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保險人工智能 (AI) 市場 - 預測 2023-2028
市場調查報告書
商品編碼
1279625

保險人工智能 (AI) 市場 - 預測 2023-2028

Artificial Intelligence (AI) for Insurance Market - Forecasts from 2023 to 2028
出版日期: | 出版商: Knowledge Sourcing Intelligence | 英文 150 Pages | 商品交期: 最快1-2個工作天內

價格
簡介目錄

國防領域的人工智能（AI）市場：預計該市場將從2021年的12.09億美元市場規模以33.05%的複合年增長率增長，到2028年達到89.25億美元。 人工智能 (AI) 也正在滲透到保險行業，保險公司利用該技術來改善其業務的許多方面。 人工智能正在用於自動化承保流程，使保險公司能夠就與特定保單相關的風險做出更明智的決策，並識別和防止欺詐性索賠。 人工智能算法可以分析來自各種來源的數據，包括社交媒體、財務報表和醫療記錄，以確定與保單相關的風險。 此外，還可以分析大量數據，例如索賠歷史記錄和保單持有人行為，以檢測表明欺詐的模式。

聊天機器人和虛擬代理在保險行業中越來越受歡迎，因為它們為客戶提供了一種便捷且易於訪問的方式來購買和管理保單。 例如，我們可以為您提供有關保險單、索賠和付款的信息，並實時回答常見問題。 區塊鏈技術為記錄交易提供了安全、透明的帳本，也是該領域的熱門話題。 該技術可以幫助保險公司提高數據隱私和安□□全性，降低與傳統管理流程相關的成本，並提高透明度和效率。

市場促進因素

遠程資訊處理和物聯網設備的增長

遠程資訊處理和物聯網 (IoT) 設備的興起正在產生大量數據，可用於增強承保和定價。 人工智能算法可以分析這些數據，以確定與保險單相關的風險並提供更準確的定價。 保險公司現在可以收集有關保單持有人的大量數據，並用它來確定保單的個性化定價。 此外，它還可用於檢測保險行業的欺詐行為。 例如，來自遠程資訊處理設備的數據可用於確定保單持有人的駕駛習慣是否與保單應用程序上提供的資訊匹配。 人工智能算法可以分析這些數據並檢測表明欺詐的模式。

偏好個性化保險

隨著數位技術和資訊獲取的興起，消費者越來越意識到個性化保險的好處。 這包括定制保險建議和定制保險，以更好地滿足您的特定需求和要求。 技術的進步使得以更實惠的價格提供更個性化的保險成為可能。 人工智能算法現在可以分析大量數據，使保險公司能夠提供更適合每個客戶的個人需求和預算的保險。 例如，與具有較高風險駕駛行為的客戶相比，始終以安全速度駕駛並避免突然制動的客戶可以獲得更低的保費。 Metromile 是一家消費者汽車保險公司，利用人工智能和遠程資訊處理技術來追蹤駕駛行為並提供個性化保險。 該公司的應用程序追蹤裡程和駕駛行為，並使用這些資訊提供實時更新的個性化保險報價。

限制

保險行業監管嚴格，利用人工智能技術需要遵守各種法律法規。 遵守這些法規對保險公司來說可能是一項挑戰，因為它們可能需要大量資源和投資。 保險業在採用新技術方面進展緩慢，一些公司可能會抵制變革。 由於擔心所涉及的成本和風險，一些傳統保險公司可能不願意採用人工智能技術。

預計北美在預測期內將佔據重要份額。

北美以其高度採用技術而聞名，保險業也不例外。 該地區的許多保險公司都是人工智能技術的早期採用者，以改善運營並保持競爭力。 它擁有發達的基礎設施，包括高速互聯網、先進的數據中心和強大的IT產業。 該基礎設施為開發和部署提供了理想的環境。 該地區強大的經濟實力使得保險公司能夠大力投資人工智能技術，並招募頂尖人才從事人工智能項目。 這使得保險公司能夠保持領先地位。 例如，北美最大的保險公司之一好事達正在利用人工智能來改善其運營和客戶體驗。 Allstate 使用人工智能分析客戶數據來提供個性化的保險產品和服務。

亞太地區近年來經歷了快速的經濟增長，是許多全球最大的保險公司的所在地，這些公司對該行業人工智能技術的發展和採用發揮了重要作用。 他們認識到人工智能在改善運營和客戶體驗方面的潛力，並正在投資人工智能技術。 例如，日本郵政保險正在利用人工智能通過分析客戶數據並提供更個性化的保險產品和服務來改善其運營和客戶體驗。

