Insurance fraud detection involves the identification and prevention of fraudulent activities related to money or property insurance. It includes software-based solutions that perform statistical analysis of historical patterns and incidents to predict future occurrences using artificial intelligence (AI), machine learning, traditional rule-based fraud analytics models, etc. Insurance fraud detection is utilized across various sectors, including banking, financial services and insurance (BFSI), automotive, healthcare, retail, etc., for fraud analytics, authentication, governance, risk and compliance to safeguard databases, identifying anomalies and vulnerabilities, etc. Insurance fraud detection also detects suspicious activity by insurance providers, agents, consumers, etc., for unlawful gains during insurance buying, underwriting, or selling, of insurance.
As the novel coronavirus (COVID-19) crisis takes over the world, we are continuously tracking the changes in the markets, as well as the industry behaviours of the consumers globally and our estimates about the latest market trends and forecasts are being done after considering the impact of this pandemic.
Insurance Fraud Detection Market Trends:
The increasing occurrences of insurance fraud across industries are primarily driving the insurance fraud detection market. In line with this, the elevating product usage for identifying any evidence of cover-ups, misinterpretation of incidents, inflating the severity of the loss incurred, etc., is further augmenting the global market. Additionally, the rising incidences of customer frauds involving inaccurate claims, fake medical records, postdated laws, abductions, etc., are also bolstering the market growth. Apart from this, the expanding improvements in the cybersecurity infrastructures across the globe and the rapid digitization of the insurance sector are also acting as significant growth-inducing factors. Furthermore, the escalating utilization of artificial intelligence (AI) and the Internet of Things (IoT)-enabled fraud detection solutions by organizations to run automated business rules, self-learning models, text mining, image screening, etc., is expected to propel the insurance fraud detection market over the forecasted period.
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Insurance Fraud Detection Market 2021-2026 Analysis and Segmentation:
The competitive landscape of the market has been studied in the report with the detailed profiles of the key players operating in the market.
The report has segmented the market on the basis on type, deployment, application and vertical.
Breakup by Component:
Breakup by Deployment Model:
Breakup by Organization Size:
Breakup by Application:
Payment and Billing Fraud
Breakup by End User:
Agents and Brokers
Breakup by Region:
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Key highlights of the report:
Market Performance (2015-2020)
Market Outlook (2021- 2026)
Porter’s Five Forces Analysis
Market Drivers and Success Factors
Comprehensive Mapping of the Competitive Landscape
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