AI and preventing insurance fraud From automatic identification to compliance

AI is perhaps the most advanced tool in the fight against insurance fraud. Machine learning and generative AI can analyse large volumes of heterogeneous data (claims, social media, open data) and identify anomalous patterns that could indicate attempted fraud.

But AI is also being used to trick consumers. One example is the “ghost broker” scam. Websites and chatbots, using generative AI, simulate real agencies and produce fake policies, managing to deceive even the most experienced users.

AI-based anti-fraud systems can cross-reference historical, behavioural and biometric data, detecting anomalies in real time, such as multiple requests from different individuals with identical or similar data, false documents generated by AI or serial claims. AI also helps automate cross-checking between public and private databases, drastically reducing identification times and the risk of human error.

The most advanced applications in the field of anti-fraud include:

• Computer vision techniques to compare images of claims and validate the authenticity of the damage detected.
• Behavioural biometrics to detect inconsistencies in user interaction patterns.
• NLP (Natural Language Processing) to analyse the content of claims and identify linguistic inconsistencies that could potentially indicate fraud.
• Automatic cross-checking of medical records, testimonies and satellite data to validate the veracity of catastrophic events.

 

The role of the AI Act and the institutional response

The EU has adopted Regulation (EU) 2024/1689, known as the AI Act, to address the challenges posed by the rapid evolution of AI. The AI Act represents the cornerstone of AI regulation and governance in the internal market. The primary objective is to protect safety and fundamental rights through a risk-based approach. But the AI Act also has significant implications for the insurance sector.

Some AI systems, like those for biometric recognition, credit scoring or emotion recognition, are classified as “high risk” and have to comply with strict requirements in terms of risk assessment, transparency, traceability and human oversight. AI systems used to detect financial fraud don’t automatically fall into this category, but they could if they're integrated with other features or systems already considered high risk. This paves the way for closer scrutiny of both the tools used by insurance companies and those misused by fraudsters.

The AI Act also introduces specific rules for systems that generate synthetic content like deepfakes or realistic imitations of people, which are increasingly common in ghost broker scams and identity theft. Suppliers and users of these systems will have to ensure transparency, affix digital watermarks and provide adequate documentation, increasing the traceability of any illegal uses. Member states and competent authorities now also have to monitor high-risk systems and coordinate at European level.

These developments are an opportunity for national authorities like IVASS to take a proactive role, not only in supervising the sector, but also in preventing and suppressing AI abuse in the insurance industry. The Insurance Supervisory Authority’s reports pay close attention to attempts at fraud against policyholders.

Fraud attempts especially affect the motor vehicle liability insurance sector. It's an extremely large market, divided among many operators, many of whom operate online. But fraud attempts could affect all sectors of the insurance business, particularly those with a high incidence of serial fraud.

The Insurance Supervisory Authority hasn't yet expressed its opinion on the use of AI in systems designed to identify fraudulent situations. But the it is considering using AI for more routine activities, such as managing consumers' complaints.

Using AI skilfully and appropriately could significantly improve insurance products in general. It could encourage companies to offer services that users want. For example, assistance policies, where resources freed up in the serial and documentary management of contractual positions could be used for personal services.

This is a long process that requires an approach different from the world of services. But it seems industry regulations are already setting the path to follow by imposing a balanced cost/benefit ratio for insurance product customers.