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Solomon Philip is Shift Technology’s Head of Market Intelligence

In technological innovation, where every advancement brings new opportunities, a darker underbelly often waits to exploit those advancements. Generative Artificial Intelligence (AI) has emerged as a powerful tool with numerous positive applications, but it's essential to acknowledge its potential misuse by bad actors. In this article, we delve into the unsettling world where the capabilities of AI, exemplified by ChatGPT, are harnessed for malicious intent. We shall also see how partnering with experts in the AI space, using GenAI for good, can be used to combat nefarious uses of this technology. 

Use-Cases for Bad Actors
The flexibility and sophistication of Generative AI-created content make it an ideal candidate for various nefarious activities. Bad actors have found creative ways to exploit AI for their gain, including

  • Constructing Fake Identities:
    Generative AI's sophistication allows malicious actors to fabricate compelling yet entirely fictional identities, a tool increasingly exploited for insurance fraud. In this context, a fraudster might use Generative AI to create a deceptive identity, leveraging details from multiple social media profiles or stealing personal information from unsuspecting victims, such as Social Security Numbers. The fabricated identity could involve manufacturing details of deceased individuals, exploiting the lack of vigilance in the aftermath of a tragedy. This fraudulent identity is then strategically employed to submit bogus insurance claims, utilizing the credibility established by amalgamating stolen or manufactured details. To counteract this evolving threat, the insurance industry must enhance detection mechanisms that distinguish between genuine and artificially generated identities, thereby fortifying defenses against deceptive practices aiming to manipulate insurance processes for illicit gains.

  • Fabricating Police Reports and Witness Statements: Generative AI's sophistication facilitates insurance fraud by crafting intricate fake documentation and evidence, including authentic-looking police reports and witness statements. Malicious actors can leverage Generative AI to replicate human handwriting and fabricate convincing accident images at recognizable locations, complete with nuanced details like weather conditions. This elaborate deception heightens the credibility of fraudulent claims. In the realm of crime, Generative AI is exploited to create forged legal documents, posing severe consequences for the justice system and potential wrongful convictions. Notably, manipulated images, such as those depicting a Pentagon explosion that impacted the stock market or the Pope in a Balenciaga coat, underscore society's struggle with the dark implications of Generative AI misuse. Due to the profound legal and financial repercussions, the insurance industry must fortify defenses against such deceptive practices.

  • Manufacturing Real-Looking but Fake Invoices and Medical Reports: In health insurance, the rising threat of financial and medical fraud is compounded by the malevolent use of Generative AI. Bad actors exploit this technology and create deceptive health documents, such as convincing medical reports detailing fictitious diagnoses. For instance, a fraudster may generate a misleading report suggesting the need for an expensive procedure, leading to illegitimate insurance claims and financial strain on healthcare providers. Generative AI can also create fabricated invoices, contributing to inflated claim amounts and disrupting the financial ecosystem of health insurance providers. The technology becomes a tool for systematically orchestrating medical scams and submitting fraudulent claims. The urgency for the health insurance industry lies in enhancing detection mechanisms to differentiate between authentic and fabricated documents, which is crucial for protecting against the disruptive and costly impact of fraudulent activities.

  • Spam Applications to Infiltrate Policy Fraud Systems: Spam applications inundate systems designed to provide genuine assistance to those in need. By deploying Generative AI-created content in applications, malicious actors can congest these systems, making it challenging for those who legitimately require aid to access it promptly.  If Ghost broking rings can hit an insurer with 10s to 100s of new policies, imagine how many more applications a tool like Generative AI can do and at what severity. The velocity of fraud is bound to increase, which will, in turn, drive volumes and, together, the severity of impact on an insurer's business.

How AI Can be Utilized to Detect These Schemes
As the capabilities of Generative AI for malicious activities increase, so must the efforts to counteract them. Several strategies can be employed:

  • Document Fraud Detection Capabilities: AI can be trained to recognize patterns consistent with fake documents. Document fraud detection algorithms can analyze minute details such as font irregularities, image manipulations, and inconsistencies in formatting to identify potential forgeries. Metadata changes and incongruencies can be detected by AI-infused document fraud detection capabilities that go beyond human expertise and skills. For example, an insurance company implementing AI-driven document fraud detection may uncover a fabricated medical report during a claim submission. The system could identify document layout inconsistencies, font usage, and metadata, helping insurers prevent a potentially fraudulent claim.