內容

第 1 章簡介

  • 市場概況
  • 市場定義
  • 調查範圍
  • 市場細分
  • 貨幣
  • 先決條件
  • 基準年和預測年時間表

第 2 章研究方法

  • 調查數據
  • 調查設計

第 3 章執行摘要

  • 調查要點

第 4 章市場動態

  • 市場促進因素
  • 市場抑制因素
  • 波特五力分析
  • 行業價值鏈分析

第 5 章保險人工智能 (AI) 市場：按應用分類

  • 簡介
  • 欺詐檢測
  • 風險分析
  • 客戶服務
  • 保險索賠評估
  • 其他

第 6 章保險人工智能 (AI) 市場：按第一部門劃分

  • 簡介
  • 人壽保險
  • 健康保險
  • 產權保險
  • 其他

第 7 章保險人工智能 (AI) 市場：按技術分類

  • 簡介
  • 深度學習
  • 機器學習
  • 機器人自動化
  • 其他

第 8 章保險人工智能 (AI) 市場：按地區劃分

  • 簡介
  • 北美
    • 美國
    • 加拿大
    • 墨西哥
  • 南美洲
    • 巴西
    • 阿根廷
    • 其他
  • 歐洲
    • 德國
    • 法國
    • 英國
    • 西班牙
    • 其他
  • 中東和非洲
    • 沙特阿拉伯
    • 阿拉伯聯合酋長國
    • 以色列
    • 其他
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 印度尼西亞
    • 台灣
    • 其他

第 9 章競爭格局與分析

  • 主要公司及戰略分析
  • 新興公司和市場盈利能力
  • 合併、收購、協議與合作
  • 供應商競爭力矩陣

第 10 章公司簡介

  • Amelia US LLC
  • Microsoft Corporation
  • Amazon Web Services Inc.
  • IBM Corporation
  • Avaamo Inc.
  • Cape Analytics LLC
  • Wipro Limited
  • Acko General Insurance
  • Shift Technology
  • BIMA
簡介目錄
Product Code: KSI061614384

AI for insurance market is expected to grow at a CAGR of 33.05% from a market size of US$1.209 billion in 2021 to reach US$8.925 billion in 2028. Artificial Intelligence (AI) has been making inroads into the insurance industry, with insurers using the technology to improve various aspects of their business. It is being used to automate the underwriting process, enabling insurers to make more informed decisions about the risk associated with a particular policy and identify and prevent fraudulent insurance claims. AI algorithms can analyze data from a variety of sources, such as social media, financial statements, and medical records, to determine the risk associated with a policy. Furthermore, it can analyze large amounts of data, such as claims history and policyholder behavior, to detect patterns that are indicative of fraud.

Chatbots and virtual agents are becoming increasingly popular in the insurance industry, as they provide customers with a convenient and accessible way to purchase and manage their insurance policies. For example, it can provide customers with information about their policies, claims, and payments, and answer frequently asked questions in real time. Blockchain technology, which provides a secure and transparent ledger for recording transactions, is also gaining attention in this sector. This technology can help insurance companies improve data privacy and security, reduce costs associated with traditional administrative processes, and increase transparency and efficiency.

Market Drivers

Growth in telematics and IoT devices

The growth in telematics and Internet of Things (IoT) devices is generating a large amount of data that can be used to enhance underwriting and pricing decisions. AI algorithms can analyze this data to determine the risk associated with a policy and provide more accurate pricing. Insurers can now gather vast amounts of data about policyholders, which can be used to determine personalized pricing for insurance policies. Further, it can be used to detect fraud in the insurance industry. For instance, data from a telematics device can be used to determine if a policyholder's driving habits match the information provided in the policy application. AI algorithms can analyze this data to detect patterns that are indicative of fraud.

Preference towards personalized insurance

With the rise of digital technology and access to information, consumers are becoming more aware of the benefits of personalized insurance. This includes customized policy recommendations and tailored coverage that better meets their specific needs and requirements. Advances in technology have made it possible to offer more personalized insurance policies at more affordable prices. AI algorithms can analyze large amounts of data, enabling insurance companies to offer policies that are better attuned to the individual needs and budget of each customer. For instance, a customer who consistently drives at safe speeds and avoids sudden braking may be offered a lower premium than someone who engages in high-risk driving behavior. Metromile is a usage-based car insurance provider that uses AI and telematics technology to track driving behavior and offers personalized insurance policies. The company's app tracks mileage and driving behavior, and based on this information, offers individualized insurance quotes that are updated in real-time.

Restraints

The insurance industry is highly regulated, and the use of AI technology must comply with various laws and regulations. This can be a challenge for insurance companies, as complying with these regulations may require significant resources and investment. The insurance industry has been slow to adopt new technology, and some companies may be resistant to change. Some traditional insurance companies may be reluctant to adopt AI technology due to concerns about the costs and risks associated with implementation.

Market Developments

  • In April 2022, Applied System an innovative insurance software provider partnered with Koos Intelligence to offer cutting-edge AI-powered insurance solutions that can help insurance companies better serve their customers with more advanced and personalized insurance solutions.
  • In July 2021, Microsoft formed a partnership with Darktrace, a U.K.-based cyber security AI service provider to leverage the strengths of both companies to deliver a comprehensive cyber security solution that helps organizations better protect against cyber threats and can help organizations better defend against cyber attacks and keep their critical assets and information secure.

North America is projected to hold a considerable share over the forecasted period.

