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	<title>Definition:Root-cause analysis - Revision history</title>
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&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;🔬 &amp;#039;&amp;#039;&amp;#039;Root-cause analysis&amp;#039;&amp;#039;&amp;#039; is a systematic investigative methodology used in the insurance industry to identify the fundamental underlying factors that lead to losses, operational failures, [[Definition:Claims | claims]] trends, or process breakdowns — going beyond surface-level symptoms to uncover the deeper systemic issues that, if addressed, would prevent recurrence. While the technique originated in engineering and quality management disciplines, it has become an essential tool within insurance operations, applied across contexts ranging from [[Definition:Claims management | claims investigation]] and [[Definition:Underwriting | underwriting]] portfolio review to [[Definition:Operational risk | operational risk]] management and [[Definition:Regulatory compliance | regulatory compliance]] remediation. An insurer conducting root-cause analysis on a surge in [[Definition:Water damage | water damage]] claims, for example, would look beyond the proximate cause of each loss to examine whether building code deficiencies, aging plumbing infrastructure, or shifts in construction practices are driving the trend.&lt;br /&gt;
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⚙️ Practitioners typically employ structured frameworks to carry out the analysis. Common techniques include the &amp;quot;Five Whys&amp;quot; method — iteratively asking why a problem occurred until the foundational cause surfaces — as well as fishbone (Ishikawa) diagrams that map contributing factors across categories such as people, processes, technology, and external environment. In a claims context, root-cause analysis might reveal that a pattern of delayed [[Definition:Subrogation | subrogation]] recoveries stems not from individual adjuster error but from a systemic gap in the [[Definition:Claims management system | claims management system]] that fails to flag recovery-eligible files at the right stage. In [[Definition:Underwriting | underwriting]], the technique can expose why a particular [[Definition:Line of business | line of business]] is consistently producing [[Definition:Loss ratio | loss ratios]] above plan — perhaps because [[Definition:Risk selection | risk selection]] criteria have not kept pace with emerging hazards, or because [[Definition:Delegated underwriting authority (DUA) | delegated authority]] partners are deviating from agreed guidelines. Insurers increasingly embed root-cause analysis into their [[Definition:Enterprise risk management (ERM) | enterprise risk management]] frameworks, using the findings to inform corrective action plans, adjust pricing models, and refine [[Definition:Risk appetite | risk appetite]] statements.&lt;br /&gt;
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💡 The discipline&amp;#039;s real value lies in transforming reactive problem-solving into proactive risk prevention. Regulators across multiple jurisdictions — including the [[Definition:Financial Conduct Authority (FCA) | FCA]] in the UK, [[Definition:European Insurance and Occupational Pensions Authority (EIOPA) | EIOPA]], and various U.S. state insurance departments — expect insurers to demonstrate that they investigate systemic issues rigorously rather than treating each incident in isolation. When a pattern of customer complaints or claims disputes emerges, a credible root-cause analysis showing corrective measures taken can be the difference between a routine supervisory conversation and a formal enforcement action. Beyond compliance, insurers that build a culture of root-cause analysis into their operations tend to achieve more sustainable [[Definition:Underwriting profit | underwriting profitability]] and operational efficiency, because they address the structural drivers of loss and inefficiency rather than cycling through the same problems repeatedly. The technique also supports continuous improvement in [[Definition:Insurtech | insurtech]] environments, where rapid product iteration demands quick diagnosis and correction of flaws in algorithms, customer journeys, or automated decision processes.&lt;br /&gt;
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&amp;#039;&amp;#039;&amp;#039;Related concepts:&amp;#039;&amp;#039;&amp;#039;&lt;br /&gt;
{{Div col|colwidth=20em}}&lt;br /&gt;
* [[Definition:Enterprise risk management (ERM)]]&lt;br /&gt;
* [[Definition:Operational risk]]&lt;br /&gt;
* [[Definition:Claims management]]&lt;br /&gt;
* [[Definition:Loss ratio]]&lt;br /&gt;
* [[Definition:Regulatory compliance]]&lt;br /&gt;
* [[Definition:Quality assurance]]&lt;br /&gt;
{{Div col end}}&lt;/div&gt;</summary>
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