using AI for security against financial fraud and crimes:
As digital finance evolves, AI is emerging as a crucial tool for combating increasingly sophisticated criminal attacks targeting banks, investment firms, insurance providers, and consumers alike. Advanced analytics, pattern recognition, and automated monitoring provide new frontiers for thwarting fraud in its many forms.
According to a McKinsey report, the rapid growth of online financial services coupled with customer preference for convenience over security has expanded the attack surface available to criminals dramatically. Security can no longer rely on walls, but intelligent systems that identify novel behavior and threats in real time.
Machine learning algorithms excel at detecting anomalies and suspicious activities within massive flows of financial data and transactions. As described by Forbes, fraud identification models can incorporate hundreds of subtle factors to pinpoint fraudulent payments, claims, applications and more with greater accuracy than rigid rule-based systems.
For example, Mastercard’s AI-powered Brighterion platform utilizes neural networks trained to recognize general patterns of deceit and specific fraudster techniques. This allows identifying risky merchants, accounts, devices, and purchases contextually. As reported by Wired, Brighterion helped reduce Mastercard losses by $50 million in just one year soon after deployment.
According to researchers from Singapore, natural language processing also aids security by extracting semantic insights from customer communications. By analyzing linguistic cues, AI chatbots and virtual assistants discern scams and fraudulent claims early before funds are compromised.
However, a report from the OECD highlights challenges around explainability. Interpretability helps instill trust when AI flags potential criminal activity. Dashboards visualizing behavior contributing toward fraud scores improves transparency and reduces mistaken fraud predictions.
The IPS notes that automating security via AI induces an arms race dynamic where criminals develop more inventive attacks to sidestep detection. Continual training, testing and improvement of algorithms is critical to counter increasingly creative social engineering, phishing and technical intrusions that prey upon the financial sector.
In summary, AI promises to bolster cybersecurity and control fraud substantially across banking, insurance and investment. But prudent governance and human-machine teaming is essential for measured adoption. When thoughtfully implemented, AI security empowers the financial system to embrace innovation while safely managing emerging risks.
References:
McKinsey – https://www.mckinsey.com/business-functions/risk-and-resilience/our-insights/fighting-banking-fraud-with-ai-and-machine-learning
Forbes – https://www.forbes.com/sites/forbestechcouncil/2018/11/14/ai-and-the-end-of-financial-fraud/?sh=a030c4f4ff55
Wired – https://www.wired.com/story/mastercard-brighterion-ai-system-fraud-detection/
Singapore Researchers – https://link.springer.com/chapter/10.1007/978-3-030-04200-4_15
OECD – http://www.oecd.org/finance/Technology-and-innovation-in-the-insurance-sector.pdf
IPS – https://www.ips-journal.eu/themes/economy/article/show/ai-in-fintech-a-game-changer-for-financial-services-4883/