  • External Data to Efficiently Flag Incongruencies: Integrating external data sources into fraud detection systems can enhance their effectiveness. Cross-referencing AI-generated content with established databases helps identify unnoticed inconsistencies and contradictions. For example, consider a fraudster attempting to file an auto insurance claim with a fabricated identity. Using information available on social media, they create a fake driver's license and submit a claim for a staged accident. However, an insurance company employing AI-enhanced fraud detection cross-references the submitted documents with external databases. The AI system quickly detects incongruencies between the purported driver's license information and official records, triggering an alert for further investigation. This proactive approach prevents processing a potentially fraudulent claim, safeguarding the insurer from financial losses.

  • Real-Time Detection of Bot-generated Applications: Real-time monitoring is crucial to combat the automated submission of fraudulent applications via bots.  Insurance companies employing real-time AI monitoring are better prepared to notice a sudden surge in online policy applications. By rapidly detecting unusual patterns and behaviors, the system can identify attempts to flood the insurer's system with fake policies. This timely intervention prevents the escalation of policy fraud and protects the insurer's resources.

The Need for Skilled AI Partnerships
In the battle against AI-fueled malice, carriers must recognize the need for strong partnerships with AI experts. Here's why:

  • Expertise in AI Technology: Effectively countering the adverse impacts of Generative AI misuse in insurance demands a comprehensive understanding of technology, including Optical Character Recognition (OCR) and Natural Language Processing (NLP). AI experts are pivotal in identifying vulnerabilities and developing proactive strategies against human and machine-driven fraud. As scams via Generative AI become globally accessible, the need for OCR and NLP expertise heightens. The ability of AI scenarios to access popular schemes accelerates their learning, enabling adept detection of patterns used by Generative AI. Leveraging network detection capabilities is crucial in uncovering massive underground operations and detecting criminal rings with the skills and funding for malicious Generative AI use. The collaboration of AI experts, alongside advanced network detection, empowers insurance providers to implement robust detection mechanisms, staying ahead of evolving tactics, protecting against the costly consequences of fraudulent activities, and securing the integrity of insurance processes.

  • Customization for Specific Threats: Generative AI-based threats, encompassing health insurance scams, potential fraud in the auto industry, and region-specific schemes like those witnessed in Florida post-hurricanes or California's wildfire-related fraud, are diverse and continually evolving. Learning lessons from typical Generative AI images used to defraud insurers, such as those that appeared after an earthquake in Japan, becomes pivotal in detecting potential fraud schemes expected after an earthquake in the US. An AI partner's expertise is crucial in calibrating detection mechanisms tailored to specific threats deployed by bad actors. This ensures a more targeted and effective defense against evolving tactics, protecting against the multifaceted challenges presented by the constantly changing landscape of fraudulent activities.

  • Continuous Adaptation: Malicious actors will continue to refine their tactics as AI technology evolves. The constant calibration and tuning of scenarios to keep up with the evolution of Generative AI can be challenging for insurers to manage independently. This necessity for constant adaptation is compounded by legal and regulatory changes, shifts in customer perception and sensitivities, nuanced handling of cases due to geo-political shifts, and, of course, the relentless evolution of technology. Partnering with AI experts, especially an AI vendor steeped in the fraud business, becomes crucial. Such a vendor can easily and quickly adapt and evolve defense mechanisms per the changing landscape. This ensures that organizations stay on the bleeding edge and maintain a proactive stance against new and sophisticated threats in the ever-evolving realm of Generative AI-driven malicious activities.

Conclusion
Generative AI, while a powerful tool for innovation, has the potential to be exploited by malicious actors for personal gain. The construction of fake identities, the creation of fraudulent documents, and the manipulation of various systems underscore the urgency of addressing these threats. By harnessing AI for detection purposes and forming strategic partnerships with AI experts, organizations can better defend against the insidious potential of AI-driven malevolence. Only through a concerted effort can the promise of AI be fully realized without succumbing to its darker implications.

For more information about how Shift can help you adopt AI to combat ever evolving fraud schemes – contact us today