Amazon Technologies, Inc.

Sanjay Dash

Dilip Kumar

Hoi-Cheung Pang

Anil Reddy Musku

Lekha A Bhargavi

Daniel M Grossman

Jordan Tyler Williams

Bilyana Slavova

Smita Joshi

Jiajun Zhao

Margaret Draughon Poole

Sarath Geethakumar

Siddharth Lathia

Venkatraman Srinivasan

Biraj Gauli

Tamer Avci

Aneeta Bhattacharyya

A biometric input device is used to obtain biometric data from a user. The biometric data is used to determine host card emulation (HCE) parameters that are associated with the user and are used to access a payment account. An interface device that is associated with the biometric input device receives the HCE parameters. The interface device includes a secure execution environment (SEE). A processor in the SEE decrypts and stores the HCE parameters in the memory of the SEE and executes an HCE instance. The HCE instance uses a communication interface to interact with a payment terminal using a contactless communication protocol. The interaction provides payment data to the payment terminal, which is then sent along a payment channel for processing. The HCE instance is then erased, and the SEE is then available for use by another user for another transaction using a different payment account.

Stateless secure payment system

Features are disclosed for recognizing network-based user in a physical location. A system is provided for generating and detecting a scannable code. A time-sensitive scannable code unique to the user may be generated and presented by an electronic device such as a smartphone. The time-sensitive scannable code may be scanned at transaction terminal in the physical store. Using the scannable code, the system may securely determine that user profile information from the user's network-based activity may be provided to the transaction terminal for use in the physical location.

Secure scannable code systems and methods

A global demand forecast is generated for a product group in a computer system, where the product group comprises a plurality of products of a predefined genre. A historical relationship between an aggregate of product level demand forecasts and actual demand for the products in the product group, and the global demand forecast are used to adjust a critical ratio employed to generate a product level demand forecast in the computer system for a product in the product group. The critical ratio expresses a probability that the product level demand forecast will exceed an actual demand for a corresponding product.

Forecasting demand for products

Various embodiments of the present invention are provided to adjust a product demand forecast. In one embodiment, a value is determined of an aggregation of a plurality of product level demand forecasts for a respective plurality of products in a product group at a desired value of a critical ratio. The critical ratio expresses a probability that a forecast will exceed a demand for a given product. A ratio is determined of the aggregation of the product level demand forecasts to a global demand forecast for the product group in the computer system. The ratio is verified as to whether it is congruous with a historical ratio of past aggregate product level demand forecasts to actual product demand.

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Mercer Island, WA, United States of America

Sanjay Dash