Estimating interchange fees for card payments

• US 10,402,807 B1
• Filed: 02/28/2017
• Issued: 09/03/2019
• Est. Priority Date: 02/28/2017
• Status: Active Grant

• Current Assignee: Block, Inc. (f/k/a Square, Inc.)
• Original Assignee: Block, Inc. (f/k/a Square, Inc.)
• Inventors: Iyer, Kalyani, Guneri, Mehmet Zahit, Jarosch, Dennis, Ward, Michael, Kaneda, Kenji
• Primary Examiner(s): Zeender, Florian M
• Assistant Examiner(s): Buchanan, Christopher B
• Application Number:
  US15/444,898
• Time in Patent Office: 917 Days
• Field of Search: 705 21, 705 16
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 20/20 Ensemble learning
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06Q 20/027 involving a payment switch or gateway
• CPC Class Codes: G06Q 20/20 Point-of-sale [POS] network systems
• CPC Class Codes: G06Q 20/202 Interconnection or interaction of plural electronic cash registers [ECR] or to host computer, e.g. network details, transfer of information from host to ECR or from ECR to ECR
• CPC Class Codes: G06Q 20/34 using cards, e.g. integrated circuit [IC] cards or magnetic cards
• CPC Class Codes: G06Q 20/405 Establishing or using transaction specific rules
• CPC Class Codes: G06Q 20/4093 Monitoring of device authentication

Abstract

A payment processing system is configured to support purchase transactions generated by merchant point-of-sale (POS) devices. Information regarding the purchase transactions is archived and periodically analyzed using machine learning to create a predictive model relating transaction attributes to bank interchange fees. The predictive model is then used to estimate interchange fees that are later passed on to merchants. This allows more accurate settlement with merchants in situations where reports regarding actual interchange fees are not yet available.

Claims

1. A method comprising:

receiving, via a device associated with a merchant, payment instruments to initiate exchanges, the device executing an instance of a merchant application installed for configuring the device as a point-of-sale (POS) terminal, the POS terminal configured to send first exchange information and second exchange information associated with the exchanges over a network to a support system;

receiving, by one or more computers of the support system, the first exchange information regarding the exchanges from the POS device, the first exchange information indicating exchange amounts and instrument identifiers associated with the exchanges, and wherein the payment instruments are issued by one or more issuers that receive issuer amounts;

determining a transaction feature value based at least in part on the first exchange information;

identifying, by the one or more computers of the support system, training data corresponding to the exchanges, the training data indicating, for each of the exchanges;

a first exchange amount;

a first instrument identifier, and one or more of;

a category code of an entity that conducted the exchange;

an amount of the exchange;

or

a type of payment instrument used in the exchange;

creating a predictive model based at least in part on analyzing, by the one or more computers of the support system, the transaction feature value and the training data, the predictive model identifying first predicted issuer amounts associated with the exchanges;

receiving, by the one or more computers of the support system, the second exchange information, wherein the second exchange information is associated with a new exchange from the POS device, and wherein the second exchange information indicates a second exchange amount and a second instrument identifier used in the new exchange;

requesting, by the one or more computers of the support system, authorization to transfer the second exchange amount from an issuer of the payment instrument to an acquirer associated with the support system;

analyzing, by the one or more computers of the support system and using the predictive model, the second exchange information to determine a second predicted issuer amount of the new exchange;

calculating, by the one or more computers of the support system, an adjusted amount for the new exchange, wherein the adjusted amount comprises the second exchange amount minus one or more processing amounts, and wherein the one or more processing amounts include the second predicted issuer amount; and

initiating, by the one or more computers of the support system and prior to receiving an indication of an actual issuer amount for the new exchange, a batch fund transfer to an entity that conducted the new exchange, wherein the batch fund transfer is for adjusted amounts of multiple ones of the exchanges that occurred during a previous time period, and wherein the multiple ones of the exchanges include the new exchange.

2. The method of claim 1, wherein analyzing the transaction feature value and the training data comprises using machine learning.

3. The method of claim 1, further comprising:

receiving, from the acquirer, a report indicating issuer amounts corresponding to the multiple ones of the exchanges; and

wherein initiating the batch fund transfer is performed prior to receiving the report.

4. The method of claim 1, the training data further indicating, for at least one of the exchanges, at least one of:

an identification number of the payment instrument;

a tip amount;

a ratio of the tip amount to the amount of the at least one of the exchanges;

whether a past exchange was a card-present exchange;

a country of the issuer of the payment instrument;

a method of entering the payment instrument;

a gateway associated with the payment instrument;

a subcategory of the payment instrument;

a brand of the payment instrument;

or

an identifier of the issuing bank of the payment instrument.

5. A system associated with a payment processing service, comprising:

one or more processors; and

one or more non-transitory computer-readable media storing instructions executable by the one or more processors, wherein the instructions program the one or more processors to perform acts comprising;

receiving, via one or more point-of-sale (POS) devices, exchange data associated with exchanges using payment instruments of one or more issuers, wherein a POS device of the one or more POS devices comprises a computing device that has installed thereon an instance of a merchant application that configures the computing device to receive the exchange data and transmit the exchange data to the payment processing service;

identifying training data corresponding to the exchanges, wherein the training data includes historical information, determined based at least in part on the exchange data, associated with the exchanges;

determining a transaction feature value based at least in part on the historical information;

creating a predictive model based at least in part on analyzing the training data and the transaction feature value, the predictive model identifying first predicted issuer amounts associated with the exchanges;

receiving, via the POS device, information regarding a new exchange, wherein the information indicates an amount of the new exchange;

analyzing, using the predictive model, the information to determine a second predicted issuer amount for the new exchange;

calculating an adjusted amount for the new exchange, wherein the adjusted amount comprises the amount minus one or more processing amounts, and wherein the one or more processing amounts include the second predicted issuer amount; and

crediting the adjusted amount to an entity that conducted the new exchange.

