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保險人工智能

市場調查報告書

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1528196

印度保險生成式人工智慧市場評估：依部署、技術、應用、地區、機會、預測（2018 年度-2032 年度）

India Generative AI in Insurance Market Assessment, By Deployment, By Technology, By Application, By Region, Opportunities and Forecast, FY2018-FY2032F

出版日期: 2024年08月07日 | 出版商:

Market Xcel - Markets and Data | 英文 132 Pages | 商品交期: 3-5個工作天內

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簡介目錄圖表

印度保險人工智慧市場規模預計將從2024 年度的 2,902 萬美元增至2032 年度的 3.8795億美元，預計2024 年度至2032 年度的年複合成長率為 38.28%。由於加強客戶互動、優化內部流程和改善風險管理等因素，生成式人工智慧改變印度保險市場的面貌，推動保險市場生成式人工智慧的成長。基於人工智慧和虛擬助理的聊天機器人透過為客戶詢問提供客製化的及時答案，自動執行保單查詢和報價請求等任務。這提高了客戶滿意度，並節省了人工顧問處理更複雜任務的時間。它還透過檢查文件的真實性和分析保險索賠資料中的可疑模式來幫助檢測詐欺行為。此外，人工智慧還有助於客製化個人保險產品和服務，讓客戶可以自行決定。

2023年7月，HDFC ERGO General Insurance Company Limited 推出了生成式AI 和Google Cloud 卓越中心（CoE），以支援HDFC ERGO，提高生成式AI 團隊的技能並開發用例，並宣布他們將識別和開發用例。

串流媒體客戶服務推動生成式人工智慧市場成長

生成式人工智慧改變印度保險市場的客戶服務體驗。這將為所有保單持有人帶來更好的控制和個人化體驗。使用自然語言處理和機器學習演算法，人工智慧聊天機器人可以模擬人類對話，獲取有關客戶詢問的知識，並即時提供準確的解決方案。預計這將增強整體互動，減少人工中介的工作量，並使他們能夠更有效地解決複雜問題。此外，生成式人工智慧將能夠處理大量資料以找到提供客製化建議的模式，確保根據每個客戶的要求和偏好推薦客製化的行動方案。隨著科技的不斷發展，生成式人工智慧將促進從保單選擇到理賠管理的保險流程，創造更令人滿意的客戶體驗，進而提高對印度保險公司的忠誠度。

2024年 1月，Bharti Enterprises 和 AXA 的合資企業 Bharti AXA General Insurance 推出了生成式 AI 聊天機器人，為客戶詢問提供個人化且及時的答覆。

增強的風險評估和詐欺偵測推動成長

生成式人工智慧模型可以增強模擬和估計與保險領域相關的風險的能力。人工智慧模型可以根據過去的資料產生各種場景。這使得保險公司能夠更佳了解各種風險的可能性和潛在影響。這有助於保險公司在確定適當的保費時做出明智的決定。透過運行各種風險場景並使用該信息，保險公司可以調整事件的機率和嚴重程度，使其更加合適。它幫助保險公司管理自己的風險，同時確保客戶公平、準確地收取代表實際保險成本的保費。生成式人工智慧在保險領域的應用展示瞭如何利用先進技術更佳管理風險並改善客戶體驗，提高保險業的彈性。

本報告研究和分析了印度保險生成式人工智慧市場，提供市場規模和預測、市場動態、主要參與者的現狀和前景等。

India generative AI in insurance market is projected to witness a CAGR of 38.28% during the forecast period FY2024-FY2032, growing from USD 29.02 million in FY2024 to USD 387.95 million in FY2032. Generative AI is changing the face of the Indian insurance market, owing to factors such as enhanced client interaction, optimization of internal processes, and better risk management, driving the growth of generative AI in insurance market. Chatbots based on AI and virtual assistants provide customized and timely responses to client queries, thereby automating tasks such as policy enquiries and quotation requests. This improves customer satisfaction and saves time of human advisors to deal with more complex tasks. It makes fraud detection easier by checking document authenticity and analyzing suspicious patterns in claims data. Additionally, AI makes it easier to custom-create personal insurance products and services that customers, by themselves, can decide upon.

