Patent Application
20180260801
Embodiments of the invention relate generally to data gathering, and more particularly, to data gathering for payment processing.
Many people have several bank accounts. A person may have a personal checking account, a personal savings account, a personal credit card, a business credit card, a joint account with another person, etc. Furthermore, some people are signers on business accounts, such as company officers and executives. Some people are signers on multiple business accounts, such as an operating account and an escrow account. Many times, things are even more complex, as sometimes these accounts are at different financial institutions. A person may desire that certain purchases come out of particular accounts. For example, a person may want her groceries to be purchased from a personal account, a bank CD purchased from a savings account, and office supplies purchased from a business account. It can be difficult to manage payments from multiple accounts. There exists a need to improve data gathering for payment processing.
In one aspect, there is provided a computer-implemented method for determining a correct account for a purchase, comprising: obtaining context information from one or more electronic information systems; determining a probability score of the purchase corresponding to an account, based on the obtained context information from the one or more electronic information systems; and associating the purchase with the account in response to the probability score exceeding a predetermined threshold.
In another aspect, there is provided an electronic device comprising: a processor; a memory coupled to the processor, the memory containing instructions, that when executed by the processor, perform the steps of: obtaining context information from one or more electronic information systems; determining a probability score of a purchase corresponding to an account, based on the obtained context information from the one or more electronic information systems; and associating the purchase with the account in response to the probability score exceeding a predetermined threshold.
In yet another aspect, there is provided a computer program product for determining a correct account for a purchase on an electronic computing device, the electronic computing device comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the electronic computing device to: obtain context information from one or more electronic information systems; determine a probability score of the purchase corresponding to an account, based on the obtained context information from the one or more electronic information systems; and associate the purchase with the account in response to the probability score exceeding a predetermined threshold.
Features of the disclosed embodiments will be more readily understood from the following detailed description of the various aspects of the invention taken in conjunction with the accompanying drawings.
The drawings are not necessarily to scale. The drawings are merely representations, not necessarily intended to portray specific parameters of the invention. The drawings are intended to depict only example embodiments of the invention, and therefore should not be considered as limiting in scope. In the drawings, like numbering may represent like elements. Furthermore, certain elements in some of the figures may be omitted, or illustrated not-to-scale, for illustrative clarity.
Disclosed embodiments provide techniques for payment processing. A purchase context is obtained by examining data from one or more electronic information systems. The electronic information systems can include, but are not limited to, social media systems, electronic calendar systems, geolocation systems, and/or image acquisition systems. Based on information from the electronic information systems(s), a probability score is computed. The probability score reflects the likelihood that a particular purchase should be associated with a particular account (e.g., a business account or a personal account). A variety of factors are used in determining the probability score. These include, but are not limited to, the date and time of an event associated with the purchase, the name of a merchant associated with the purchase, contacts with the user at the time of the purchase, and/or a geographical location at which the purchase is made. Based on these factors, a determination of which account the user should use to complete the purchase is determined. The purchase is then completed using the associated account from a mobile electronic device such as a smartphone or tablet computer. Thus, disclosed embodiments greatly simplify the management of personal and business accounts.
Reference throughout this specification to “one embodiment,” “an embodiment,” “some embodiments”, or similar language means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, appearances of the phrases “in one embodiment,” “in an embodiment,” “in some embodiments”, and similar language throughout this specification may, but do not necessarily, all refer to the same embodiment.
Moreover, the described features, structures, or characteristics of the invention may be combined in any suitable manner in one or more embodiments. It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit and scope and purpose of the invention. Thus, it is intended that the present invention cover the modifications and variations of this invention provided they come within the scope of the appended claims and their equivalents. Reference will now be made in detail to the preferred embodiments of the invention.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of this disclosure. As used herein, the singular forms “a”, “an”, and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. Furthermore, the use of the terms “a”, “an”, etc., do not denote a limitation of quantity, but rather denote the presence of at least one of the referenced items. The term “set” is intended to mean a quantity of at least one. It will be further understood that the terms “comprises” and/or “comprising”, or “includes” and/or “including”, or “has” and/or “having”, when used in this specification, specify the presence of stated features, regions, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, regions, integers, steps, operations, elements, components, and/or groups thereof.
Device 100 may further include storage 106. In embodiments, storage 106 may include one or more magnetic storage devices such as hard disk drives (HDDs). Storage 106 may include one or more solid state drives (SSDs). Any other storage device may be included instead of, or in addition to, those disclosed herein.
