Insurance Analytics Market

The global insurance analytics market is driven by factors such as increase in the frequency and intensity of extreme weather events, increasing penetration of technology in insurance products, growing awareness about risk management strategies among customers, and technological advancements. Increasing aging population across the globe is expected to provide opportunities for insurers to offer long-term policies with riders to protect against inflation or healthcare costs.

Growing Adoption of Insurance analytics by Insurance Providers to Boost Growth of Insurance Analytics Market

Demand for insurance analytics is on the rise as organizations are increasingly investing in advanced data analytic techniques and risk management tools to improve operational efficiency, reduce costs, and enhance customer satisfaction. By analyzing data from a variety of sources, including social media, weather patterns, and claims history, insurers can identify risk trends and develop more accurate pricing models. Insurers are also turning to analytics to improve the customer experience.

By analyzing customer data, insurers can identify common complaints and areas of dissatisfaction and take steps to address them. Additionally, insurers can gain a better understanding of customer sentiment regarding products and services by collecting and analyzing social media data.

The use of analytics is not limited to large insurers, however. In fact, many small and midsize insurers are using analytics to gain a competitive edge. By analyzing data from agent interactions, for example, these insurers can identify which agents are selling the most policies and develop marketing strategies to attract more business from these agents. The growth of the insurance analytics market is likely to continue to grow in the years ahead as insurers increasingly recognize the value of advanced data analytic techniques in helping them achieve their business goals.

Insurance Analytics Tools to Dominate Global Insurance Analytics Market

There is a wide range of tools and software that are used for insurance analytics. Some of the most common tools include data mining software, predictive modeling software, and actuarial software. Data mining software is used to analyze large data sets in order to find patterns and correlations. This information can then be used to predict future events or trends. Predictive modeling software is used to assist in predicting future events, which can then be used as a base for actuarial software. Actuarial software is a tool that can be used to calculate accurate cost projections and pricing information for proposed policies.

In insurance, data analytics tools have been implemented on the claims side of the business, but not as much on the underwriting side. However, with the ever-growing availability of data and the need to make better and faster decisions, insurers are starting to use these tools more for underwriting purposes. The goal is to improve the accuracy of risk selection and pricing, as well as identify new opportunities for growth.

There are a few challenges that arise when using insurance analytics tools. Challenges can include a lack of internal expertise or IT capabilities, maintaining data privacy and security, the struggle to choose the correct tool that will fit needs, and determining which questions should be asking in order to get the most out of analysis. However, with proper planning and support, these challenges can be overcome.

Asia Pacific’s Per Capita Income Rise to Boost Insurance Analytics Market

Insurance analytics is a part of the new-age insurance domain which uses advanced technology to aid in the decision-making process of insurance business, leading to higher revenue. The demand for insurance analytics has increased exponentially in Europe, the U.S., and Canada over last few years while it has only recently started gaining traction in Asia Pacific region.

Asia Pacific presents a highly challenging environment with some notable markets like China, India, Japan, Australia, and South Korea markets being controlled by few players. This makes it difficult for smaller players to survive or compete effectively on their own without any external help. To get around these challenges, insurance operators are increasingly choosing tie-ups with companies that can provide them innovative solutions at lower costs. This fits neatly into the agenda of data analytic companies looking out for new business opportunities in Asia Pacific region.

The growing economy of Asia Pacific shows a steady increase in per capita income with an increase in adoption of data analytic solutions. This is further driving growth of the regional insurance analytics market. Asia Pacific is a very heterogeneous market with each country having a distinct culture and preference leading to variation in demand for different kinds of analytic tools. For instance, Japanese customers are more likely to go for 'discounts' while Australian customers prefer seamless navigation functionality when it comes to electronic platforms. In order to address these varied preferences, companies need to have a clearly defined marketing strategy which would help them target the most relevant customer base.

The increasing preference for cost-effective services is leading to an increased growth of the insurance analytics market. Insurance companies from the U.S. and Europe have been using analytics to optimize their premium income stream by introducing new products, re-pricing underwritten policies, risk analysis etc. The need to gain competitive advantage over others has led many insurers to adopt innovative technology-based tools that can effectively lower costs and improve efficiencies across all functions of business. Since these tools are available on SaaS (software as a service) basis, they can be made affordable with smaller operations having access to advanced analytics tools at much lower costs than before.

Global Insurance Analytics Market: Key Players

The global insurance analytics market is dominated by a few players who offer a broad range of services including strategy development, mobile solutions, rating automation, rating enhancement through analytics & visualization, analytical tools for capital management & process improvement, business intelligence reporting capabilities at affordable prices. The other players in this market focus on providing one service or product within an insurance organization across all major lines of businesses such as life insurance, health insurance, property & casualty insurance, and reinsurance.

Some of the key players in the insurance analytics market are Oracle (US), IBM (US), Salesforce (US), Sapiens (Israel), Microsoft (US), OpenText (Canada), Verisk Analytics (US), SAP (Germany), SAS Institute (US), TIBCO (US), Vertafore (US), Qlik (US), BRIDGEi2i (US), Board International (Switzerland), MicroStrategy (US), LexisNexis Risk Solutions (US), Guidewire Software (US), WNS (India), Pegasystems (US), Hexaware Technologies (India), Applied Systems (US), InsuredMine (US), RiskVille (Ireland), ReFocus AI (US), Pentation Analytics (US), Habit Analytics (US), CyberCube (US), Artivatic.ai (India), and Arceo.ai (US).

Key Elements Included In The Study: Global Insurance Analytics Market

• Insurance Analytics Market by Product/Technology/Grade, Application/End-user, and Region
• Executive Summary (Opportunity Analysis and Key Trends)
• Historical Market Size and Estimates, Value, 2018 - 2021
• Market Value at Regional and Country Level, 2022 - 2029
• Market Dynamics and Economic Overview
• Market Size in Value, Growth Rates, and Forecast Figures, 2022 - 2029
• Competitive Intelligence with Financials, Key Developments, and Portfolio of Leading Companies 
• Regional and Product/Grade/Application/End-user Price Trends Analysis
• Value Chain and Five Force’s Analysis
• Regional/Sub-region/Country Market Size and Trend Analysis
• Company Market Share Analysis and Key Player Profiles

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• The segmentation/company profiles/countries depicted above may vary in the actual report.