Automated Underwriting, Risk assessment & Fraud Detection

Artificial intelligence (AI) is reshaping the insurance industry, revolutionising the way companies operate and interact with customers. As a cornerstone of financial services, insurers are increasingly leveraging AI to streamline operations, minimise risks, and enhance customer experiences. From underwriting and fraud detection to claims processing and tailored policies, AI is transforming traditional business models. Financial institutions collaborating with insurers,  including banks and investment firms, are also reaping the benefits of AI-powered risk management and predictive analytics. This first article of the series written by LHoFT Research examines AI’s growing influence on the insurance sector, focusing on two key areas: Automated underwriting and risk assessment, and fraud detection and prevention.

Section 1 – Automated Underwriting & Risk Assessment

• Using AI for richer risk data: Insurers are deploying machine learning models to augment underwriting with non-traditional data sources. Modern “accelerated underwriting” systems in life insurance, for example, now analyse applicants’ credit attributes, prescription drug histories, motor vehicle records, public records, wearable device metrics, and even social media activity​. By quickly sifting these vast data sets, AI can paint a more granular risk profile, though regulators caution that such complex models could inadvertently introduce bias or unfair discrimination if not properly managed^[1]​.
• Speed and accuracy gains: AI-driven underwriting platforms dramatically cut decision times and improve consistency. Allianz reported that AI reduced its average policy underwriting time from 3-5 days to about 12 minutes while maintaining a 99.3% accuracy rate in risk assessment​. These models “digitise” risk information from disparate sources (financial records, driving data, etc.) into a format that algorithms can triage, allowing underwriters to focus on exceptions​. In practice, over 380 insurance companies now rely on AI-based underwriting as a “second set of eyes,” and firms like Allianz have even introduced an AI virtual assistant to guide underwriters in real time^[2]​.
• Industry adoption: Even the most traditional insurers are embracing AI for risk selection. In 2023, Hiscox, the specialist global insurer, partnered with a major tech company to build an AI-enhanced underwriting model to help underwriters evaluate risks more dynamically^[3]​. This trend reflects a wider industry push to boost underwriting efficiency and predictive power through AI while maintaining compliance with evolving guidelines on data privacy and fairness.

Section 2 – Fraud Detection & Prevention

• AI spotting anomalies in claims: To combat insurance fraud (which experts estimate may affect up to 1 in 10 claims)​, carriers are investing heavily in AI-powered fraud analytics. Global insurer Zurich, for instance, uses machine-learning models to flag anomalous claim patterns in real-time, alongside its traditional rule-based engines​. This AI-driven approach has paid off: Zurich’s UK unit reported preventing £78.5 million in bogus claims in 2023 (over £200k per day)​^[4]. Across the industry, about 60% of insurers now use AI/ML tech for fraud detection^[5]​, freeing up human investigators to focus on the most suspicious cases.
• Battling deepfakes and digital fraud: As fraudsters turn to AI-generated deceptions (doctored documents, “deepfake” accident photos, and so on), insurers are responding in kind. Industry analysts note a rise in AI-assisted insurance fraud attempts (“shallow fakes”), especially in auto claims​. Carriers began deploying new GenAI tools to detect telltale signs of manipulated images or text. According to Gallagher Re, generative AI can readily identify AI-fabricated content in claims, helping insurers catch these scams before payout​^[6]. Insurers are also using AI to monitor customer interactions (e.g. NLP analysis of claim chats or calls) for red flags, further improving fraud interception rates. The arms race is ongoing, but AI gives insurers a growing edge in spotting fraudulent claims early and preventing losses.

Conclusion

The integration of AI into underwriting, risk assessment, and fraud detection is not just an evolution; it is a fundamental shift in how insurers operate. As AI continues to refine decision-making, enhance efficiency, and combat fraud, insurers must balance innovation with ethical considerations, regulatory compliance, and data privacy. The rapid adoption of AI-driven solutions signals a future where insurance is not only faster and more accurate but also more personalised and secure.

For industry leaders, now is the time to invest in AI capabilities, collaborate with technology partners, and adapt to the changing landscape. Those who embrace AI strategically will gain a competitive edge, while those who hesitate risk being left behind. Join us for the next article in this series, where we explore how insurers are leveraging AI for claims processing, automation, personalised policies, and dynamic pricing. How will your organisation harness AI to stay ahead? The conversation is just beginning.

 

Notes:

^[1] NAIC Accelerated Underwriting (A) Working Group Ad Hoc Drafting Subgroup (June 3, 2024) “Regulatory Guidance and Considerations”

^[2] J.P. Pressley (March 4, 2025) “How Artificial Intelligence Is Transforming the Insurance Underwriting Process”

^[3] Hiscox (December 12, 2023) “Hiscox and Google Cloud Collaborate on AI in lead underwriting for the London Market”

^[4] Alice Ratcliffe (August 20, 2024) “AI poses challenges, offers tantalizing solutions to insurers fighting fraud”

^[5] Amanda Paule (Oct 24, 2023) “Insurance companies are betting on AI and mass data analytics in a battle against fraud that costs billions”

^[6] Gallagher Re (February 2024) “Beyond the Hype: 5 Trends in Generative AI and Insurance”