liveBook · Manning

Entity profile

As explained in Inside AI

An entity profile is a structured representation of information and behavioral history associated with a particular entity.

An entity profile is a structured, evolving record of information and behavioral history for one entity. Smart agents aggregate relevant data over time to form profiles for cardholders, stores, and merchants. section 4.1.2

Fraud prevention

A cardholder profile continuously learns from transactions, establishes a baseline of spending behavior, and helps detect deviations from that individual’s normal pattern. Personalization allows decisions tailored to the cardholder rather than generic rules. section 4.1.2

Common profiling approaches include:

  • Real-time profiling, which updates transaction counters continuously across selected time frames. section 4.1.2
  • Long-term profiling, which aggregates activity over extended periods to establish behavioral baselines. section 4.1.2
  • Recursive profiling, which tracks activity across a rolling time frame. section 4.1.2
  • Geo-location profiling, which incorporates location-related data. section 4.1.2

How Inside AI covers it

How deep it goes
Defines profiles operationally through continuously aggregated data, behavioral baselines, and multiple time-based criteria.
Examples
Uses cardholder, store, and merchant profiles within a fraud-prevention solution.
What it assumes
Requires precise goals and objective functions when designing smart-agent solutions.
What you can do after
Apply it via smart agents to detect deviations from individualized behavioral baselines.
How it connects
Connects smart agents, personalization, fraud detection, behavioral baselines, and real-time, long-term, recursive, and geo-location profiling.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Inside AI. The section links point to the parts of the book it draws on.