Which of the following applications would NOT be considered an OLTP application?

Fraud detection systems analyze large volumes of past transactions using complex pattern-matching, statistical models, and multi-dimensional queries to identify anomalies - characteristics of OLAP, not OLTP. OLTP applications are defined by high-volume, short-duration, atomic transactions such as inserts and updates, whereas fraud detection requires heavy read-intensive analytical processing that is incompatible with the OLTP model.

A badge reader records individual access events as simple, discrete insert transactions with minimal processing, fitting the high-volume, low-complexity definition of OLTP.

An eCommerce site continuously processes orders, payments, and inventory updates as atomic transactions requiring high concurrency and data integrity, which are the defining traits of OLTP.

A stock-trading site executes buy and sell orders as real-time atomic transactions requiring high throughput and strict consistency guarantees, making it a classic OLTP application.