AI in Financial Crime Prevention
Since 2018, we've been at the forefront of using supervised AI models for fraud prevention in Financial Crime Prevention (FCP). Our advanced models analyze complex data inputs in real-time to block suspicious transactions effectively.
Key to this process are Profiles—sophisticated data constructs created using expert knowledge of fraud scenarios. These Profiles not only enhance the performance of our AI models but also ensure they remain transparent and explainable.
Trust in our innovative approach to keep your financial transactions secure and fraud-free. Discover the future of financial crime prevention with us.
AI in Fraud Detection
Fraud is categorized into:
- Card Fraud: The theft of physical cards or card information.
- Account Fraud: Identity theft involving the stealing of personal information.
One key advantage in fighting fraud is the presence of victim reports. Since fraud victims typically report the crime, supervised AI models can be effectively trained on these reported cases accurately identify and prevent similar incidents. This allows us to accurately identify and prevent similar fraudulent activities, ensuring better protection for your financial assets. Due to their reporting nature, fraud cases are well-suited for supervised AI models.
AI in Anti-Money Laundering
In contrast, Money Laundering operates under a veil of secrecy. Money launderers do not report their activities, making detection much more complex. Unlike fraud, ML cannot be tackled using only supervised AI techniques.
To effectively combat ML, we utilize a combination of unsupervised learning and generative AI (GenAI). These advanced techniques allow us to detect hidden patterns and anomalies, even in the absence of explicitly labeled data. This robust approach enables us to uncover sophisticated ML schemes that traditional methods would miss.
At our company, we harness the power of AI to provide comprehensive, cutting-edge solutions for detecting and preventing financial crimes. Join us in making financial ecosystems safer and more secure for everyone.
Leader of the Financial Crime Prevention AI Team
Insights
Using AI in Fraud Detection
Supervised AI models, trained on both fraudulent and normal transactions, play a crucial role in identifying and blocking suspicious activities. These models analyze accompanying data to make informed decisions about whether to block a transaction. However, the reasoning behind these decisions is often complex and requires a robust and interpretable approach.
Profiles
By transforming and combining raw data, we create comprehensive Profiles built on expert knowledge. These Profiles enhance the model's ability to generalize and detect fraud effectively, while maintaining interpretability for better decision-making and transparency in blocking transactions.
Our Solution: Profile-Based Detection
Rather than relying solely on AI, we use expert-driven profile creation. By transforming and combining raw data, we build comprehensive profiles that detect fraudulent patterns across extensive datasets. This method ensures accurate and transparent fraud detection. Experience the future of secure financial transactions with our blend of AI precision and expert knowledge. Explore our solutions today!
Fraud prevention suiteComing soon: Argus Large Financial Model (LFM)
Tietoevry Bankings Financial Crime Prevention unit has designed, built, and trained our own generative model, the Atlas Large Financial Model (LFM). Using a public money laundering dataset from IBM, Atlas outperforms state-of-the-art models by over 60%. We are preparing to launch the Atlas API and AI Explore powered by Argus.