Device 100 may further include a user interface 108, examples of which include a liquid crystal display (LCD), a plasma display, a cathode ray tube (CRT) display, a light emitting diode (LED) display, an organic LED (OLED) display, or other suitable display technology. The user interface 108 may further include a keyboard, mouse, and/or a touch screen, incorporating a capacitive or resistive touch screen in some embodiments.
The device 100 may further include a communication interface 110. In some embodiments, the communication interface 110 may include a wireless communication interface that includes modulators, demodulators, and antennas for a variety of wireless protocols including, but not limited to, Bluetooth™, Wi-Fi, and/or cellular communication protocols for communication over a computer network.
The device 100 may further include a geolocation receiver 112. Geolocation receiver 112 may be any type of location-detecting system. For example, it may include a global positioning (satellite) system, triangulation system, or other suitable technology.
The device 100 may further include an orientation sensor 116. Orientation sensor may be an accelerometer and/or tilt sensor. Orientation sensor 116 senses and determines the orientation of the device 100. In embodiments, the orientation can be a vertical (portrait) orientation, in which the device is oriented such that it is longer in the vertical direction than in the horizontal direction. In embodiments, the orientation can be a horizontal (landscape) orientation, in which the device is oriented such that it is longer in the horizontal direction than in the vertical direction.
The device 100 may further include a camera 114. The camera can be a user-facing camera that can acquire digital images of a user. The device may encode geolocation data obtained from geolocation receiver 112 into an image header of an acquired digital image. The geolocation data may include longitude and latitude coordinates.
The device 100 may further include a fingerprint sensor 115. A fingerprint sensor is an electronic device that captures a digital image of a fingerprint pattern. The image, called a live scan, is digitally processed to produce a biometric template (a collection of extracted features) which is stored in memory for utilization in matching.
Social media system 216 and social media system 218 may each comprise instructions and memory for executing social media platforms. Social media platforms may include Facebook®, Twitter®, LinkedIn®, Instagram®, and/or any other social media platform now known or hereafter developed. For example, system 216 may include Facebook® and system 218 may include LinkedIn®. In addition, although only two social media systems are shown, in embodiments, more or fewer social media systems may be included.
Electronic calendaring system 220 may, in some embodiments, be a calendar shared among a group of people, such as a shared electronic calendar. In some embodiments, the calendar may instead be personal to the user, such as a calendaring application installed on the user's phone.
Rules engine 222 stores in memory a set of rules for assigning weights to factors based on the likelihood that the factor indicates a purchase is of a particular type of expense as opposed to another (e.g., business versus personal). In some embodiments, the rules engine 222 may be accessible to the purchase processing system 202 via network 224. In other embodiments, the rules engine 222 may be local to the purchase processing system 202.
Purchase processing system 202 includes instructions for determining from which account a purchase should be made. System 202 includes account information either entered manually from a user, or imported, for example, from a bank. Alternatively, system 202 may communicate with a payment redirection system (e.g., via an API), for example Apple Pay or Android Pay, to select the proper account based on the acquired purchase context information. When an account is stored or accessed by purchase processing system 202, it is labeled either from account metadata, or manual entry from a user, which type of account it is. For example, account types may include “business,” “personal,” “business1,” “business2,” “personal_checking,” “personal_savings,” “personal_credit_card,” “business_credit_card,” etc. If a person has two business accounts, s/he may designate a first one “business1” and a second one “business2.” If a person has a personal checking and personal savings account, s/he may designate them as “personal_checking” and “personal_savings,” respectively. Alternatively, the system 202 may associate a type from information imported from the bank, such as title of the account, signer on the account, amount in the account, etc.