In July 2023, HDFC ERGO General Insurance Company Limited announced the launch of the Centre of Excellence (CoE) for the Generative Artificial Intelligence (AI) and Google Cloud to support HDFC ERGO in the identification and development of the use-cases along with upskilling its teams on Gen AI.

Streaming Customer Service to Drive Market Growth of Generative AI

Generative AI is changing the customer service experience in the India insurance market. It is set to bring better management and personalized experience for all policyholders. Using natural language processing and machine learning algorithms, AI-enabled chatbots can simulate human conversations to gain knowledge of customer queries and respond to them with accurate solutions in real time. This is expected to enhance overall interaction and reduce the workload on human agents, allowing them to deal with complex issues more effectively. Further, generative AI will be able to process huge amounts of data to find the pattern for providing customized recommendations so that each customer gets policy recommendations tailored according to their requirements and tastes. With continued developments in technology, generative AI is bound to play a crucial role in smoothing out insurance processes from policy selection to management of claims, which shapes customer experiences with greater satisfaction, and hence loyalty toward insurance companies in India.

In January 2024, Bharti AXA General Insurance, the joint venture between Bharti Enterprises and AXA, initiated generative AI chatbots to provide personalized and timely responses to customer queries.

Enhanced Risk Assessment and Fraud Detection to Drive Growth

Generative AI models can enhance the capability to simulate and estimate risks involved in the realm of insurance. It can generate a large spectrum of scenarios based on historical data. This helps insurers to better understand the likelihood and potential impact of various risks. These valuable insights help insurers make informed decisions in deciding appropriate premiums. It runs different risk scenarios, and based on that information, companies can correct the setting of probability and magnitude of an event with a better view, hence modifying their pricing accordingly. It is helpful in self-risk management for the insurers, but it assures the customers that they will be charged a priced premium fairly and precisely, representing the actual cost of coverage. The use of generative AI in insurance how advanced technologies can be harnessed toward better risk management and enhanced customer experience, thereby improving the resilience of the sector.

Chatbot Segment to Dominate Market

The chatbot segment is dominating the Indian insurance industry. Generative AI is changing the face of insurance with new ways of analyzing data, customer interaction, fraud detection, and business insights. Chatbots and virtual assistants, powered by AI, are rendering customized and timely responses to customer queries, which are automating processes such as policy inquiries and quotation requests. The automation increases customer satisfaction and allows human advisors to engage in more complex value-adding tasks. In addition, AI algorithms can flag potentially fraudulent activities by checking the authenticity of documents and detecting suspicious patterns in claims data, hence aiding insurers in fraud detection and deterrence.

In March 2024, Bajaj Allianz General Insurance launched Insurance Samjho, a Gen AI-powered bot, to simplify insurance for customers. This bridges the gap for customers by explaining the meaning of jargons in simplified and conversational terms. Customers are free to ask anything with regard to policies such as about what is covered or excluded and procedures of buying insurance.

Future Market Scenario (FY2024 - FY2032F)

The potential of generative AI in insurance is tremendous. The market is gradually moving into the space where AI can perform customer service and underwriting processes more efficiently, along with largely reducing fraudulent activities.

AI-driven chatbots and virtual assistants will provide personalized and timely responses to customer queries, increasing satisfaction, and allowing human advisors to address higher-core value functions. Predictive AI and machine learning models will help insurers to avoid adverse selection, perform constant fraud detection and remote claims assessment, and process claims quickly and seamlessly.

Generative AI will enable interactions that are hyper-personalized in nature, where the channels of interactions offer customized solutions to the customers based on their choices and risk profiles.

Key Players Landscape and Outlook

The growth of generative AI in insurance market is driven by increasing adoption across digital platforms, growing demand for personalized solutions in insurance, and government investments in research and development to focus on process optimization of products and services. With increasing adoption of generative AI in the India insurance industry the rise of competition from global and domestic market players can be witnessed. The insurers who are better equipped to use generative AI to achieve operational efficiencies, manage risks, and improve customer experience will gain a competitive advantage over others in the transforming Indian insurance market.

