Learning Objectives:

  • Understand the role of AI in fraud detection and cyber risk management.

  • Explain emerging cybercrime risks related to AI: adversarial AI, deepfake fraud, phishing, synthetic identities.

  • Apply AI risk management strategies and frameworks.

6.1 AI in Fraud Detection

The Amrita course covers “Fraud detection in banking, insurance, and digital payments” . The NobleProg course covers “Fraud detection, and anomaly detection” . The SIBM Nagpur course requires students to “assess fraud risk in banking and financial service” .

Key Applications of AI in Fraud Detection:

  • Anomaly Detection: The NobleProg course covers “anomaly detection” . Identifying unusual transactions and patterns.

  • Real-Time Monitoring: AI-powered systems that monitor transactions in real-time.

  • Pattern Recognition: The House of Training course covers “Examples of FinTech firms” and “Promises & pitfalls of Data Analytics” .

  • Behavioural Analytics: Analysing customer behaviour to detect anomalies.

6.2 Emerging Cybercrime Risks

The NUS course covers “Emerging AI-related cyber crime risks, including adversarial AI, deep fake fraud, phishing, synthetic identities, etc.” . The STEP course notes that applications include “facial recognition” but also raises questions about “ethical, accountable and transparent” AI use .

Key Risks:

  • Adversarial AI: Attacks that manipulate AI systems. The NUS course identifies “adversarial AI” as an emerging risk .

  • Deepfake Fraud: Using AI-generated content to impersonate individuals. The NUS course identifies “deep fake fraud” as a risk .

  • Phishing: Fraudulent attempts to obtain sensitive information.

  • Synthetic Identities: Fraudsters creating fake identities using a combination of real and fabricated information. The NUS course identifies “synthetic identities” as a risk .

6.3 AI Risk Management Strategies

The NUS course covers “Understanding of and strategies, frameworks, and tools in managing AI Risks” . The NobleProg course covers “Ethics and Compliance – Ethical considerations of using Big Data and AI in banking. Navigating compliance and regulatory challenges” .

Key Strategies:

  • Risk Assessment: The NobleProg course covers “Risk assessment, fraud detection, and anomaly detection” .

  • Governance Frameworks: The NobleProg course covers “Managing data quality, security, and governance” .

  • Regulatory Compliance: The NobleProg course covers “Navigating compliance and regulatory challenges” .

  • Incident Response: Having a plan to respond to cyber incidents.

Key Frameworks:

  • AI Governance: Establishing policies and procedures for AI development and deployment.

  • Model Risk Management: The NobleProg course covers “Building predictive models for bank examination” .

  • Data Protection: Adhering to data protection regulations.

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