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市場調查報告書
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1139258

全球保險分析市場 - COVID-19 的增長、趨勢、影響和預測(2022-2027 年)

Global Insurance Analytics Market - Growth, Trends, and Forecasts (2022 - 2027)

出版日期: | 出版商: Mordor Intelligence | 英文 120 Pages | 商品交期: 2-3個工作天內

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簡介目錄

保險分析市場預計在預測期間(2022-2027 年)將達到 12.6% 的複合年增長率。

隨著信息流入組織,保險公司開始關注海量數據存儲並將其轉化為可操作的見解。因此,公司需要實施保險分析系統,以管理快速變化的市場環境並通過更好的決策來提高盈利能力。

主要亮點

  • 全球保險業正在朝著採用數字技術的方向發生重大轉變。最近的一項調查發現,86% 的保險公司正在研究保險數據分析機制,以最好地預測大數據報告(來源:DAMCO Solutions)。
  • 最近對 68 家 EMEA 保險公司進行的一項調查發現,大約 85-90% 的受訪 EMEA 保險公司難以為數據分析解決方案找到積極的商業案例。這一點變得很清楚。保險公司面臨著阻礙他們釋放數據分析解決方案潛力的各種挑戰。保險公司現在覺得他們需要潛入以跟上競爭對手和 InsurTech 初創公司的步伐,但他們首先需要可靠的數據分析能力才能從這些技術中獲利。在過去的幾年裡,美國的人壽保險公司也提高了承保業務的簡化和自動化程度,使在線購買人壽保險變得更加容易和更具成本效益。這些因素正在增加市場增長採用的趨勢。
  • 此外,人工智能和機器學習等技術進步為這些解決方案增加了價值。根據埃森哲的研究,到 2035 年,在金融領域引入人工智能可以將盈利能力提高 31%。此外,人工智能將為客戶提供定制的金融服務,從而改善客戶體驗。因此,基於人工智能的保險分析解決方案可以為金融機構降低數十億美元的成本,產生數十億美元的額外收入,並減少欺詐。
  • 此外,公司還面臨著應對災難、管理放大的風險、應對加強監管的需求、信息日益豐富且要求苛刻的客戶群以及在仍不確定的經濟環境中駕馭等挑戰。面臨的挑戰越來越多進一步推動保險分析的採用。據 IBM 稱,實施高級分析解決方案的保險公司的表現比競爭對手高出 76%。
  • 隨著 COVID-19 危機的爆發,波動性、不確定性和經濟活動低迷導致的結構性變化正在對保險業產生重大影響。這種轉變正迫使保險公司重塑其運營和客戶體驗。此外,對數字交互以及更好地管理個人和健康風險的需求正在加速對數字和分析解決方案的投資。因此,預計市場將在預測期內增長。

主要市場趨勢

風險和欺詐的增加正在推動保險分析的採用。

  • 保險業圍繞著定期識別和管理人為和自然風險展開。這種不確定的風險對整合日常運營的洞察力、控制和優化的綜合風險管理提出了巨大的需求。保險分析解決方案提供了重要的見解,以改善各個層面的風險管理。
  • 企業及其保險公司必須不斷應對複雜且瞬息萬變的風險,例如極端天氣、通脹壓力和網絡威脅。保險公司面臨的挑戰是在正確的時間為正確的人提供大規模的數據分析。保險公司必須將數據分析納入其日常決策和流程。
  • 此外,不斷增長的數字人口及其需求正在推動市場參與者不斷創新以降低風險和欺詐行為。例如,2021 年 5 月,為保險公司提供基於人工智能的 SaaS 工具的 Shift Technology 宣布已籌集 2.2 億美元,用於擴大其在財產險市場的業務。
  • 趨勢的採用正在增加使用分析來預測新客戶風險並防止欺詐性索賠。保險公司越來越多地使用基於雲的 GPU 加速人工智能 (AI) 和機器學習 (ML) 預測分析模型,以改善客戶體驗並快速準確地識別欺詐性保險索賠。.
  • 例如,2022 年 9 月,機器學習和預測分析解決方案提供商 Attidot 與 IT 服務和數字業務提供商 NTT DATA 合作開發成熟的維護計劃,降低意外風險並提高投資回報率。該公司宣布將提供向客戶提供信息並增強客戶體驗,通過優化和提高增長效率來推進其增長目標。利用分析來減少承保週期時間並改善新客戶獲取。
  • 2021 年,印度人壽保險公司 (LIC) 簽發了大約 2100 萬份新的個人保單。總體而言,同年全國新增個人保單約2800萬份。保險業的這種激增增加了對保險分析市場的需求,以進一步降低相關風險。