In some embodiments, purchase context information includes an event date for an event. A date that falls on a weekday, such as Monday, Tuesday, Wednesday, Thursday, or Friday may indicate it is more likely a business purchase than a purchase occurring on a weekend day, such as a Saturday or Sunday. For example, if a user purchases a set of theatre tickets for June 2nd, system 202 (
In some embodiments, purchase context information includes an event time for an event. A time that falls within typical business hours may indicate that the purchase is more likely a business purchase than a personal one. For example, if the purchase is made between 9:00 a.m. and 5:00 p.m., it is more likely a business expense than a purchase made at 7:00 p.m. since many people work from 9:00 a.m. to 5:00 p.m., and are on personal time outside of that window. For example, if a user purchases a set of tickets for a show at 7:00 p.m., rules engine 222 (
In some embodiments, purchase context information includes one or more contacts associated with the event. In some embodiments, the one or more contacts are identified by a computer-implemented facial recognition process performed on an image acquired by a user device. A user may post a “selfie” to a social media site within a predetermined window prior to the purchase. Alternatively, a user may take and store such a photo in his/her phone within that time period. For example, the window may be 1 hour prior. The selfie may be taken using the user facing camera of
For example, in some embodiments, rules of rules engine 222 (
In some embodiments, purchase context information includes geographic location of the purchase based on “check-in” data. System 202 (
In some embodiments, purchase context information includes a geographic location based on information obtained using a geolocation receiver 112 of the user device. If the purchase is being made from within a predetermined geographic radius of a user's home, it is more likely a personal expense. If the purchase is being made from within a predetermined geographic radius of the user's office, the purchase is more likely a business expense. For example, if the predetermined radius is three miles, when the user makes a purchase at a coffee shop two miles from his/her home, rules engine 222 (
In some embodiments, purchase context information includes a destination associated with a purchase. For example, if the purchase is a plane ticket, train ticket, ferry ticket, etc., where data about a destination is included, such data may be captured and analyzed by system 202 (
In some embodiments, purchase context information includes a merchant identification for the purchase. The classification may be determined based on a merchant category. A merchant category can be any of a number of types of differentiators. For example, a purchase from a wholesaler is much more likely a business purchase than from a retailer. A purchase from an office supply store is more likely a business purchase than a purchase from a shoe retailer. A purchase from a grocery store is more likely a personal purchase than a purchase from a web hosting company. A purchase from a rental car agency may be given a neutral weight since a car rental may be made when a user's personal car, or business car, breaks down. Any suitable categories may be used. Rules engine 222 (
In some embodiments, purchase context is based on user attire.
In embodiments, image processing techniques can be used to determine that user 405 is wearing a necktie 407. The image processing techniques can include edge detection, gradient processing, pattern recognition, and/or other suitable techniques. In some embodiments, machine learning may be used to recognize the user's attire. In some embodiments, the machine learning can include classification using Support Vector Machine (SVM) classifiers, random forests, and/or transfer forests. In some embodiments, a convolutional neural network (CNN) system may be used for performing the image processing. The machine learning may be supervised machine learning, in which a plurality of training images are used to train the system to recognize business attire. The image processing may include a clothing type classification, where the clothing type classification may include, but is not limited to, classifications of hat, jacket, shirt, and/or necktie. This information can be used as a criterion in determining the context of the purchase and, thus, which account should be used to complete the purchase. In the example of
In some embodiments, purchase context is based on user contacts.
An example method of calculating the score includes the following. The example formula includes a scale of 100 points. A factor weight of 0 indicates a personal expense, a factor weight of 5 indicates a neutral weight, and a factor weight of 10 indicates a business expense. In some embodiments, the distance from the neutral weight can be interpreted as a confidence level. The farther the distance from neutral, the higher the confidence of a particular account association. Where exactly on the scale the weight is assigned is based on a confidence level of the weight. In embodiments, the closer to 0 or 10, the more confidence in the weight, whereas the closer to 5, the less confidence. In some embodiments, the range can be from 0 to 100, 0 to 1,000, or other suitable range. In the example, the account probability score is on a 100 scale. The threshold is 50. If the score is 50 or over, the purchase is determined to be a business expense. If the score is less than or equal to 50, it is determined to be a personal expense. In the example, there are 9 factors, and the associated assigned weights are assigned as follows:
Event date: 9
Event time: 8
One or more contacts associated with the event: 2
Check-in data: 5
Destination associated with a purchase: 8
Geographic location of the purchase: 7
Merchant identification: 3
User attire: 3
User contacts: 2
The weights are added up for a total of 47, multiplied by 100, and divided by 90 in order to fit it on a 100 scale. The resulting account probability score is 52.2. Accordingly, since the score is over the threshold of 50, it is determined that the expense is a business expense and associated with the user's business account. Note that the aforementioned calculations are merely exemplary, and other weighting factors and algorithms are possible. Accordingly, the purchase is charged to a business account of the user.
As can now be appreciated, disclosed embodiments enable a user to conveniently and easily associate purchases with the appropriate account when making purchases on a mobile device. In this way, the management of multiple accounts, such as personal and business accounts becomes greatly simplified.
