Core Concepts

\<font color="#78b5c7">\</font> topic type concept purpose explain how evaluates fraud risk across events, time, and customer behavior audience api integrators and client developers applies to applies to all apis involved in fraud detection and risk assessment does not apply to does not apply to data privacy apis, which exist solely to support regulatory requirements the event model at the center of ’s risk intelligence is an event an event represents a specific customer action, transaction, or claim submitted for evaluation at a particular moment in time depending on the api, an event may represent a login attempt, a purchase, a return, a dispute, or another fraud‑relevant action while each api request describes a single event, fraud evaluation does not occur in isolation every event is evaluated within a broader analytical context informed by historical data, industry‑specific patterns, and global fraud activity observed across the what an event represents a fraud event captures the immediate details of a transaction, including the action or transaction being evaluated the customer, account, or identity involved the merchant or client context the device, payment method, or channel the timing and surrounding circumstances this event data provides the current snapshot needed to perform evaluation, but it is only one input into the overall decision making process how events are evaluated risk evaluation incorporates multiple layers of context beyond the individual event, including historical customer behavior patterns associated with the customer or account over time, where applicable client‑specific history observed transaction behavior, fraud outcomes, and risk characteristics associated with the client submitting the event industry‑specific intelligence long‑term fraud patterns and behaviors observed within the relevant industry, reflecting how fraud manifests differently across sectors such as air, retail, travel, ticketing, and theme parks global and real‑time fraud trends signals derived from fraud activity occurring across the platform, including emerging patterns that may be developing at the moment the event is evaluated the submitted event is therefore evaluated as part of a continuum of observed behavior , not as a standalone occurrence why this model matters fraud is inherently adaptive risk signals that were reliable in the past may change as fraud techniques evolve, and patterns that appear safe in isolation may indicate elevated risk when viewed in aggregate by combining pre‑transaction signals ( ) transaction signals ( apis) post‑transaction signals ( , ) cross‑event intelligence ( ) the apis provide risk evaluation that reflects both long‑term trends and current conditions across a customer's journey this approach allows decisions to incorporate context that cannot be captured by a single event alone, while still enabling real‑time integration at the point where decisions must be made the role of the api request the api request supplies the event‑level data required for evaluation it does not attempt to replicate or expose the full historical dataset or analytical processes used by the instead, it provides the necessary context for to correlate the event with historical and industry‑level intelligence, apply fraud detection logic informed by ongoing trends, and return a decision that reflects the broader risk landscape see also getting started docid\ mff0kez4dg0xsdeld1tae introduce the apis and their role within the global constraints docid\ hxd7wt2raxtw6nh2h3yn0 authentication methods, hashing requirements, and other api parameters api reference page docid 40scz3hvgitth6c2i6jja field definitions and requirements for every api