亞太地區增長最快

  • 由於消費者和企業越來越多地使用分析工具,預計亞太地區將見證保險分析市場的最快增長。該地區的分析市場主要由數字基礎設施的高采用率推動,推動了對算法開發、機器學習、客戶分析和行為分析的日益增長的需求。
  • 政府通過實施舉措來增強企業對雲的信心,在亞太地區保險分析市場的未來增長中發揮著關鍵作用。由於數據隱私法規和政府對雲的大力支持,香港和新加坡等國家/地區正變得更加適合雲計算。
  • 此外,該地區國家擁有雄厚的基礎和不斷發展的保險業,進一步推動了市場的增長。 2022年9月,HDFC ERGO General Insurance將搭建在線保險銷售平台,為客戶提供量身定制的數字化體驗,快速響應監管變化,並利用數據分析和機器學習(ML)分析保險風險。 ,它宣布與穀歌雲建立合作夥伴關係。谷歌還將提供人工智能/機器學習技術來建立預測性洞察力並減少保險欺詐。
  • 根據日本人壽保險公司的數據,到 2021 年,日本 55 歲至 59 歲的戶主家庭中約有 95% 將擁有人壽保險,而 29 歲及以上的家庭戶主將擁有人壽保險。 18、人壽保險參保率約為70.2%。這一高比例的投保人正在推動區域企業轉向基於分析的解決方案,以提供更好的客戶參與和風險管理解決方案。
  • COVID-19 大流行擾亂了保險分銷模式。亞洲保險公司正在調整治理和管理,並建立新的技術能力以滿足不斷增長的客戶需求。例如,在中國,與健康保險相關的業務由於 COVID-19 而急劇增加。

競爭格局

保險分析市場適度分散。參與者傾向於投資於產品創新,以滿足保險業不斷變化的需求。此外,參與者正在通過合作、併購等戰略活動來擴大其影響力。市場的最新發展包括:

  • 2021 年 6 月- Minsite 與微軟在雲轉型服務和項目的戰略推廣方面加強合作。 Minsait 的目標是促進客戶的超細分和實時信息處理,以設計更符合其個人資料的個性化保險。
  • 2021 年 6 月 - Eckerson Group 與保險數據管理協會 (IDMA) 合作,為保險公司的企業數據和分析團隊啟動了一項在線基準研究。該基準由一組保險行業數據和分析專家監督。
  • 2021 年 5 月 - LexisNexis Risk Solutions 宣佈為其 Attract for Commercial Insurance 平台推出新的保險模式。該模型利用其與小型企業金融交易所 (SBFE) 的關係,為保險公司提供針對小型和微型企業的增強可見性和財務數據洞察力。
  • 2021 年 4 月 - AXA 與 Microsoft 合作,在雲計算平台上構建數字醫療保險。這種新的合作預計將建立一個生態系統,當地醫療保健網絡可以訪問遠程諮詢、自我評估工具和第三方服務。預計這將推動微軟保險分析平台的採用。

其他福利。

  • Excel 格式的市場預測 (ME) 表
  • 3 個月的分析師支持

內容

第1章介紹

  • 研究假設和市場定義
  • 調查範圍

第2章研究方法

第 3 章執行摘要

第 4 章市場洞察

  • 市場概覽
  • 工業吸引力 - 波特五力分析
    • 供應商的議價能力
    • 消費者的議價能力
    • 新進入者的威脅
    • 替代品的威脅
    • 競爭公司之間的敵對關係
  • 評估 COVID-19 對行業的影響
  • 市場驅動力
    • 更多地採用先進技術
    • 保險業競爭加劇
  • 市場製約因素
    • 嚴格的政府法規
    • 隱私和安全問題

第 5 章市場細分

  • 按組件
    • 工具
    • 按服務
  • 按業務應用(定性分析)
    • 索賠管理
    • 風險管理
    • 流程優化
    • 客戶管理和個性化
  • 按部署模式
    • 本地
  • 按最終用戶
    • 保險公司
    • 政府機構
    • 第三方管理員、經紀人和顧問
  • 按地區
    • 北美
    • 歐洲
    • 亞太地區
    • 世界其他地區

第 6 章競爭格局

  • 公司簡介
    • IBM Corporation
    • LexisNexis Risk Solutions
    • Hexaware Technologies Limited
    • Guidewire Software Inc.
    • Applied Systems Inc.
    • Microsoft Corporation
    • MicroStrategy Incorporated
    • OpenText Corporation
    • Oracle Corporation
    • Sapiens International Corporation

第 7 章供應商市場份額

第 8 章市場機會和未來趨勢

簡介目錄
Product Code: 71514

The insurance analytics market is expected to reach a CAGR of 12.6% during the forecast period (2022 - 2027). With information pouring into the organization, insurance companies focus and turn vast data stores into actionable insights. Hence, this creates a demand for companies to adopt an insurance analytics system to manage rapidly changing market environments and profitability through better decision-making.

