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📋 '''Quality management''' in the insurance industry refers to the systematic framework of policies, processes, and controls that insurers, [[Definition:Managing general agent (MGA) | MGAs]], and other market participants use to ensure that underwriting, claims handling, policy administration, and customer service consistently meet defined standards. Unlike manufacturing, where quality management focuses on physical product defects, insurance quality management addresses intangible outputs — the accuracy of a [[Definition:Policy | policy]] wording, the consistency of [[Definition:Underwriting | underwriting]] decisions, the fairness of [[Definition:Claims adjustment | claims settlements]], and the reliability of data flowing through operational systems. Regulatory frameworks in many jurisdictions now explicitly require quality management disciplines: the UK's Financial Conduct Authority expects firms to demonstrate fair outcomes for consumers, while [[Definition:Solvency II | Solvency II]] mandates robust internal controls and governance under its Pillar II requirements.

⚙️ In practice, quality management operates through a combination of documented procedures, performance metrics, audit programs, and feedback loops. A [[Definition:Delegated underwriting authority (DUA) | delegated authority]] arrangement, for instance, typically includes quality assurance provisions requiring the [[Definition:Coverholder | coverholder]] to submit to periodic audits of its underwriting files, ensuring adherence to the [[Definition:Binding authority agreement | binding authority agreement]]. [[Definition:Lloyd's of London | Lloyd's]] has formalized this through its own coverholder oversight framework, mandating that managing agents conduct regular reviews of delegated portfolios. In claims operations, quality management often involves file reviews scored against criteria such as reserving accuracy, communication timeliness, and settlement appropriateness. Increasingly, [[Definition:Insurtech | insurtech]] tools are being deployed to automate quality checks — using [[Definition:Artificial intelligence (AI) | artificial intelligence]] to flag outlier claims decisions or [[Definition:Natural language processing (NLP) | natural language processing]] to verify policy document accuracy at scale.

🔍 Robust quality management protects insurers from a cascade of downstream problems: regulatory sanctions, [[Definition:Errors and omissions (E&O) insurance | errors and omissions]] liability, customer complaints, and portfolio deterioration that only reveals itself years later when [[Definition:Loss reserve | reserves]] prove inadequate. For organizations operating across borders, maintaining consistent quality standards is especially challenging, as service expectations and regulatory requirements differ between markets such as the United States, the EU, and Asia-Pacific jurisdictions like Singapore and Japan. Carriers that embed quality management deeply into their culture — rather than treating it as a compliance checkbox — tend to achieve more predictable [[Definition:Loss ratio (L/R) | loss ratios]], stronger relationships with [[Definition:Reinsurance | reinsurers]], and better outcomes in regulatory examinations.

'''Related concepts:'''
{{Div col|colwidth=20em}}
* [[Definition:Internal controls]]
* [[Definition:Delegated underwriting authority (DUA)]]
* [[Definition:Coverholder]]
* [[Definition:Regulatory compliance]]
* [[Definition:Claims management]]
* [[Definition:Audit]]
{{Div col end}}

Definition:Quality management - Revision history

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