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What 284,807 Credit Card Transactions Taught Me About Fraud (And About Trusting My Own Charts) I've been building a data analytics portfolio that combines my finance and accounti...
BackgroundAccording to the Communications Fraud Control Association's 2025 survey...
Most fraud detection tutorials stop at “train a model and print the accuracy.” That’s the easy 10%. The other 90% — the part that decides…Continue reading on Medium »
Built for the TigerGraph Agentic Fraud Investigation challenge (Hacker House Goa, 2026)Continue reading on Medium »
Building an XGBoost fraud detection system with feature engineering, threshold optimization, SHAP explainability, batch inference…Continue reading on Medium »
Rules, ML scoring, streams, graphs and hybrid controls solve different fraud problems. The wrong fit fails before model accuracy matters.Continue reading on Medium »
Cifas recorded 220,041 fraud-risk cases in the first half of 2026, just 1% up on the same period las...
Learn how Snowflake ML powers real-time fraud detection with the Online Feature Store (now GA), low-latency model serving and integrated MLOps — all on a single, secure platform. S...
What if we stopped thinking about fraud as simply a criminal problem and started thinking about it as a quality problem?
A payment can move between accounts before a person has time to review it. Real-time AI fraud detection helps financial institutions assess transactions as they arrive, using patte...
SEON has expanded its fraud detection platform to more than 1,100 data signals to help uncover fake identities and linked fraudulent accounts. The Signal Intelligence update increa...
AI fraud detection now hinges on data quality, not model sophistication, because fragmented data drives false positives that erode client trust.
The U.S. department has increased its scrutiny of payments using new sources of data in an attempt to stem past ‘pay and chase’ patterns.
A new report highlights the vast growth in fraudulent candidates, presenting significant insider threat challenges to organizations
The fraud risk the industry is least equipped to handle, and the payments reality most people in insurance have wrong
The fraud detection technologies used in insurance claims today center on AI-driven pattern scoring, multimodal AI for images and documents, network and social-graph analysis, natu...
A fraud ring activates at 11 PM. Your detection model starts missing transactions it would have caught three months ago. By Wednesday morning, your monitoring dashboard is red. The...
Fraud used to leave clues: a new device, an unusual IP, a login from somewhere the customer had neve...
Author: A finextra community member
Corporate finance departments are grappling with AI-enabled fraud, according to the results of a new survey by Early Warning Services’ Certos.
The U.S. Department of Justice recently launched a prosecutor-led, multi-agency team designed to investigate those defrauding federal government programs, including individuals ove...
Get to know the signs of this new form of scam that combines real and fake information to create a whole new identity. The post Synthetic identity fraud: The scam that’s fooling le...
The adapted model caught a larger share of fraudulent transaction value, a measure that can matter more than simply counting detected cases.
Every click on a digital advertisement represents a small financial transaction, and in an industry where billions of these micro-payments change hands daily, the temptation to gam...
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