Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
This Office Action is in response to Applicant’s communication filed on February 20, 2025 for the patent application 19/059,204. Claims 1 – 20 are pending in the application.
Information Disclosure Statement
The Information Disclosure Statement (IDS) submitted on February 20, 2025 was filed in compliance with the provisions of 37 CFR 1.97. Accordingly, this Information Disclosure Statement is being considered by the Examiner.
Claim Objections
Claims 9 and 14 are objected to under 37 CFR 1.75(c), as being of improper dependent form for failing to further limit the subject matter of a previous claim. Applicant is required to cancel the claim(s), or amend the claim(s) to place the claim(s) in proper dependent form, or rewrite the claim(s) in independent form. The claims site “The processor server computer of claim 8, the method further comprising”. This is improper because if the preceding claim is cancelled or withdrawn from consideration the next claim will be the preceding claim, which would make the claim mapping incorrectly.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim(s) 1 – 20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1 - 20 are either directed to a method or system or computer readable medium, which are statutory categories of invention. (Step 1: YES).
The Examiner has identified method claim 1 as the claim that represents the claimed invention for analysis and is similar to apparatus claim 8 and method claim 15. Claim 1 recites the limitations of:
( A ) receiving, by a processor server computer from a transport computer, an authorization request message for an interaction, the authorization request message comprising interaction data comprising an interaction amount;
( B ) transmitting, by the processor server computer, the authorization request message to an authorization computer;
( C ) receiving, by the processor server computer from the authorization computer, an authorization response message indicating that the interaction is approved;
( D ) based on the interaction data, generating, by the processor server computer, an indicator, wherein the indicator indicates a likelihood that the interaction amount in the authorization request message will equal a clearing amount for the interaction;
( E ) generating, by the processor server computer, a modified authorization response message comprising the indicator;
( F ) transmitting, by the processor server computer to the transport computer, the modified authorization response message;
( G ) generating, by the processor server computer, a clearing message based on the indicator and at least a subset of the interaction data; and
( H ) transmitting, by the processor server computer to the authorization computer or the transport computer, the clearing message, thereby causing clearing and settlement of the interaction.
These limitations without the bolded limitations above, cover performance of the limitations as certain methods of organizing human activity under their broadest reasonable interpretation.
More specifically, these limitations cover performance of the limitations as a fundamental economic practice.
In summary, if claim 1 limitations, under its broadest reasonable interpretation, covers performance of the limitation as a fundamental economic practice, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. Claims 8 and 15 are also abstract for similar reasons. (Step 2A-Prong 1: YES. The claims are abstract).
The use of the processor or any of the bolded limitations in claim 1 are just applying generic computer components to the recited abstract limitations. Similar arguments apply to claims 8 and 15.
Therefore, the above mentioned judicial exception is not integrated into a practical application by merely applying generic computer components (bolded elements).
Furthermore, the “receiving” step is recited at a high level of generality and amounts to mere data gathering/transmitting, which are forms of insignificant extra-solution activity (See MPEP 2106.05(g): CyberSource v. Retail Decisions, Inc., 654 F.3d 1366, 1375 (Fed. Cir. 2011); and OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015)).
In addition, supported by specification, the computer hardware are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component., see MPEP 2106.05(f), where applying a computer or using a computer is not indicative of a practical application).
Claim 1, limitation ( A ) – ( H ) above in Applicant’s specification para [0040], which discloses “FIG. 1 shows a process flow of a traditional clearing and settlement process. The clearing and settlement process 100 is performed in a system including a resource provider computer 110, a transport computer 120, a processor server computer 130, and an authorization computer 140. The system can further include a settlement agent 150. For simplicity of illustration, a limited number of components are shown in FIG. 1. It is understood, however, that embodiments may include more than one of each component. The components in the system depicted in FIG. 1 can be in operative communication with each other through any suitable communication channel or communications network.“.
Also, claim 1, limitation ( A ) and ( F ) above in Applicant’s specification para [0011], which discloses “In some embodiments, a method comprises transm1ttmg, by a transport computer to a processor server computer, an authorization request message for an interaction, the authorization request message comprising interaction data comprising an interaction amount; receiving, by the transport computer from the processor server computer, an authorization response message indicating that the inter-action is approved, the authorization response message further comprising an indicator, generated using a machine learning model, which indicates a likelihood that the inter-action amount in the authorization request message will equal a clearing amount for the interaction; receiving, by the transport computer, a clearing notification based on the indicator and at least a subset of the interaction data; and transmitting, by the transport computer to a computing device, at least a subset of the clearing message, thereby
causing updating of the machine learning model.”.
