AI Applications in Corporate Fraud Investigations

Mastercard's recent integration of GenAI into its Fraud platform, Decision Intelligence Pro, has caught my attention. The results are impressive and shows the potential of “GenAI in Advanced Business Applications”. As someone who follows AI advancements in Fraud across the FSI industry, this news is genuinely exciting. The transformative capabilities of GenAI in fortifying consumer protection against evolving financial fraud threats showcase the potential impact of this integration for improving the robustness of AI models detecting fraud. The financial services sector faces an escalating threat from fraud, including evolving cyber threats that pose significant challenges. A recent study by Juniper Research forecasts global cumulative merchant losses exceeding $343 billion due to online payment fraud between 2023 and 2027. Mastercard's groundbreaking approach to fraud prevention with GenAI integrated Decision Intelligence Pro is revolutionary. - Processing a staggering 143 billion transactions annually, DI Pro conducts real-time scrutiny of an unprecedented one trillion data points, enabling rapid fraud detection in just 50 milliseconds. - This innovation results in an average 20% increase in fraud detection rates, reaching up to 300% improvement in specific instances. As we consider strategic imperatives for AI advancement in fraud, this news suggests what future AI models must prioritize: - Rapid analysis of vast datasets in real-time, maintain agility to counter emerging fraudulent tactics effectively, and assess relationships between entities in a transaction. - By adopting a proactive approach, AI systems should anticipate and deflect potential fraudulent events, evolving and learning from emerging threats to bolster security. - Addressing the challenge of false positives by evolving AI models capable of accurately distinguishing legitimate transactions from fraudulent ones is vital to enhancing overall security accuracy. - Committing to continuous innovation embracing AI is essential to maintaining a secure and trustworthy financial ecosystem. #artificialintelligence #technology #innovation

👁 Soon enterprise solution architects will be able to design complex System-Knowledge-Human-AI system for any existing enterprise use cases. In the below fraud detection & prevention use case in financial services, we designed four AI Agents interacting with human, systems, and knowledge : 1️⃣ AI Agent #1: Pattern Recognition Agent Role: Accelerate fraudulent activity identification for analysts. Knowledge & Memory: Fraud patterns and user behavior knowledge. Integrated Systems: Interfaces with transaction monitoring systems. Specificities: Specializes in real-time pattern and anomaly detection. 2️⃣ AI Agent #2: Investigation Assistant Agent Role: Supports analysts in verifying flagged transactions. Knowledge & Memory: Transaction history and known fraud methods. Integrated Systems: Taps into core banking and digital platforms. Specificities: Extracts data, provides context, and assesses risk. 3️⃣ AI Agent #3: Resolution Suggestion Agent Role: Proposes solutions for confirmed fraud cases. Knowledge & Memory: Past resolutions and related outcomes. Integrated Systems: Connects to incident management and customer platforms. Specificities: Analyzes scenarios, assesses impacts, and recommends actions. 4️⃣ AI Agent #4: Fraud Prevention Education Agent Role: Educates on fraud prevention. Knowledge & Memory: Fraud tactics and effective prevention methods. Integrated Systems: Works with customer channels, internal learning systems, or knowledge management systems. Specificities: Curates personalized content, updates dynamically, and nudges behavior. #llm #generativeai #multiagents

Artificial intelligence (AI) has transformed banking in both positive and negative ways, enabling more personalized customer service and a more efficient workplace, but also opening new avenues for cyberattacks and fraud. 🛡️ As a result, the banking sector faces a growing challenge of combating complex and advanced threats and increasingly sophisticated scams. 😨 McAfee's 2024 predictions underscore the looming threat, with AI taking center stage as cybercriminals harness the technology’s capabilities for dangerous deepfakes and identity theft. 😱 These concerns reflect a surge in misuse of AI, with the Sumsub Identity Fraud Report highlighting a 10x increase in deepfakes detected globally from 2022 to 2023. 📈 AI solutions can help combat fraud when customers are directly targeted in scams by enhancing accuracy, reducing investigations and mitigating compliance risk. 🙌   Many banks leverage AI for fraud prevention, expediting case resolutions and enabling focused attention on complex issues. 💯 For instance, a regional US bank employs custom and third-party machine learning solutions to combat fraud. Additionally, a leading payments card network introduced a new Generative AI model, enhancing banks' fraud detection rates by up to 300%. 🚀   Yet, the best defense lies in collaboration. 🤝 Industry-wide cooperation can enable the discovery of previously hidden data relationships to combat emerging fraud methods effectively. Additionally, sharing fraud indicators across FS firms, without revealing identifying customer attributes, can pave the way for more robust fraud prevention networks. 🔗   In this critical juncture, advanced AI techniques, collaborative efforts and fraud data sharing networks are imperative to combat the looming threat of AI-based fraud effectively. It's a necessity to safeguard financial systems, preserve trust in the digital age and create #longtermvalue. 💎   #AI #FraudPrevention #Cybersecurity #Deepfakes #IdentityTheft #GenAI #DataSharing #Collaboration   https://lnkd.in/gdwffnrp