보험 분석 : 시장 점유율 분석, 산업 동향 및 통계, 성장 예측(2025-2030년)

The Insurance Analytics Market size is estimated at USD 13.29 billion in 2025, and is expected to reach USD 27.80 billion by 2030, at a CAGR of 15.9% during the forecast period (2025-2030).

Companies can identify dubious claims, fraudulent activities, and behavioral patterns using predictive analytics submitted for further research. This will improve the efficiency of claims, policy, and sales processes helping in sound business decisions. For instance customer lifetime value (CLV/CLTV) tool provides the client's informative insights that enable forecasting the possibility of customer behavior and attitude, policy maintenance, or a policy surrender.

Key Highlights

• These solutions are becoming more valuable with AI and machine learning integration. Using AI in the financial sector might boost profitability rates by 31% by 2035, according to a report by Accenture. Additionally, AI will likely make it possible to give tailored financial services to clients, improving the customer experience. As a result, AI-based insurance analytics solutions can help financial organizations cut costs by billions, increase revenues by billions, and decrease fraud. Advanced Analytics (AA) increased the operating profit of the top four performers by 10 to 25 percent in EMEA. They anticipate this impact to grow over the following two years.
• With the onset of the COVID-19 crisis, structural changes brought on by turbulence, uncertainty, and weak economic activity had essential ramifications for the insurance sector. These changes compelled insurance companies to rethink how they conducted business and interacted with customers. Also, the need for digital interactions and enhanced risk management for personal and health boosted investments in digital and analytics solutions. As a result, market growth was predicted throughout the study period.
• Data reliability and security are significant due to increased connection and distant accessibility. Concerns about nefarious parties getting access to personal data are very high. Historically, insurance companies have yet to be known to make significant expenditures in infrastructure, so purchasing and maintaining pricey security software will hinder the growth of the Insurance Analytics Market.
• With the rise in competition in the insurance sector, the need for analytics solutions tends to rise to sustain stiff competition across the global market. Companies are adopting scalable & efficient solutions for managing amplified risk, dealing with catastrophes, and meeting demands of regulatory scrutiny, which are some of the significant factors that propel the adoption of insurance analytics.
• Furthermore, as consumers are inclined toward getting online quotes & customized insurance solutions 24/7 from different companies, it creates competition among industry firms. Therefore, an increase in competition is accelerating the adoption of insurance analytics among key players in the market.

Insurance Analytics Market Trends

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

• Risks from man-made and natural disasters are regularly identified and managed in the insurance sector. The need for integrated risk management, which combines knowledge, control, and optimization of routine company operations, is high due to this uncertain risk. Insurance analytics solutions provide the crucial understanding to enhance risk management at all levels.
• 86% of insurance companies are creating insurance data analytics systems to provide the most accurate predictions of big data reports. Data analytics enable unprecedented creativity across all product categories and corporate functions. For instance, instead of depending on internal data sources like loss records, auto insurance started working on behavior-based analytics and incorporating credit ratings from credit bureaus into their study.
• Due to false claims, insurance firms suffer enormous losses every year. Insurers believe that between 10% to 20% of claims are fraudulent and that less than 20% of fraudulent claims are discovered. It is possible to detect fraudulent activities, suspicious claims, and behavioral patterns using predictive analytics incorporating statistical models for efficient fraud detection.
• AI for claims fraud detection is quite beneficial since it can immediately notice patterns, allowing them to identify anomalies and suspicious requests in real-time. Businesses are using AI to speed up the entire insurance claims process and gain access to more advanced fraud detection without adding more staff or spending more money.
• The speed at which claims are settled is crucial to determining how effectively an insurance company runs. Many claim-related tasks are processed quickly, and the entire claim-settlement process is streamlined post-adoption of data analytics' excellent abilities to process and analyze huge datasets.

Asia-Pacific to Witness Highest Growth

• APAC region's insurance analytics markets are primarily driven by the increased adoption of digital infrastructure due to the growing need for customer and behavioral analytics, machine learning, and algorithm development. For instance, In India, Max Life Insurance launched a real-time analytics solution to identify false medical reports and provide relative health scores for a customer.
• Furthermore, populations in the Asia-Pacific region are becoming more urbanized, which brings all the health hazards related to a more sedentary lifestyle. This scenario will urge customers to invest in health insurance plans. Thus there is a vast opportunity for insurers to capture this newly added urban crowd, and data analytics can help study this customer base before issuing them any insurance.
• Insurance companies in the region are investing in automating processes with straight-through processing at the back end and digitally enabling distribution channels on the front end. For instance, Prudential collaborated with Google Cloud for its data analytics solution. Through this partnership, protection, health, and savings solutions will be more straightforward and accessible across Asia.
• In recent years, most Asia-Pacific markets relaxed their limitations on foreign ownership. Six of seven emerging Asia Pacific markets have permitted foreign investors to control and own a majority interest in domestic insurers.
• The laws and regulations for insurers in Asia-Pacific are constantly evolving. These regulatory improvements have focused on policyholder protection, capital preservation, and InsurTech promotion despite the varying degrees of development across various regional nations.

Insurance Analytics Industry Overview

Insurance Companies can use data analytics to learn more about client behavior and deliver customized solutions per user needs. These Analytics providers sign contracts with various companies to help them with Information Technology Software and services. As businesses shift to digital technologies, they have a wider scope of expansion. The insurance analytics market needs to be more cohesive. Players tend to invest in innovating their product offerings to cater to the insurance industry's changing demands.

• August 2023 - IBM and FGH Parent, L.P. (with its subsidiaries, "Fortitude Re") announced business has entered into a USD 450 million deal to change Fortitude Re's life insurance policy servicing operations with the implementation of AI technology and other automation tools developed to deliver a best-in-class customer experience for policyholders and insurers.
• February 2023 - LexisNexis Risk Solutions has launched LexisNexis Total Property Understanding, a new comprehensive property intelligence solution to help enable U.S. home insurance underwriters to narrow in on properties needing additional evaluation based on risk, capture complete interior, exterior, and aerial data from those properties through a consumer self-guided survey tool, and access AI-enabled insights to fast-track decision making.

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 Advanced 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