Key Highlights

  • The global insurance industry has witnessed a significant shift toward adopting digital technologies. According to the findings of a recent study, 86% of insurance companies are working on Insurance data analytics mechanisms for optimum predictions of big data reports (source: DAMCO Solutions).
  • A recent study among 68 EMEA insurance companies has shown that around 85 to 90% of interviewed EMEA insurance firms struggle to see a positive business case on data analytics solutions. Insurance companies face various challenges that prevent them from reaching the potential of Data Analytics solutions. Insurers now feel that they have to jump in to not get behind of competition or behind of InsurTech startups, but in order to profit from these technologies, they will need a solid Data Analytics capability first. Also, over the past several years, in the US, life insurers have expanded their simplified and automated underwriting practices to make buying life insurance online easier and more cost-effective. Such factors are increasing the trend adoption of market growth.
  • Furthermore, technological advancements such as AI, Machine learning are adding value to these solutions. According to a study by Accenture, implementing AI in the financial sector could lead to a 31% increase in profitability rates by 2035. Moreover, AI will enable customized financial services delivered to clients, leading to enhanced customer experience. Hence, AI-based insurance analytics solutions can save financial institutions billions in cost, create billions in additional revenues, and reduce fraudulent activities.
  • Moreover, the increasing challenges faced by companies, such as dealing with catastrophes, managing amplified risk, meeting the demands of greater regulatory scrutiny, a more informed and demanding customer base, and navigating through a still uncertain economic environment, are further boosting the adoption of insurance analytics. According to IBM, Insurance organizations that have implemented advanced analytical solutions outperformed the competition by 76%.
  • With the outbreak of the COVID-19 crisis, structural shifts due to volatility, uncertainty, and depressed economic activity have significant implications for the insurance industry. These shifts are forcing insurance providers to reimagine their business operations and customer experience. Moreover, the demand for digital interactions and better management of personal and health risks are accelerating investments in digital and analytics solutions. Hence the market is anticipated to grow over the forecast period.

Key Market Trends

Increasing Risks And Fraudulent Activities Are Boosting the Adoption Of Insurance Analytics.

  • The insurance industry revolves around identifying and managing both human-made and natural disaster risks regularly. This uncertain risk creates considerable demand for integrated risk management, a combination of insight, control, and optimization of daily business practices. The insurance analytics solutions offer the essential insight required to improve risk management at all levels.
  • Businesses and their insurers regularly have to keep pace with fast-changing and complex risks, such as extreme weather events, inflationary pressures, or cyber threats. For insurers, the challenge is to deliver data analytics at scale, to the right people, and at the right time. Insurers need to integrate data analytics into day-to-day decision-making and processes.
  • Further, due to the rising digital population and their demands, players in the market are continuously driving innovation to mitigate risk and fraudulent activities. For instance, In May 2021, Shift Technology, a provider of AI-based SaaS tools to insurance companies, announced that it had raised USD 220 million to expand in the property and casualty insurance market.
  • The trend adoption is more towards analytics being used to predict new customer risk and prevent fraud claims. Insurance organizations are increasingly using cloud-based, GPU-accelerated artificial intelligence (AI) and machine learning (ML) predictive analysis models to improve the customer experience and identify fraudulent insurance claims quickly and accurately.
  • For instance, In September 2022, Atidot, a machine learning and predictive analytics solution provider, announced its partnership with NTT DATA, an IT services and digital business provider, to enhance customer experience by developing mature conservation programs, mitigating unintended risks, and providing the customers the intelligence to drive growth objectives by optimizing ROI and increasing growth efficiencies. It will enable the use of analytics to reduce underwriting cycle time to improve new client acquisition.
  • India's Life Insurance Corporation (LIC) issued around 21 million new individual policies in 2021. Overall, about 28 million new separate policies were issued nationwide that year. Such a surge in the Insurance sector is increasing the demand for the insurance analytics market to lower the related risks further.

