Risk Management

Financial services organizations have pioneered the application of AI-driven risk management. Global bank HSBC, working with vendor Ayasdi, developed an AI-enabled anti-money laundering solution. The software is designed to identify patterns within historical data that may point toward money laundering, which helps the bank stop payments before they violate regulations. Ayasdi says it identified numerous behavioral patterns related to fraud and reduced false positives by 20%. Ayasdi’s solutions are primarily based on anomaly detection technology, which is helpful for recognizing deviations from a pre-established norm. Well-trained AI algorithms can detect anomalies much faster than human analysts.

PayPal, which processes more than 1 billion online transactions a day and manages more than 450 million accounts, illustrates the power of AI to reduce fraud losses in ecommerce. PayPal’s AI-powered fraud detection system analyzes over 400 factors in real-time, including transaction history, device information, and behavioral patterns, according to SuperAGI, a provider of AI-powered sales software. By integrating AI into its fraud detection systems, PayPal has successfully reduced its fraudulent transaction rate to 0.32%, far below the 2024 average fraud rate of 3.6% reported by credit card company Capital One.

Trade publication PYMNTS says its research shows that companies embedding AI into fraud and compliance monitoring record 22% fewer false positives and 30% lower compliance costs than those relying solely on manual review.

Risk management professionals have high hopes for AI. 85% expect AI will enable them to better predict and mitigate risk and 65% report that AI has helped reduce fraud-related risks, according to market research firm Zipdo. The global AI in risk management market is expected to reach $3.4 billion by 2027, growing at a CAGR of 23%, Zipdo says.