Fraud is a persistent threat. With the increased use of AI, it is becoming easier for fraudsters to perpetrate crimes. From financial scams to cybersecurity breaches, fraudsters continuously evolve their tactics, making prevention more critical than ever. Effective fraud risk management is not just about detecting deception; it’s about building robust systems that minimize vulnerabilities and protect assets. In this article, we’ll explore methods of detection, the impact of AI, and preventing AI driven fraud, to help your organization can stay ahead of potential threats.
Who can commit fraud? Under the right circumstances, anyone can. Fraud takes many forms. Donald Kressy’s 1953 book, Other People’s Money: A Study in the Social Psychology of Embezzlement, introduced the fraud triangle, explaining why people commit fraud. The three elements of this triangle are Pressure, Opportunity, and Rationalization.[1]
- Pressure often comes from financial struggles such as uncontrolled debt, gambling debts, or an excessive lifestyle. It can also be caused by work-related stress, like the pressure to perform or cover up poor results.
- Opportunity is another factor contributing to explaining fraud and usually more obvious than pressure. For any organization to function, a certain level of trust must be placed in employees.
- Rationalization, the third factor, is typically a person’s excuse for committing the fraud. In many cases perpetrators tell themselves that they are only temporarily borrowing from the organization.
Over 85% of surveyed organizations have experienced Business Email Compromise (BEC). Common BEC tactics include fraudsters impersonating vendors to transfer funds based on actual invoices, third parties requesting changes to bank accounts, and spoofed emails from fake senior executives directing finance personnel to transfer.[2]
Methods of Detection: To detect fraud, organizations should implement tools such as:
- Ongoing anti-fraud training for all employees
- Effective fraud reporting mechanisms
- Proactive detection measures, such as surprise audits and data analytics
- Regular reviews of controls, processes, and transactions by managers
Defending Against Fraud: Preventing fraud requires tight financial controls. Consider these questions:
- Do you have an internal audit department or outsource to a third party?
- Are you receiving automatic exception reports on financial transactions?
- Are policies and procedures consistently applied across all business units?
- Are vendor names checked against employee databases for conflicts of interest?
The impact of AI, AI can be used in various ways to commit fraud, often by exploiting the capabilities of machine learning, automation, and data analysis. Some common methods include:
- Deepfakes (Audio/Video Manipulation) - Deepfakes can be used to create convincing fake videos or audio recordings of people, often public figures or business leaders. These deepfakes might be used to manipulate others into giving money, disclosing sensitive information, or making decisions based on fraudulent information.
- Phishing and Social Engineering - AI is used to create highly personalized phishing emails and messages that mimic legitimate communication from banks, employers, or other trusted entities. By analyzing vast amounts of data, AI can craft messages that appear extremely convincing.
- Identity Theft - AI tools can analyze vast amounts of publicly available data to generate fake identities or uncover private information about individuals. This information can be used for financial fraud, such as taking out loans in someone else's name or accessing their bank accounts.
- Automated Loan Scams - AI can be used to craft fake profiles and documents that appear legitimate to secure loans, mortgages, or credit. This method often involves generating realistic financial histories or fake assets.
- Synthetic Fraud- AI can create synthetic identities by combining real and fake data to produce a new person that doesn't exist. These identities can be used for fraudulent activities, including committing crimes and accessing financial services.
Preventing AI-driven Fraud:
- AI and Machine Learning for Detection - Using AI itself to detect unusual behavior or fraudulent patterns is one of the most effective ways to combat fraud. By training algorithms to identify anomalies, institutions can spot fraudulent activities early and stop them before significant damage occurs.
- Multi-layered Security: Implementing multi-layered security systems that combine AI detection with human oversight can help detect and prevent fraud in real-time.
- Strong Authentication Protocols: The use of strong multi-factor authentication (MFA) and biometric systems (like facial recognition or voice verification) makes it more difficult for fraudsters to use AI to break into accounts or systems.
- User Awareness: Educating individuals and organizations about the risks of AI-driven fraud, phishing scams, and identity theft can help reduce the effectiveness of these tactics.
- Regulation and Oversight: Governments and regulatory bodies are beginning to create rules and frameworks around AI to ensure that it's not used for harmful purposes. By having strict laws regarding AI usage and fraud, the impact of AI-driven fraud can be minimized.
One of the most common forms of fraud is social engineering, which includes phishing, malware, and other scams. These attacks typically follow four stages: Information gathering, Relationship development, Exploitation, and Execution.
Best Practices for Deterring Social Engineering Fraud
- Classify data to determine who has access to sensitive information and identify potential targets.
- Instruct employees and customers to never release confidential information unless necessary.
- Implement procedures for verifying incoming checks and wire transfers.
- Reduce reliance on email for financial transactions and establish call-back procedures for fund transfers.
- Provide a hotline for inquiries and emphasize which information should never be shared.
- Be cautious of unsolicited emails and avoid “rogue devices” like unauthenticated flash drives.
- Verify changes to customer or vendor information, regardless of the requester.
By implementing robust preventive measures, fostering a culture of awareness, and leveraging technology-driven solutions, organizations can stay ahead of potential threats. Fraud prevention is not a one-time effort but an ongoing commitment to safeguarding financial integrity and trust. The key to minimizing fraud risks is staying informed, adaptable, and ready to counter emerging threats before they take root.
[1]
Donald Kressy, Other People's Money: A Study in the Social Psychology of Embezzlement, 1953, Free Press.
[2]Association of Finance Professionals 2020 Payments Fraud and Control Survey Report