Asia-Pacific to Witness Highest Growth

  • Asia-Pacific is expected to witness the fastest growth in the insurance analytics market due to consumer and businesses' increased take-up of analytics tools. The high adoption of digital infrastructure primarily drives the region's analytics markets due to the growing algorithm development, machine learning, and the rising need for customer and behavioral analytics.
  • National governments play a pivotal role in the future growth of the insurance analytics market across the Asia-Pacific region by implementing initiatives to build more business confidence in the cloud. Countries like Hong Kong and Singapore have defined data privacy regulations and solid governmental support for the cloud leading the way in cloud readiness.
  • Moreover, countries in the region have a strong base and growing insurance industry, further driving the market's growth. In September 2022, HDFC ERGO General Insurance announced its partnership with google cloud to build an online platform for selling insurance, offering tailored digital experiences to customers, responding to regulatory changes faster, and identifying insurance risks using data analytics and machine learning (ML). Google will also provide them with AI/ML technologies to build predictive insights and mitigate insurance fraud.
  • According to the Japan Institute of Life Insurance, In 2021, around 95 percent of households in Japan head aged between 55 to 59 years had at least one member who owned life insurance whereas, with the head age of 29 or less, the life insurance ownership rate was recorded at around 70.2 percent. Such a large percentage of the insured population in the country is creating the demand for regional companies to switch to analytics-based solutions to offer better customer engagement and risk management solutions.
  • Due to the COVID-19 pandemic, the insurance distribution model has been disrupted. The Asian insurers are adjusting governance and management and building new technical capabilities to satisfy the growing customer needs. For instance, China has experienced a dramatic increase in health insurance-related activities due to COVID-19.

Competitive Landscape

The insurance analytics market is moderately fragmented. Players tend to invest in innovating their product offerings to cater to the insurance industry's changing demands. Moreover, players adopt strategic activities like partnerships, mergers, and acquisitions to expand their presence. Some of the recent developments in the market are:

  • June 2021 - Minsait and Microsoft strengthen their collaboration in strategically promoting cloud transformation services and projects. Minsait's purpose is to facilitate the hyper-segmentation of customers and real-time information processing to design more personalized insurance to suit each profile.
  • In June 2021 - Eckerson Group, in partnership with Insurance Data Management Association (IDMA), launched an online benchmark assessment geared to insurance companies' enterprise data and analytics teams. The benchmark is overseen by a board of data & analytics experts from the insurance industry.
  • May 2021 - LexisNexis Risk Solutions announced the launch of a new insurance model for the Attract for Commercial Insurance platform, which leverages its relationship with the Small Business Financial Exchange (SBFE) and provides insurance carriers with extended visibility and financial data insight on small and micro-businesses.
  • April 2021 - AXA Collaborated with Microsoft to create digital healthcare insurance on a cloud computing platform. The new collaboration is expected to establish an ecosystem for the local health networks that enables them to gain access to teleconsultation, self-assessment tools, and third-party services. This is expected to boost Microsoft's adoption of the insurance analytics platform.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET INSIGHTS

  • 4.1 Market Overview
  • 4.2 Industry Attractiveness - Porter's Five Forces Analysis
    • 4.2.1 Bargaining Power of Suppliers
    • 4.2.2 Bargaining Power of Consumers
    • 4.2.3 Threat of New Entrants
    • 4.2.4 Threat of Substitutes
    • 4.2.5 Intensity of Competitive Rivalry
  • 4.3 Assessment of the Impact of COVID-19 on the Industry
  • 4.4 Market Drivers
    • 4.4.1 Increased Adoption of Advance Technologies
    • 4.4.2 Rise in Competition among the Insurance Sector
  • 4.5 Market Restraints
    • 4.5.1 Stringent Government Regulations
    • 4.5.2 Privacy and Security Concern

5 MARKET SEGMENTATION

  • 5.1 By Component
    • 5.1.1 Tool
    • 5.1.2 Services
  • 5.2 By Business Application (Qualitative Analysis)
    • 5.2.1 Claims Management
    • 5.2.2 Risk Management
    • 5.2.3 Process Optimization
    • 5.2.4 Customer Management and Personalization
  • 5.3 By Deployment Mode
    • 5.3.1 On-premise
    • 5.3.2 Cloud
  • 5.4 By End-User
    • 5.4.1 Insurance Companies
    • 5.4.2 Government Agencies
    • 5.4.3 Third-party Administrators, Brokers, and Consultancies
  • 5.5 By Geography
    • 5.5.1 North America
    • 5.5.2 Europe
    • 5.5.3 Asia-Pacific
    • 5.5.4 Rest of the World

6 COMPETITIVE LANDSCAPE

  • 6.1 Company Profiles
    • 6.1.1 IBM Corporation
    • 6.1.2 LexisNexis Risk Solutions
    • 6.1.3 Hexaware Technologies Limited
    • 6.1.4 Guidewire Software Inc.
    • 6.1.5 Applied Systems Inc.
    • 6.1.6 Microsoft Corporation
    • 6.1.7 MicroStrategy Incorporated
    • 6.1.8 OpenText Corporation
    • 6.1.9 Oracle Corporation
    • 6.1.10 Sapiens International Corporation

7 VENDOR MARKET SHARE

8 MARKET OPPORTUNITIES AND FUTURE TRENDS