AI Could Save Insurers $160 Billion in Fraud Prevention by 2032

Deloitte report reveals how multimodal AI technologies across text, audio, video and IoT data are transforming fraud detection in the P&C sector, where 10% of claims are fraudulent.
By: | April 24, 2025
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Insurers could save from $80 billion to as much as $160 billion by 2032 after deploying AI-powered multimodal technologies to detect and prevent fraud across the claims life cycle, according to Deloitte.

Insurance fraud remains a pervasive problem in the United States, ranking as the second-most costly white-collar crime after tax evasion. The impact extends beyond insurance companies to consumers, who bear the cost through higher premiums. The Federal Bureau of Investigation reports that insurance fraud costs an average American family between $400 and $700 annually.

The property and casualty (P&C) insurance sector is particularly vulnerable, with an estimated 10% of claims being fraudulent. This results in approximately $122 billion in annual losses, representing 40% of the total fraud losses across the insurance industry.

One key factor contributing to this vulnerability is the infrequent interaction between policyholders and insurers, which typically occurs only during premium payments or claims filing, limiting companies’ ability to monitor potential fraudulent activities.

Fraud typically falls into two categories: soft and hard. Soft fraud, accounting for 60% of all incidents, involves inflating legitimate claims, such as overstating repair costs or exaggerating injuries. Hard fraud occurs when individuals take premeditated actions to create false claims, including staging accidents, committing arson, or faking theft. The prevalence of soft fraud is largely due to its difficulty to prove.

The situation has intensified since the COVID-19 pandemic, which accelerated digitization and created new opportunities for fraudsters. Simultaneously, insurers face growing customer attrition due to inflation-driven policy rate hikes, making it increasingly difficult to offset fraud losses by raising premiums further.

AI’s Transformative Potential in Fraud Detection

The fraud-detection technology industry is experiencing rapid growth, projected to expand from $4 billion in 2023 to $32 billion by 2032. This growth reflects the increasing demand for advanced solutions to combat sophisticated fraud schemes. Regulatory bodies, including The National Association of Insurance Commissioners, are also pushing insurers to implement more effective detection systems.

AI-fueled multimodal technologies represent a significant advancement in this field. These systems leverage artificial intelligence to process and integrate data from multiple sources, including text, images, audio, video, and sensor data. By analyzing diverse types of information simultaneously, these technologies can generate more comprehensive and accurate insights than traditional single-modality systems.

In a recent Deloitte survey, 35% of insurance executives identified fraud detection as one of the top five areas for developing or implementing generative AI applications over the next 12 months. These technologies are particularly beneficial in property claims and personal auto insurance segments due to their complexity, high data volume, need for real-time processing, and potential for significant cost savings.

Implementing AI Across the Fraud Detection Lifecycle

Several specific AI applications show promise in revolutionizing fraud detection across the insurance industry, according to Deloitte:

  • Text analytics: Uses natural language processing to analyze claims forms, emails, and social media posts, identifying suspicious language or inconsistencies while complying with regulations like the Colorado AI Act to avoid discrimination and bias.
  • Audio-image-video analysis: Examines customer calls for signs of duress, uncovers irregularities in photo metadata and manipulation, and verifies damage extent and image authenticity.
  • Geospatial analysis: Employs satellite images and 3D drone footage to verify damage extent and location not visible during physical inspection, reducing injury risk to claims personnel at disaster sites.
  • Internet of Things data: Utilizes vehicle telematics to reconstruct accidents and verify claims, while smart home sensors gather evidence to verify claims and detect staged activities.
  • Simulation models: Replicates behavior of medical providers, repair shops, and other entities to identify patterns and deviations from standard practices, detecting overbilling, unnecessary services, and coordinated fraudulent activities.

Over the past two decades, insurance companies have established special investigative units to detect and mitigate fraud. Moving forward, attracting and retaining skilled talent, alongside continued investment in automation, will be essential for companies to achieve their long-term anti-fraud goals, Deloitte said.

View the full report here. &

The R&I Editorial Team can be reached at [email protected].

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