Some of the functional components described in this specification have been labeled as systems or units in order to more particularly emphasize their implementation independence. For example, a system or unit may be implemented as a hardware circuit comprising custom VLSI circuits or gate arrays, off-the-shelf semiconductors such as logic chips, transistors, or other discrete components. A system or unit may also be implemented in programmable hardware devices such as field programmable gate arrays, programmable array logic, programmable logic devices, or the like. A system or unit may also be implemented in software for execution by various types of processors. A system or unit or component of executable code may, for instance, comprise one or more physical or logical blocks of computer instructions, which may, for instance, be organized as an object, procedure, or function. Nevertheless, the executables of an identified system or unit need not be physically located together, but may comprise disparate instructions stored in different locations which, when joined logically together, comprise the system or unit and achieve the stated purpose for the system or unit.
Further, a system or unit of executable code could be a single instruction, or many instructions, and may even be distributed over several different code segments, among different programs, and across several memory devices. Similarly, operational data may be identified and illustrated herein within modules, and may be embodied in any suitable form and organized within any suitable type of data structure. The operational data may be collected as a single data set, or may be distributed over different locations including over different storage devices and disparate memory devices.
Furthermore, systems/units may also be implemented as a combination of software and one or more hardware devices. For instance, location determination and alert message and/or coupon rendering may be embodied in the combination of a software executable code stored on a memory medium (e.g., memory storage device). In a further example, a system or unit may be the combination of a processor that operates on a set of operational data.
As noted above, some of the embodiments may be embodied in hardware. The hardware may be referenced as a hardware element. In general, a hardware element may refer to any hardware structures arranged to perform certain operations. In one embodiment, for example, the hardware elements may include any analog or digital electrical or electronic elements fabricated on a substrate. The fabrication may be performed using silicon-based integrated circuit (IC) techniques, such as complementary metal oxide semiconductor (CMOS), bipolar, and bipolar CMOS (BiCMOS) techniques, for example. Examples of hardware elements may include processors, microprocessors, circuits, circuit elements (e.g., transistors, resistors, capacitors, inductors, and so forth), integrated circuits, application specific integrated circuits (ASIC), programmable logic devices (PLD), digital signal processors (DSP), field programmable gate array (FPGA), logic gates, registers, semiconductor devices, chips, microchips, chip sets, and so forth. However, the embodiments are not limited in this context.
Also noted above, some embodiments may be embodied in software. The software may be referenced as a software element. In general, a software element may refer to any software structures arranged to perform certain operations. In one embodiment, for example, the software elements may include program instructions and/or data adapted for execution by a hardware element, such as a processor. Program instructions may include an organized list of commands comprising words, values, or symbols arranged in a predetermined syntax that, when executed, may cause a processor to perform a corresponding set of operations.
The present invention may be a system, a method, and/or a computer program product at any possible technical detail level of integration. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention.
The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, may be non-transitory, and thus is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.
Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device. Program data may also be received via the network adapter or network interface.
Computer readable program instructions for carrying out operations of embodiments of the present invention may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++ or the like, and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of embodiments of the present invention.
These computer readable program instructions may be provided to a processor of a computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
While the disclosure outlines exemplary embodiments, it will be appreciated that variations and modifications will occur to those skilled in the art. For example, although the illustrative embodiments are described herein as a series of acts or events, it will be appreciated that the present invention is not limited by the illustrated ordering of such acts or events unless specifically stated. Some acts may occur in different orders and/or concurrently with other acts or events apart from those illustrated and/or described herein, in accordance with the invention. In addition, not all illustrated steps may be required to implement a methodology in accordance with embodiments of the present invention. Furthermore, the methods according to embodiments of the present invention may be implemented in association with the formation and/or processing of structures illustrated and described herein as well as in association with other structures not illustrated. Moreover, in particular regard to the various functions performed by the above described components (assemblies, devices, circuits, etc.), the terms used to describe such components are intended to correspond, unless otherwise indicated, to any component which performs the specified function of the described component (i.e., that is functionally equivalent), even though not structurally equivalent to the disclosed structure which performs the function in the herein illustrated exemplary embodiments of the invention. In addition, while a particular feature of embodiments of the invention may have been disclosed with respect to only one of several embodiments, such feature may be combined with one or more features of the other embodiments as may be desired and advantageous for any given or particular application. Therefore, it is to be understood that the appended claims are intended to cover all such modifications and changes that fall within the true spirit of embodiments of the invention.
