From Rules to AI and Back
This article discusses the evolution of fraud prevention techniques. Fraud-prevention systems have to balance several competing demands: catching fraudulent activity without blocking legitimate customers, adapting quickly to new attack patterns, processing decisions efficiently and keeping those decisions explainable.
It covers the period from the 1970s to the present, when companies moved from rules-based approaches to relying on ML and then eventually adopted hybrid approaches. We’ll look into the main driving forces that caused each shift, the problems each new approach tried to solve and who was first to make the move.
Rules-Based Era
In 1973, Visa launched VisaNet that brought computerised authorisation, clearing and settlement to card transactions (Dee Hock — In memoriam). The system relied on static rules to prevent fraudulent transactions.
Most of rules-based systems were concerned with card-present fraud. They relied on velocity checks, geo anomalies and BIN blocklists.
Rules shined when it came to...
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