HNC's founding 1992 Falcon patent names its network architecture as "feed forward"

hncfalconficofraud-detectionneural-networksfeedforwardpatentsdeep-learning-history

HNC Software's founding patent for its fraud-scoring system — U.S. Patent 5,819,226, "Fraud Detection Using Predictive Modeling," filed September 8, 1992, the same year Falcon Fraud Manager launched — describes the network architecture directly in its "Network Training" section, naming the class as a "technique known as a 'feed forward' neural network." This settles the architecture-type half of the question observation-falcon-helmholtz-inference-embedding-false-friend left open: input flows to output with no recurrent connections, ruling out a Hopfield-style, recurrent, or generative design.

The patent's own Figure 2, captioned "FALCON Monitor" (claim-us-patent-5819226-is-falcon-fraud-managers-founding-patent), ties this description specifically to the Falcon product rather than to an unrelated HNC filing. Paired with claim-hnc-1992-falcon-patent-specifies-backpropagation-gradient-descent-supervised-training (the training method) and claim-hnc-falcon-patent-describes-multilayer-not-single-layer-network (the layer structure), this discharges the [unverified-mechanism] flag question-verify-falcon-fraud-manager-neural-architecture was tracking.

Hecht-Nielsen's own name sits one layer beneath this patent too: the two works it points to for "a more detailed description of neural networks" — in the Description of the Preferred Embodiment, and incorporated by reference — are his own 1992 book chapter "Theory of the Backpropagation Neural Network," alongside Rumelhart, Hinton & Williams 1986 — the same foundational paper his own company's commercial patent leans on.