Insurance Fraud Detection

Written by
Harriet O'Connor
Aug 14, 2024
Person signing an insurance document

Insurance fraud is costing businesses and honest customers billions each year. According to The Coalition Against Insurance Fraud, fraud costs businesses and consumers $308.6 billion annually, and the FBI estimates that it costs the average family between $400 and $700 a year in premiums.

From inflated claims to fake identities, the world of insurance fraud is complex and costly, but with the power of AI, we are now more equipped than ever to fight back and tackle this challenge effectively.

In this article, we will cover the various types of insurance fraud, its impact, the legal frameworks in place, and how advanced technologies are revolutionizing insurance fraud detection.

What is insurance fraud? 

At its core, insurance fraud involves any deceitful practice intended to achieve financial gain from insurance policies. While traditional insurance fraud may have involved falsified paperwork, as the insurance industry digitalizes, fraud methods have evolved, requiring advanced technologies to combat these modern threats effectively.

The most common types of online insurance fraud are:

  • Fake accounts: Fraudsters may create bogus accounts with false information to purchase policies and file fraudulent claims. This is often done using stolen or fabricated identities to avoid detection.

  • Identity theft: Scammers use stolen personal information to obtain insurance policies and submit false claims. This can happen through phishing, hacking, or social engineering tactics to acquire sensitive data.

  • False claims: Perpetrators submit claims for incidents that never occurred, such as fake accidents or non-existent medical treatments, using online platforms to file and manage these claims.

  • Exaggerated claims: Legitimate claims are exaggerated to receive higher payouts. For instance, the severity of an accident or the extent of damage is overstated when filing claims online.

  • Ghost brokers: Fraudsters pose as insurance brokers online, selling non-existent or invalid policies through fake websites or apps, leaving victims without coverage and at financial risk.

The impact of insurance fraud

Insurance fraud has severe consequences. For individuals, it can lead to higher premiums, financial losses, and in some cases, legal action if they are unknowingly involved in fraudulent schemes. For businesses, especially online insurance platforms, fraud can significantly damage their reputation, leading to a loss of customer trust and reduced market share. Additionally, the costs associated with investigating and managing fraudulent claims can be substantial.

A notable case is the 2018 "Operation Catch-22," where a large fraud ring was busted for staging accidents and submitting false claims, costing insurers millions of dollars. This underscores the importance of robust insurance fraud detection systems to maintain the integrity and trust of online insurance services.

What are the insurance fraud laws?

Understanding the legal and regulatory frameworks surrounding insurance fraud is crucial for businesses. Around the world, strict laws and regulations are in place:

  • In the US: The Insurance Fraud Protection Act and various state-level regulations impose severe penalties on those found guilty of insurance fraud, including fines, imprisonment, and restitution orders.

  • In the UK: The Fraud Act 2006 provides the legal framework for prosecuting insurance fraud, with penalties including up to 10 years in prison, unlimited fines, and the establishment of the Insurance Fraud Enforcement Department (IFED) to tackle insurance fraud specifically.

  • In the EU: The European Union has implemented several directives and regulations to combat insurance fraud across member states. The Insurance Distribution Directive (IDD) aims to ensure fair competition and transparency in the insurance market, indirectly helping to reduce fraud. Additionally, the General Data Protection Regulation (GDPR) plays a role in protecting personal data, which is often targeted in fraudulent schemes. EUROPOL, the European Union's law enforcement agency, works with member states to investigate and prosecute cross-border insurance fraud, ensuring a coordinated effort to combat this issue.

Insurance fraud detection - how is it done?

Detecting fake accounts is crucial in combating insurance fraud. Fraudsters rarely use their real identities due to the illegal nature of their activities. Instead, they rely on fabricated or stolen identities to create accounts, purchase policies, and file fraudulent claims. Identifying these fake accounts early in the process can prevent fraud from occurring and save companies significant resources. 

AI and machine learning technologies are particularly effective in detecting these fake accounts, identifying patterns and anomalies that indicate connected fraudulent activity at scale, which is often missed by traditional methods.

  • Behavioral analysis: AI analyzes the behavior of users over time, identifying deviations from normal behavior that could indicate fraudulent intent. For example, a sudden spike in claims activity or changes in application information might be flagged for further investigation.
  • Network analysis: Fraudsters often operate in networks. AI can map relationships between different accounts and identify clusters of related activities, helping to uncover organized fraud rings.
  • Real-Time monitoring: AI systems provide continuous monitoring, allowing for the detection of emerging threats and fraudulent activities as they happen. This real-time approach ensures quicker responses and reduces the potential financial damage from fraud.

At Pasabi, we specialize in using AI to combat fraud. Our Trust & Safety Platform employs advanced AI, behavioral analytics, and cluster technology to detect non-genuine behaviors and fraudulent activities including fake accounts. 

For more information on how our AI technology can enhance your insurance fraud detection, contact Pasabi today. Together, we can build a safer and more trustworthy experience.

Up next

How to Spot a Fake Account

How to Spot a Fake Account on Your Platform

June 27, 2024

Fraud detection machine learning | Machine learning for fraud detection

The Benefits of Using Machine Learning for Fraud Detection

February 27, 2024

The Benefits of Visual Analytics for Investigation Teams

The Benefits of Visual Analytics for Investigation Teams

November 14, 2023

How to Spot a Fake Account on Your Platform

Learn how to spot a fake account on your platform, and why accurate identification requires advanced AI and behavioral analytics software.

The Benefits of Using Machine Learning for Fraud Detection

Machine learning is revolutionizing fraud detection. Stay ahead and discover how cutting-edge AI technology can safeguard your platform.

The Benefits of Visual Analytics for Investigation Teams

In the realm of Digital Trust and Safety, find out how fraud investigation and content integrity teams can benefit from visual analytics.