Also, claim 1, limitation ( B ), ( C ) and ( H ) above in Applicant’s specification para [0053], which discloses “FIG. 2 shows an example system 200 and flow for performing a clearing and settlement process using a clearing model according to various embodiments. The system 200 can comprise one or more computers associated with a processor server computer 230 and clearing model 260. The system 200 may further include a resource provider computer 210, an authorization computer 240, and a transport computer 220. For simplicity of illustration, a limited number of components are shown in FIG. 2. It is understood, however, that embodiments may include more than one of each component.“. Similar arguments apply to claims 8 and 15.
Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Therefore, claims 1, 8 and 15 are directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application).
The claims 1, 8 and 15 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more (also known as an “inventive concept”) to the exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements (bolded elements above) amount to no more than mere instructions to apply the abstract idea using generic computer components. In conclusion, merely "applying" the exception using generic computer components cannot provide an inventive concept. Therefore, claims 1, 8, and 15 are not patent eligible under 35 USC 101. (Step 2B: NO. The claims do not provide significantly more).
Dependent Claims
Dependent claims 2 – 7, 9 - 14 and 16 - 20 are also rejected under 35 U.S.C. 101. Dependent claims 2 – 7, 9 - 14 and 16 - 20 are further define the abstract idea or further define the extra-solution activities that are present in independent claim 1 thus abstract idea correspond to certain methods of organizing human activity as presented above. Claims 2 – 7, 9 - 14 and 16 - 20 clearly further define the abstract idea as stated above and further define extra-solution activities such as presenting data and transmitting/receiving data.
Furthermore, dependent claims 2 – 7, 9 - 14 and 16 - 20do not include any additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination.
Regarding claims 2, 10 and 16, these claims merely recite additional steps that amount to no more than insignificant extra-solution activity. Specifically, claim 2 states “wherein the clearing of the interaction is performed in less than an hour from transmitting the modified authorization response message.”. These steps amount to no more than mere data gathering/analysis, which is a form of insignificant extra- solution activity (See M PEP 2016.05(g): CyberSource v. Retail Decisions, Inc., 654 F.3d 1366, 1375 (Fed. Cir. 2011); and GIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015)). Such limitations do not integrate the abstract idea into a practical application, or amount to significantly than the abstract idea, because the courts have found the concept of data gathering to be well-understood, routine, and conventional activity (See MPEP 2106.05(d): GIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015); and buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, (Fed. Cir. 2014)). Similar arguments can be made for claims 10 and 16.
Regarding claims 3, 11 and 17, these claims merely recite, " wherein the indicator is generated using a machine learning model trained to predict the likelihood that the interaction amount in the authorization request message will equal the clearing amount for the interaction.“. These limitation merely recites storing data in a server which amounts to no more than gathering/storing data which is a form of insignificant extra-solution activity (See MPEP 2106.0S(g)(3)(iii): GIP Technologies, 788 F.3d at 1363). This does not integrate the abstract idea into a practical application because it has been determined, by the courts, that the concept of storing data is well-understood, routine, and conventional activity (See MPEP 2106.0S(d)(II): Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334 (Fed. Cir. 2015)). Similar arguments can be made for claims 11 and 17.
Regarding claims 4 and 12, these claims merely add further description to the process of “training the machine learning model using historical interaction data.”. This amount to no more than mere data gathering/outputting as described in reference to claims 1, 8 and 15 (see analysis above). Merely describing the comparing the historical interaction data does not integrate the abstract idea into a practical application, or amount to significantly more than the judicial exception, because it does not impose any meaningful limitations on practicing the abstract idea. Similar arguments can be made for claim 12.
Regarding claims 5 and 13, these claims merely add further description to the process of “the machine learning model comprises a multi-task learning model having a plurality of layers.”, which amounts to no more than gathering/storing data which is a form of insignificant extra-solution activity (See MPEP 2106.0S(g)(3)(iii): GIP Technologies, 788 F.3d at 1363). This does not integrate the abstract idea into a practical application because it has been determined, by the courts, that the concept of storing data is well-understood, routine, and conventional activity (See MPEP 2106.0S(d)(II): Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334 (Fed. Cir. 2015)). Similar arguments can be made for claim 13.
Regarding claim 6, this claim merely recite, "wherein the processor server computer transmits the clearing message to both the authorization computer and the transport computer.“. These limitation merely recites storing data in a server which amounts to no more than gathering/storing data which is a form of insignificant extra-solution activity (See MPEP 2106.0S(g)(3)(iii): GIP Technologies, 788 F.3d at 1363). This does not integrate the abstract idea into a practical application because it has been determined, by the courts, that the concept of storing data is well-understood, routine, and conventional activity (See MPEP 2106.0S(d)(II): Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334 (Fed. Cir. 2015)).
