Paypal, Inc.

Oscar Charles Edward Sanderson

Patrick Babcock

Laura Clark

Rajvijay Govindaraju

Nitin Prabhu

Yanfei Dong

Ziyuan Pan

William Lowell Conway

Jessica Tjong

Susheela Tirukavalluri

Chern Jie Lim

Systems, computer-implemented methods, apparatus, and/or computer program products that can facilitate electronic generation of enhanced, transaction-based QR codes for improved fraud detection are provided. In various aspects, a processor can receive a signal from an electronic beacon of a point-of-sale device, wherein the signal includes information associated with a first merchant. In various instances, in response to receiving the signal from the electronic beacon, the processor can identify a quick response (QR) code from a set of quick response codes that corresponds to the first merchant. In various cases, the processor can render the identified QR code on an electronic display that is scannable by the point-of-sale device, wherein scanning the identified QR code causes the point-of-sale device to transmit the identified QR code and a second merchant identifier to a payment processor. In various aspects, the processor can receive a transaction confirmation based on a verification of a transaction completed using the identified QR code from the payment processor, wherein the verification is based on determining that the identified QR code corresponds to the merchant identifier transmitted by the point-of-sale device. In various embodiments, the identified QR code can correspond to other types of verification data (e.g., geo-location stamps, time stamps, product or service identifiers, price identifiers).

QR code initiative: fraud detection

A machine learning engine may be trained using artificial intelligence techniques and used according to techniques discussed herein. While an initial electronic transaction for a resource may be permitted, a subsequent related transaction to the initial electronic transaction may be analyzed in view of additional electronic information that was not available at the time of the initial transaction. Analysis of the subsequent related transaction, using the machine learning engine, may indicate a new classification related to the resource and/or the acquisition of the resource. Based on this new classification, usage of the resource may be restricted and/or denied, and the initial transaction for the resource may even be canceled retroactively.

Machine learning engine using following link selection

Systems, computer-implemented methods, apparatus, and/or computer program products that can facilitate electronic generation and/or display of enhanced, transaction-based QR codes are provided. In various embodiments, a system can receive, from an electronic beacon of a point-of-sale device, context data characterizing a transaction facilitated by the point-of-sale device. In various instances, the system can generate a quick response (QR) code based on the context data and based on financial instrument data, such that the context data and the financial instrument data are embedded within or correlated to the QR code. In various aspects, the system can visually render the QR code on an electronic display, such that the QR code is scannable by the point-of-sale device.

QR code initiative: checkout

Systems/techniques that can facilitate video/animated QR codes are provided. In various aspects, a processor can identify a QR code. In various instances, the processor can decompose the QR code into a static fragment and a plurality of dynamic fragments. The static fragment can be a portion of the QR code that contains sufficient information to facilitate an online transaction, whereas the plurality of dynamic fragments can be a plurality of portions of the QR code that collectively contain sufficient information to facilitate an offline transaction. In various instances, the processor can sequentially render a plurality of frames on an electronic display, where each frame depicts the static fragment and a corresponding one of the plurality of dynamic fragments. Accordingly, a point-of-sale device can facilitate an online transaction by scanning one frame rendered by the processor, and/or can facilitate an offline transaction by scanning all frames rendered by the processor.

Video/animated QR codes—privacy

Systems, computer-implemented methods, apparatus, and/or computer program products that can facilitate adaptable QR codes to launch customized experiences are provided. In various embodiments, a system can receive, from a client device, a quick response (QR) code, a client identifier, and location data associated with the client device. In various aspects, the system can identify, from a plurality of merchants, a first merchant that corresponds to the QR code, based on identifying that the first merchant corresponds to the location data. In various instances, the system can identify, from a plurality of client profiles, a first client profile that corresponds to the client identifier. In various cases, the system can identify a digital content based on the first merchant and the first client profile. In various aspects, the system can cause the digital content to be provided to the client device.

Adaptable QR codes to launch customized experiences

Systems, computer-implemented methods, apparatus, and/or computer program products that can facilitate electronic generation and/or display of enhanced, transaction-based QR codes are provided. In various embodiments, a processor can store a plurality of electronic personas. In various cases, each electronic persona in the plurality of electronic personas can contain data governing electronic generation of quick response (QR) codes. In various cases, the plurality of electronic personas can respectively correspond to a plurality of privacy levels, such that each electronic persona corresponds to a different privacy level. In various aspects, the processor can, in response to a request to generate a QR code, identify a first electronic persona from the plurality of electronic personas. In various cases, the first electronic persona can correspond to a first privacy level in the plurality of privacy levels. In various instances, the processor can generate the QR code based on the first electronic persona, such that information embedded within the QR code corresponds to the first privacy level. In various aspects, the processor can render the QR code on an electronic display.

QR code initiative: privacy

Video/animated QR codes

A machine learning engine for fraud detection following link selection may be trained using artificial intelligence techniques and used according to techniques discussed herein. A buyer account may be used to establish and generate a digital gift card having a particular value specified by the buyer. The digital gift card may then be conveyed to another account, such as an email address. The digital gift card may be provided with an online electronic process for redemption and use of the value, for example, by selecting a link and navigating to the process. When the claimer account attempts to utilize the value of the gift card by navigating to the process or otherwise engaging in the electronic process through a device, a risk and fraud analysis engine may execute to determine, based on real-time data of the claimer account, the buyer account, and/or device, whether the digital gift card was generated fraudulently or is being used fraudulently.

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Singapore, Singapore

Oscar Charles Edward Sanderson