In an era of increasing digital transactions and complex financial operations, traditional methods of fraud detection are no longer sufficient. Leveraging AI for Proactive Fraud Detection in Finance is a comprehensive, hands-on session designed for finance professionals, auditors, risk managers, and compliance officers who want to stay ahead of fraud using the power of artificial intelligence.

Rather than reacting to fraud after the fact, this session focuses on how AI can be used to detect anomalies, flag suspicious activity, and strengthen internal controls in real-time, significantly reducing risk and financial loss.

In this session, you will learn how to:

Understand the types of financial fraud most susceptible to AI-driven detection, such as payment fraud, expense manipulation, and invoice tampering.

Use machine learning algorithms to analyze large volumes of financial data and identify patterns indicative of fraud.

Implement anomaly detection models that flag unusual transactions and behavior across accounts and departments.

Integrate AI with your existing ERP, accounting software, and audit systems to enhance fraud monitoring.

Leverage natural language processing (NLP) to scan emails, contracts, and communications for early signs of collusion or policy violations.

Set up automated workflows that escalate red flags and reduce manual oversight burdens.

The session will highlight no-code and low-code tools that allow finance and audit teams to apply AI without technical expertise, using intuitive dashboards, pre-built models, and simple automation logic.

Real-world case studies will demonstrate how leading organizations have reduced fraud exposure, enhanced compliance, and created a culture of proactive risk management by adopting AI-powered detection systems.

By the end of this session, you’ll be equipped with a practical roadmap to begin integrating AI into your organization’s fraud detection strategy, helping you move from reactive investigations to preventive action, safeguarding both financial assets and reputation.