North America is known for its high adoption of technology, and the insurance industry is no exception. Many insurance companies in the region have been quick to adopt AI technology to improve their operations and stay competitive. It has a well-developed infrastructure, including high-speed internet, advanced data centers, and a robust IT industry. This infrastructure provides an ideal environment for development and deployment. The strong economy of this region has allowed insurance companies to invest heavily in AI technology and hire top talent to work on AI projects. This has led insurance companies to stay ahead of the curve. For instance, Allstate is one of the largest insurance companies in North America, and the company is using AI to improve its operations and customer experience. Allstate is using AI to analyze customer data and to provide personalized insurance products and services.

The Asia Pacific region has been experiencing rapid economic growth in recent years, this region is home to many of the world's largest insurance companies, and these companies are playing a major role in the development and adoption of AI technology in this industry. They are recognizing the potential of AI to improve their operations and customer experience and investing in AI technology. For instance, Japan Post Insurance is using AI to improve its operations and customer experience, by analyzing customer data and providing more personalized insurance products and services.

Market Segmentation

By Application

  • Fraud Detection
  • Risk Analysis
  • Customer Service
  • Claims Assessment
  • Others

By Sector

  • Life Insurance
  • Health Insurance
  • Title Insurance
  • Others

By Technology

  • Deep Learning
  • Machine Learning
  • Robotic Automation
  • Others

By Geography

  • North America
    • USA
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Others
  • Europe
    • Germany
    • France
    • United Kingdom
    • Spain
    • Others
  • Middle East and Africa
    • Saudi Arabia
    • UAE
    • Israel
    • Others
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Indonesia
    • Taiwan
    • Others

TABLE OF CONTENTS

1. INTRODUCTION

  • 1.1. Market Overview
  • 1.2. Market Definition
  • 1.3. Scope of the Study
  • 1.4. Market Segmentation
  • 1.5. Currency
  • 1.6. Assumptions
  • 1.7. Base, and Forecast Years Timeline

2. RESEARCH METHODOLOGY

  • 2.1. Research Data
  • 2.2. Research Design

3. EXECUTIVE SUMMARY

  • 3.1. Research Highlights

4. MARKET DYNAMICS

  • 4.1. Market Drivers
  • 4.2. Market Restraints
  • 4.3. Porter's Five Forces Analysis
    • 4.3.1. Bargaining Power of Suppliers
    • 4.3.2. Bargaining Power of Buyers
    • 4.3.3. Threat of New Entrants
    • 4.3.4. Threat of Substitutes
    • 4.3.5. Competitive Rivalry in the Industry
  • 4.4. Industry Value Chain Analysis

5. AI FOR INSURANCE MARKET BY APPLICATION

  • 5.1. Introduction
  • 5.2. Fraud Detection
  • 5.3. Risk Analysis
  • 5.4. Customer Service
  • 5.5. Claims Assessment
  • 5.6. Others

6. AI FOR INSURANCE MARKET BY SECTOR

  • 6.1. Introduction
  • 6.2. Life Insurance
  • 6.3. Health Insurance
  • 6.4. Title Insurance
  • 6.5. Others

7. AI FOR INSURANCE MARKET BY TECHNOLOGY

  • 7.1. Introduction
  • 7.2. Deep Learning
  • 7.3. Machine Learning
  • 7.4. Robotic Automation
  • 7.5. Others

8. AI FOR INSURANCE MARKET, BY GEOGRAPHY

  • 8.1. Introduction
  • 8.2. North America
    • 8.2.1. USA
    • 8.2.2. Canada
    • 8.2.3. Mexico
  • 8.3. South America
    • 8.3.1. Brazil
    • 8.3.2. Argentina
    • 8.3.3. Others
  • 8.4. Europe
    • 8.4.1. Germany
    • 8.4.2. France
    • 8.4.3. United Kingdom
    • 8.4.4. Spain
    • 8.4.5. Others
  • 8.5. Middle East and Africa
    • 8.5.1. Saudi Arabia
    • 8.5.2. UAE
    • 8.5.3. Israel
    • 8.5.4. Other
  • 8.6. Asia Pacific
    • 8.6.1. China
    • 8.6.2. Japan
    • 8.6.3. India
    • 8.6.4. South Korea
    • 8.6.5. Indonesia
    • 8.6.6. Taiwan
    • 8.6.7. Others

9. COMPETITIVE ENVIRONMENT AND ANALYSIS

  • 9.1. Major Players and Strategy Analysis
  • 9.2. Emerging Players and Market Lucrativeness
  • 9.3. Mergers, Acquisitions, Agreements, and Collaborations
  • 9.4. Vendor Competitiveness Matrix

10. COMPANY PROFILES

  • 10.1. Amelia US LLC
  • 10.2. Microsoft Corporation
  • 10.3. Amazon Web Services Inc.
  • 10.4. IBM Corporation
  • 10.5. Avaamo Inc.
  • 10.6. Cape Analytics LLC
  • 10.7. Wipro Limited
  • 10.8. Acko General Insurance
  • 10.9. Shift Technology
  • 10.10. BIMA