br />
* [[Definition:Claims management system]]<br />
* [[Definition:Fraud detection]]<br />
* [[Definition:Insurtech]]<br />
* [[Definition:First notice of loss (FNOL)]]<br />
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