In May 2024, Bajaj Allianz General Insurance introduced generative AI systems for its underwriting process automation. These AI models will analyze data from applicants, medical records, and other information that may award risky profiles and modify accordingly the coverage and premium charged for that particular risk. It quickens the speed of underwriting with more consistency and accuracy.

1. Project Scope and Definitions

2. Research Methodology

3. Executive Summary

4. Voice of Customer

4.1. Product and Market Intelligence
4.2. Factors Considered in Purchase Decisions
- 4.2.1. Customization and Flexibility
- 4.2.2. Data Security and Privacy
- 4.2.3. Company Reputation
- 4.2.4. Product Scalability
- 4.2.5. Integration Capabilities
- 4.2.6. Regulatory Compliance
4.3. Claim Processing Efficiency
4.4. Implementation Timeline
4.5. Customer Support and Service

5. India Generative AI in Insurance Market Outlook, FY2018-FY2032F

5.1. Market Size Analysis & Forecast
- 5.1.1. By Value
5.2. Market Share Analysis & Forecast
- 5.2.1. By Deployment
  - 5.2.1.1. Cloud-based
  - 5.2.1.2. On-premises
- 5.2.2. By Technology
  - 5.2.2.1. Machine Learning
  - 5.2.2.2. Natural Language Processing
- 5.2.3. By Application
  - 5.2.3.1. Fraud Detection and Credit Analysis
  - 5.2.3.2. Customer Profiling and Segmentation
  - 5.2.3.3. Product and Policy Design
  - 5.2.3.4. Underwriting and Claims Assessment
  - 5.2.3.5. Chatbots
- 5.2.4. By Region
  - 5.2.4.1. North
  - 5.2.4.2. East
  - 5.2.4.3. West and Central
  - 5.2.4.4. South
- 5.2.5. By Company Market Share Analysis (Top 5 Companies and Others - By Value, FY2024)
5.3. Market Map Analysis, FY2024
- 5.3.1. By Deployment
- 5.3.2. By Technology
- 5.3.3. By Application
- 5.3.4. By Region

6. Demand Supply Analysis

7. Value Chain Analysis

8. Porter's Five Forces Analysis

9. PESTLE Analysis

10. Subscription Cost Analysis

11. Market Dynamics

11.1. Market Drivers
11.2. Market Challenges

12. Market Trends and Developments

13. Case Studies

14. Competitive Landscape

14.1. Competition Matrix of Top 5 Market Leaders
14.2. SWOT Analysis for Top 5 Players
14.3. Key Players Landscape for Top 5 Market Players
- 14.3.1. Markovate Inc.
  - 14.3.1.1. Company Details
  - 14.3.1.2. Key Management Personnel
  - 14.3.1.3. Products and Services
  - 14.3.1.4. Financials (As Reported)
  - 14.3.1.5. Key Market Focus and Geographical Presence
  - 14.3.1.6. Recent Developments/Collaborations/Partnerships/Mergers and Acquisition
- 14.3.2. Leewayhertz Technologies Private Limited
- 14.3.3. Insurstaq Technologies Private Limited
- 14.3.4. Simplifai Cognitive Services Private Limited
- 14.3.5. Lithasa Technologies Private Limited

Companies mentioned above DO NOT hold any order as per market share and can be changed as per information available during research work.