6. The system of claim 5, wherein determining the transaction feature value includes determining at least one of a bank identification number (BIN) of the payment instrument, a purchase transaction amount, a merchant category code (MCC), a payment instrument type, a tip amount, a ratio between a tip amount and the purchase transaction amount, a payment method, a payment gateway associated with the payment instrument, whether the transaction is a prepayment, a payment instrument brand, a payment instrument nationality, a sub-category of the payment instrument, whether the payment instrument is a flexible spending account (FSA) debit card, whether the payment instrument is a health savings (HAS) debit card, a merchant account number, or a percentage of past transactions having the BIN.

7. The system of claim 5, wherein the crediting is performed before receiving an indication of an actual issuer amount corresponding to the new exchange, and wherein creating the predictive model is performed via machine learning.

8. The system of claim 5, further comprising:

receiving one or more reports indicating actual issuer amounts for multiple ones of the exchanges, wherein the multiple ones of the exchanges include the new exchange; and

wherein the crediting is performed before receiving the one or more reports.

9. The system of claim 5, further comprising initiating a batch fund transfer to the entity that conducted the new exchange before receiving an indication of an actual issuer amount for the new exchange, wherein the batch fund transfer is for adjusted amounts of multiple ones of the exchanges that occurred during a previous time period, and wherein the multiple ones of the exchanges include the new exchange.

10. The system of claim 5, wherein:

the information regarding the new exchange identifies a payment instrument used in the new exchange; and

the payment instrument comprises at least one of a credit card or a debit card.

11. The system of claim 5, wherein the historical information indicates at least one of:

a category code of an entity that conducted a past exchange of the exchanges;

an indication that the past exchange was a card-present transaction or a card-not-present transaction;

or

a payment entry method.

12. A method implemented at least in part by a server computing device associated with a payment processing service, the method comprising:

receiving, via one or more point-of-sale (POS) devices, exchange data associated with exchanges using payment instruments of one or more issuers, wherein an issuer amount is associated with each of the exchanges, wherein a POS device of the one or more POS devices comprises a computing device that has installed thereon an instance of a merchant application that configures the computing device to receive the exchange data and transmit the exchange data to the payment processing service;

identifying training data corresponding to the exchanges, wherein the training data includes historical information, determined based at least in part on the exchange data, associated with the exchanges;

determining a transaction feature value based at least in part on the historical information;

creating a predictive model based at least in part on analyzing the training data and the transaction feature value, the predictive model identifying first predicted issuer amounts associated with the exchanges;

receiving information regarding a new exchange via the POS device; and

analyzing, using the predictive model, the information regarding the new exchange to determine a second predicted issuer amount for the new exchange.

13. The method of claim 12, wherein determining the transaction feature value includes determining at least one of a bank identification number (BIN) of the payment instrument, a purchase transaction amount, a merchant category code (MCC), a payment instrument type, a tip amount, a ratio between a tip amount and the purchase transaction amount, a payment method, a payment gateway associated with the payment instrument, whether the transaction is a prepayment, a payment instrument brand, a payment instrument nationality, a sub-category of the payment instrument, whether the payment instrument is a flexible spending account (FSA) debit card, whether the payment instrument is a health savings (HAS) debit card, a merchant account number, or a percentage of past transactions having the BIN.

14. The method of claim 12, wherein the information regarding the new exchange indicates at least one of:

an amount of the new exchange;

a category code of an entity that conducted the new exchange;

an indication that the new exchange was a card-present transaction or a card-not-present transaction;

or

a method of entering a payment instrument used in the new exchange.

15. The method of claim 12, further comprising:

calculating an adjusted amount for the new exchange, wherein the adjusted amount comprises a transaction amount of the new exchange minus one or more processing amounts, wherein the one or more processing amounts include the second predicted issuer amount; and

crediting the adjusted amount to an entity that conducted the new exchange.

16. The method of claim 15, wherein the crediting is performed before receiving an indication of an actual issuer amount corresponding to the new exchange.

17. The method of claim 15, further comprising initiating a batch fund transfer to an entity that conducted the transaction before receiving an indication of an actual issuer amount for the new exchange, wherein the batch fund transfer is for adjusted amounts of multiple ones of the exchanges that occurred during a previous time period, and wherein the multiple ones of the exchanges include the new exchange.

18. The method of claim 12, further comprising producing a report that is based at least in part on the second predicted issuer amount.

19. The method of claim 12, wherein the information indicates a payment instrument that is associated with multiple exchange processors, and wherein the first predicted issuer amounts are associated with a first exchange processor of the multiple exchange processors, the method further comprising:

analyzing the information using the predictive model to determine the second predicted issuer amount associated with a second exchange processor of the multiple exchange processors;

selecting at least one of the first or second exchange processors based at least in part on the first predicted issuer amounts and the second predicted issuer amount; and

initiating processing of the new exchange using the at least one of the first or second exchange processors based at least in part on selecting the at least one of the first or second exchange processors.

20. The method of claim 12, wherein the historical information indicates at least one of:

a category code of an entity that conducted at least one of the exchanges;

an indication that the at least one of the exchanges was a card-present transaction or a card-not-present transaction;

or

a payment entry method.