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保险人工智能

市场调查报告书

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1528196

印度保险生成式人工智慧市场评估：依部署、技术、应用、地区、机会、预测（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个工作天内

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简介目录图表

印度保险人工智慧市场规模预计将从2024 年度的 2,902 万美元增至2032 年度的 3.8795亿美元，预计2024 年度至2032 年度的年复合成长率为 38.28%。由于加强客户互动、优化内部流程和改善风险管理等因素，生成式人工智慧改变印度保险市场的面貌，推动保险市场生成式人工智慧的成长。基于人工智慧和虚拟助理的聊天机器人透过为客户询问提供客製化的及时答案，自动执行保单查询和报价请求等任务。这提高了客户满意度，并节省了人工顾问处理更复杂任务的时间。它还透过检查文件的真实性和分析保险索赔资料中的可疑模式来帮助检测诈欺行为。此外，人工智慧还有助于客製化个人保险产品和服务，让客户可以自行决定。

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 团队的技能并开发用例，并宣布他们将识别和开发用例。

串流媒体客户服务推动生成式人工智慧市场成长

生成式人工智慧改变印度保险市场的客户服务体验。这将为所有保单持有人带来更好的控制和个人化体验。使用自然语言处理和机器学习演算法，人工智慧聊天机器人可以模拟人类对话，获取有关客户询问的知识，并即时提供准确的解决方案。预计这将增强整体互动，减少人工中介的工作量，并使他们能够更有效地解决复杂问题。此外，生成式人工智慧将能够处理大量资料以找到提供客製化建议的模式，确保根据每个客户的要求和偏好推荐客製化的行动方案。随着科技的不断发展，生成式人工智慧将促进从保单选择到理赔管理的保险流程，创造更令人满意的客户体验，进而提高对印度保险公司的忠诚度。

2024年 1月，Bharti Enterprises 和 AXA 的合资企业 Bharti AXA General Insurance 推出了生成式 AI 聊天机器人，为客户询问提供个人化且及时的答覆。

增强的风险评估和诈欺侦测推动成长

生成式人工智慧模型可以增强模拟和估计与保险领域相关的风险的能力。人工智慧模型可以根据过去的资料产生各种场景。这使得保险公司能够更佳了解各种风险的可能性和潜在影响。这有助于保险公司在确定适当的保费时做出明智的决定。透过运行各种风险场景并使用该信息，保险公司可以调整事件的机率和严重程度，使其更加合适。它帮助保险公司管理自己的风险，同时确保客户公平、准确地收取代表实际保险成本的保费。生成式人工智慧在保险领域的应用展示瞭如何利用先进技术更佳管理风险并改善客户体验，提高保险业的弹性。

本报告研究和分析了印度保险生成式人工智慧市场，提供市场规模和预测、市场动态、主要参与者的现状和前景等。

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

简介目录图表

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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印度保险生成式人工智慧市场评估：依部署、技术、应用、地区、机会、预测（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

目录

第1章专案范围与定义

第2章研究方法

第3章执行摘要

第4章顾客回馈

第5章印度生成式人工智慧保险市场展望（2018 财政年度-2032 财政年度）

第6章供需分析

第7章价值链分析

第8章波特五力分析

第9章 PESTLE分析

第10章订阅成本分析

第11章市场动态

第12章市场趋势与发展

第13章案例研究

第14章竞争态势

第15章策略建议

第16章关于本公司，免责声明

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

印度保险生成式人工智慧市场评估：依部署、技术、应用、地区、机会、预测（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

目录

第1章 专案范围与定义

第2章 研究方法

第3章 执行摘要

第4章 顾客回馈

第5章 印度生成式人工智慧保险市场展望（2018 财政年度-2032 财政年度）

第6章 供需分析

第7章 价值链分析

第8章 波特五力分析

第9章 PESTLE分析

第10章 订阅成本分析

第11章 市场动态

第12章 市场趋势与发展

第13章 案例研究

第14章 竞争态势

第15章 策略建议

第16章 关于本公司，免责声明

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章专案范围与定义

第2章研究方法

第3章执行摘要

第4章顾客回馈

第5章印度生成式人工智慧保险市场展望（2018 财政年度-2032 财政年度）

第6章供需分析

第7章价值链分析

第8章波特五力分析

第10章订阅成本分析

第11章市场动态

第12章市场趋势与发展

第13章案例研究

第14章竞争态势

第15章策略建议

第16章关于本公司，免责声明