GLOBAL INSURANCE ANALYTICS MARKET SIZE & SHARE ANALYSIS - GROWTH TRENDS & FORECASTS (2023 - 2028)


Insurance Analytics Market Analysis:

The Insurance Analytics Market achieved a valuation of USD 11.47 billion in the previous year and is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15.9%, reaching USD 27.07 billion within the next five years.

Predictive analytics can enable companies to identify dubious claims, fraudulent activities, and behavioral patterns, thereby enhancing the efficiency of claims, policy, and sales processes and facilitating sound business decisions. For instance, the customer lifetime value (CLV/CLTV) tool provides clients with informative insights that enable forecasting of customer behavior and attitude, policy maintenance, or policy surrender.

These solutions are increasingly valuable with the integration of Artificial Intelligence (AI) and machine learning. According to a report by Accenture, the use of AI in the financial sector could increase profitability rates by 31% by 2035. Furthermore, AI is likely to enable the provision of tailored financial services to clients, thereby enhancing the customer experience. Consequently, AI-based insurance analytics solutions can assist financial organizations in reducing costs by billions, increasing revenues by billions, and mitigating fraud. Advanced Analytics (AA) increased the operating profit of the top four performers by 10 to 25 percent in EMEA, with this impact expected to grow over the next two years.

The COVID-19 crisis has brought about structural changes characterized by turbulence, uncertainty, and weak economic activity, which have had significant ramifications for the insurance sector. These changes have compelled insurance companies to reconsider how they conduct business and interact with customers. Additionally, the need for digital interactions and enhanced risk management for personal and health insurance has spurred investments in digital and analytics solutions. As a result, market growth is anticipated throughout the study period.

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