https://www.insurerbrain.com/w/index.php?action=history&feed=atom&title=Definition%3AStructured_dataDefinition:Structured data - Revision history2026-06-13T19:26:41ZRevision history for this page on the wikiMediaWiki 1.43.8https://www.insurerbrain.com/w/index.php?title=Definition:Structured_data&diff=8291&oldid=prevPlumBot: Bot: Creating new article from JSON2026-03-10T13:56:14Z<p>Bot: Creating new article from JSON</p>
<p><b>New page</b></p><div>📊 '''Structured data''' in insurance refers to information organized in a predefined, consistent format — typically rows and columns within databases or spreadsheets — that can be readily queried, analyzed, and processed by [[Definition:Policy administration system | policy administration systems]], [[Definition:Claims management system | claims platforms]], and [[Definition:Actuarial analysis | actuarial tools]]. Examples include [[Definition:Policyholder | policyholder]] names and addresses, [[Definition:Premium | premium]] amounts, [[Definition:Claims | claim]] numbers, [[Definition:Coverage | coverage]] limits, [[Definition:Effective date | effective dates]], and [[Definition:Loss code | loss codes]]. This type of data contrasts with [[Definition:Unstructured data | unstructured data]] — such as handwritten adjuster notes, scanned documents, photographs, or emails — which lacks a fixed schema and requires additional processing before it can be used analytically.<br />
<br />
🔧 Insurance operations generate enormous volumes of structured data at every stage of the [[Definition:Insurance value chain | value chain]]. When a [[Definition:Broker | broker]] submits a [[Definition:Submission | submission]], when an [[Definition:Underwriting | underwriter]] binds a policy, when a [[Definition:Claims adjuster | claims adjuster]] records a [[Definition:First notice of loss (FNOL) | first notice of loss]], and when a [[Definition:Reinsurer | reinsurer]] receives a [[Definition:Bordereau | bordereau]] — each transaction produces fields of structured information that flow into an insurer's core systems. The reliability of downstream activities like [[Definition:Experience rating | experience rating]], [[Definition:Reserving | reserving]], [[Definition:Regulatory reporting | regulatory reporting]], and [[Definition:Predictive analytics | predictive modeling]] depends directly on the quality, consistency, and completeness of this structured data. Poor data governance — duplicate records, inconsistent coding, missing fields — cascades through the organization, degrading everything from [[Definition:Pricing | pricing]] accuracy to [[Definition:Financial statement | financial statements]].<br />
<br />
💡 The insurance industry's push toward [[Definition:Digital transformation | digital transformation]] and [[Definition:Artificial intelligence (AI) | artificial intelligence]] has elevated structured data from an IT concern to a strategic asset. [[Definition:Insurtech | Insurtech]] companies often gain their competitive edge precisely because they are built on clean, well-structured data architectures from day one, avoiding the legacy data quality problems that plague established carriers. Regulators, too, are demanding more granular and standardized data submissions — as seen in initiatives like [[Definition:Lloyd's | Lloyd's]] market modernization and the expansion of [[Definition:ACORD | ACORD]] data standards. Insurers that invest in robust [[Definition:Data governance | data governance]] frameworks and structured data infrastructure position themselves to extract actionable insights, automate workflows, and respond faster to market opportunities than competitors still wrestling with fragmented spreadsheets and siloed systems.<br />
<br />
'''Related concepts'''<br />
{{Div col|colwidth=20em}}<br />
* [[Definition:Unstructured data]]<br />
* [[Definition:Data governance]]<br />
* [[Definition:Bordereau]]<br />
* [[Definition:ACORD]]<br />
* [[Definition:Predictive analytics]]<br />
* [[Definition:Data lake]]<br />
{{Div col end}}</div>PlumBot