---
title: "Cognizant says AI-driven FNOL cuts insurance claims cycles 20%-30%"
type: "News"
locale: "en"
url: "https://longbridge.com/en/news/294915429.md"
description: "Cognizant urges insurers to adopt multimodal, cloud-native AI platforms for First Notice of Loss (FNOL) and damage assessment. This shift aims to resolve fragmented intake and manual workflows that cause delays and high costs. The analysis suggests AI can reduce claims cycles by 20%-30% and cut cost per claim by 30%, while enhancing fraud detection and compliance. Additionally, sentiment analytics during FNOL can improve customer retention by helping agents address stress effectively."
datetime: "2026-08-05T05:42:10.000Z"
locales:
  - [zh-CN](https://longbridge.com/zh-CN/news/294915429.md)
  - [en](https://longbridge.com/en/news/294915429.md)
  - [zh-HK](https://longbridge.com/zh-HK/news/294915429.md)
generator: "portal-rs"
---

# Cognizant says AI-driven FNOL cuts insurance claims cycles 20%-30%

-   Cognizant published an industry analysis urging insurers to redesign first notice of loss and damage assessment using multimodal, cloud-native AI platforms. \* Report targets fragmented intake, manual workflows, inconsistent assessments, delayed decisions, which drive longer cycle times, higher costs, weaker customer trust. \* AI tools could cut claims cycles 20%-30% and reduce cost per claim 30%, while strengthening fraud detection and regulatory compliance. \* Sentiment and vocal analytics during FNOL could help agents respond to customer stress, positioning claims handling as a retention lever. Disclaimer: This news brief was created by Public Technologies (PUBT) using generative artificial intelligence. While PUBT strives to provide accurate and timely information, this AI-generated content is for informational purposes only and should not be interpreted as financial, investment, or legal advice. Cognizant Technology Solutions Corporation published the original content used to generate this news brief on August 05, 2026, and is solely responsible for the information contained therein. © Copyright 2026 - Public Technologies (PUBT) Original Document: here

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> **Disclaimer: This article is for reference only and does not constitute any investment advice.**