<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Claims on Actuarial Ninja</title><link>https://www.actuarialninja.com/tags/claims/</link><description>Recent content in Claims on Actuarial Ninja</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sat, 20 Sep 2025 10:00:00 +0000</lastBuildDate><atom:link href="https://www.actuarialninja.com/tags/claims/index.xml" rel="self" type="application/rss+xml"/><item><title>Cleaning Messy Claims Data: An Actuarial Perspective</title><link>https://www.actuarialninja.com/tutorials/cleaning-messy-claims-data-an-actuarial-perspective/</link><pubDate>Sat, 20 Sep 2025 10:00:00 +0000</pubDate><guid>https://www.actuarialninja.com/tutorials/cleaning-messy-claims-data-an-actuarial-perspective/</guid><description>&lt;h1 id="cleaning-messy-claims-data-an-actuarial-perspective"&gt;
 Cleaning Messy Claims Data: An Actuarial Perspective
 
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&lt;p&gt;Claims data forms the backbone of actuarial analysis, pricing models, and reserving calculations in the insurance industry. However, raw claims data is often messy, incomplete, and fraught with inconsistencies that can significantly impact the accuracy of actuarial models and business decisions. This article explores the common challenges actuaries face when working with claims data and provides practical strategies for effective data cleaning from an actuarial perspective.&lt;/p&gt;</description></item></channel></rss>