15. Strategic Recommendations

16. About Us and Disclaimer

簡介目錄圖表

List of Tables

Table 1. Pricing Analysis of Products from Key Players
Table 2. Competition Matrix of Top 5 Market Leaders
Table 3. Mergers & Acquisitions/ Joint Ventures (If Applicable)
Table 4. About Us - Regions and Countries Where We Have Executed Client Projects

List of Figures

Figure 1. India Generative AI in Insurance Market, By Value, In USD Million, FY2018-FY2032F
Figure 2. India Generative AI in Insurance Market Share (%), By Deployment, FY2018-FY2032F
Figure 3. India Generative AI in Insurance Market Share (%), By Technology, FY2018-FY2032F
Figure 4. India Generative AI in Insurance Market Share (%), By Application, FY2018-FY2032F
Figure 5. India Generative AI in Insurance Market Share (%), By Region, FY2018-FY2032F
Figure 6. By Deployment Map-Market Size (USD Million) & Growth Rate (%), FY2024
Figure 7. By Technology Map-Market Size (USD Million) & Growth Rate (%), FY2024
Figure 8. By Application Map-Market Size (USD Million) & Growth Rate (%), FY2024
Figure 9. By Region Map-Market Size (USD Million) & Growth Rate (%), FY2024

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保險領域生成式人工智慧的全球市場評估：按部署、按技術、按應用、按地區、機會、預測，2017-2031 年

FAQ

印度保險生成式人工智慧市場評估：依部署、技術、應用、地區、機會、預測（2018 年度-2032 年度）

India Generative AI in Insurance Market Assessment, By Deployment, By Technology, By Application, By Region, Opportunities and Forecast, FY2018-FY2032F

目錄

第1章專案範圍與定義

第2章研究方法

第3章執行摘要

第4章顧客回饋

第5章印度生成式人工智慧保險市場展望（2018 財政年度-2032 財政年度）

第6章供需分析

第7章價值鏈分析

第8章波特五力分析

第9章 PESTLE分析

第10章訂閱成本分析

第11章市場動態

第12章市場趨勢與發展

第13章案例研究

第14章競爭態勢

第15章策略建議

第16章關於本公司，免責聲明

Table of Contents

1. Project Scope and Definitions

2. Research Methodology

3. Executive Summary

4. Voice of Customer

5. India Generative AI in Insurance Market Outlook, FY2018-FY2032F

6. Demand Supply Analysis

7. Value Chain Analysis

8. Porter's Five Forces Analysis

9. PESTLE Analysis

10. Subscription Cost Analysis

11. Market Dynamics

12. Market Trends and Developments

13. Case Studies

14. Competitive Landscape

15. Strategic Recommendations

16. About Us and Disclaimer

List of Tables

List of Figures

印度保險生成式人工智慧市場評估：依部署、技術、應用、地區、機會、預測（2018 年度-2032 年度）

India Generative AI in Insurance Market Assessment, By Deployment, By Technology, By Application, By Region, Opportunities and Forecast, FY2018-FY2032F

目錄

第1章 專案範圍與定義

第2章 研究方法

第3章 執行摘要

第4章 顧客回饋

第5章 印度生成式人工智慧保險市場展望（2018 財政年度-2032 財政年度）

第6章 供需分析

第7章 價值鏈分析

第8章 波特五力分析

第9章 PESTLE分析

第10章 訂閱成本分析

第11章 市場動態

第12章 市場趨勢與發展

第13章 案例研究

第14章 競爭態勢

第15章 策略建議

第16章 關於本公司，免責聲明

Table of Contents

1. Project Scope and Definitions

2. Research Methodology

3. Executive Summary

4. Voice of Customer

5. India Generative AI in Insurance Market Outlook, FY2018-FY2032F

6. Demand Supply Analysis

7. Value Chain Analysis

8. Porter's Five Forces Analysis

9. PESTLE Analysis

10. Subscription Cost Analysis

11. Market Dynamics

12. Market Trends and Developments

13. Case Studies

14. Competitive Landscape

15. Strategic Recommendations

16. About Us and Disclaimer

List of Tables

List of Figures

第1章專案範圍與定義

第2章研究方法

第3章執行摘要

第4章顧客回饋

第5章印度生成式人工智慧保險市場展望（2018 財政年度-2032 財政年度）

第6章供需分析

第7章價值鏈分析

第8章波特五力分析

第10章訂閱成本分析

第11章市場動態

第12章市場趨勢與發展

第13章案例研究

第14章競爭態勢

第15章策略建議

第16章關於本公司，免責聲明