Insurance Analytics Market worth $20.6 billion by 2026
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The rising need for big data and predictive modeling capability during the COVID-19 pandemic drives the adoption of insurance analytics solutions and the rise in adoption of IoT products driving the adoption of insurance market.
Demand to reduce the time for efficient management of claims and insurance policies is expected to boost insurance companies segment to hold a larger market size
Insurance companies are the end-user companies that provide various types of insurance, such as consumer insurance (including life and health insurance, and vehicle/auto insurance) and commercial insurance (employee insurance and asset insurance for manufacturing companies). Insurance companies are now widely adopting various technology solutions, including analytics, for their internal and customer-facing services. For example, multi-line carriers that supply consumer policies — for homes, cars, and small groups — in addition to business services, such as P&C insurance, run several applications to handle underwriting, claims, and Customer Relationship Management (CRM). Increasing service demand coupled with critical end-of-year fiscal reporting forces these organizations to adopt advanced technological solutions, leading to a larger market size during the forecast period. Bajaj Allianz Life Insurance, a Pune, India-based life insurance provider, is among the leading insurers in India who are using predictive analytics across their insurance operations. The company is leveraging predictive analytics across its customer life cycle to assess customer risk, to determine the potential of a customer to renew or lapse a policy, and to act accordingly. Risk management, fraud detection, customer management, and personalization are some of the key application areas where the India-based insurer is applying analytics to improve operational efficiency, reduce cost, and enrich customer experience.
The growing demand to reduce the response time for various claims management processes and the increasing adoption of IoT insurance driving the demand for process optimization during the forecast period
Insurers are widely using analytics solutions to understand the potential risks and deploy countermeasures to mitigate losses, or at least screen, pre-empt, and assess the cost of risks in the underwriting process. Risk management involves the identification, assessment, and management of potential risks, incorporating analytics to support decision-making by clearly stating business goals and objectives, and facilitating precise information management with a better understanding of the trade-offs between risks and rewards. Risk management provides insurers with the risk capacity to maintain specific credit ratings, manage capital, and reduce earnings volatility across insurance companies.
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North America to dominate the market during the forecast period
North America is expected to dominate the global market from 2020 to 2026, owing to the presence of several solution vendors in the US. Canada has the highest internet penetration rate responsible for the growth of North America. Additionally, the presence of several vendors and favorable support environments has led to the foundation of a robust support ecosystem in the region. The increasing demand for fraud detection solutions and the rise in the requirement of on-time authentic information would drive the growth of the insurance analytics market in this region.
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The major vendors offering insurance analytics tools are IBM (US), Salesforce (US), Oracle (US), Microsoft (US), Sapiens (Israel), OpenText (Canada), SAP (Germany), Verisk Analytics (US), SAS Institute (US), Vertafore (US), TIBCO (US), Qlik (US), Board International (Switzerland), BRIDGEi2i (US), MicroStrategy (US), Guidewire Software (US), LexisNexis Risk Solutions (US), WNS (India), Hexaware Technologies (India), Pegasystems (US), Applied Systems (US), InsuredMine (US), ReFocus AI (US), RiskVille (Ireland), Pentation Analytics (US), Habit Analytics (US), Artivatic.ai (India), CyberCube (US), and Arceo.ai (US).
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