Regarding claims 7 and 14, these claims merely recite additional steps that amount to no more than insignificant extra-solution activity. Specifically, claim 7 states “determining, based on the interaction data, that the transport computer is enrolled in a program before generating the indicator, wherein generating the indicator, generating the modified authorization response message comprising the indicator, and generating and transmitting the clearing message are performed responsive to determining the enrollment.”. These steps amount to no more than mere data gathering/analysis, which is a form of insignificant extra- solution activity (See M PEP 2016.05(g): CyberSource v. Retail Decisions, Inc., 654 F.3d 1366, 1375 (Fed. Cir. 2011); and GIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015)). Such limitations do not integrate the abstract idea into a practical application, or amount to significantly than the abstract idea, because the courts have found the concept of data gathering to be well-understood, routine, and conventional activity (See MPEP 2106.05(d): GIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015); and buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, (Fed. Cir. 2014)). Similar arguments can be made for claim 14.
Regarding claim 9, this claim merely provide further detail regarding the processing the message, recited in claim 8. Merely stating, “receiving the authorization request message from the transport computer prior to transmitting it to the authorizing computer.”. This does not integrate the abstract idea into a practical application because it does not impose any meaningful limitation on practicing the abstract idea.
Regarding claim 18, this claim merely recite, "refraining from generating the clearing message based on the indicator.“. These limitation merely recites storing data in a server which amounts to no more than gathering/storing data which is a form of insignificant extra-solution activity (See MPEP 2106.0S(g)(3)(iii): GIP Technologies, 788 F.3d at 1363). This does not integrate the abstract idea into a practical application because it has been determined, by the courts, that the concept of storing data is well-understood, routine, and conventional activity (See MPEP 2106.0S(d)(II): Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334 (Fed. Cir. 2015)). Similar arguments can be made for claims 11 and 17.
Regarding claim 19, this claim merely add further description to the process of “wherein the processor server computer generates the clearing message based on the indicator.”. This amount to no more than mere data gathering/outputting as described in reference to claims 1, 8 and 15 (see analysis above). Merely describing the clearing message does not integrate the abstract idea into a practical application, or amount to significantly more than the judicial exception, because it does not impose any meaningful limitations on practicing the abstract idea.
Regarding claim 20, this claim merely add further description to the process of “providing, to the processor server computer, configuration data configuring enrollment in a program, wherein receiving the indicator and generating the clearing message based on the indicator and at least a subset of the interaction data are performed responsive to providing the configuration data.”, which amounts to no more than gathering/storing data which is a form of insignificant extra-solution activity (See MPEP 2106.0S(g)(3)(iii): GIP Technologies, 788 F.3d at 1363). This does not integrate the abstract idea into a practical application because it has been determined, by the courts, that the concept of storing data is well-understood, routine, and conventional activity (See MPEP 2106.0S(d)(II): Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334 (Fed. Cir. 2015)).
As a result, such limitations do not overcome the requirements as described above. Therefore, claims 2 – 7, 9 - 14 and 16 - 20 are directed to an abstract idea. Thus, claims 1 - 20 are not patent eligible.
Claim Rejections – 35 USC §103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1 – 20 are rejected under 35 U.S.C. 103 as being obvious over Xi Kan et al. (Pub. # US 2022/0245516 A1 – herein referred to as Kan) in view of Arnab Banerjee (Pub. # US 2023/0088260 A1 – herein referred to as Banerjee).
Re: Claim 1, Kan discloses a method comprising:
receiving, by a processor server computer from a transport computer, an authorization request message for an interaction, the authorization request message comprising interaction data comprising an interaction amount (Kan, [0016] – In some non-limiting embodiments or aspects, the computer-implemented method further includes: the first task comprising generating, based on an authorization request, a first prediction associated with a likelihood of a first transaction amount in the authorization request matching a second transaction amount in at least one clearing message corresponding to the authorization request. );
transmitting, by the processor server computer, the authorization request message to an authorization computer (Kan, [0017] – In some non-limiting embodiments or aspects, the computer-implemented method further includes: the at least one second task comprising at least one of generating, based on the authorization request, a second prediction associated with when the at least one clearing message will be received after the authorization message, generating, based on the authorization request, a third prediction associated with a number of clearing messages of the at least one clearing message, or any combination thereof.);
receiving, by the processor server computer from the authorization computer, an authorization response message indicating that the interaction is approved (Kan, [0064] – For example, during token requestor registration, the token service provider may formally process a token requestor's application to participate in the token service system. In some non-limiting embodiments or aspects, the token service provider may collect information pertaining to the nature of the requestor and relevant use of tokens to validate and formally approve the token requestor and establish appropriate domain restriction controls. Additionally or alternatively, successfully registered token requestors may be assigned a token requestor identifier that may also be entered and maintained within the token vault. In some non-limiting embodiments or aspects, token requestor identifiers may be revoked and/or token requestors may be assigned new token requestor identifiers. In some non-limiting embodiments or aspects, this information may be subject to reporting and audit by the token service provider.);
transmitting, by the processor server computer to the transport computer, the modified authorization response message (Kan, [0024] – According to some non-limiting embodiments or aspects, provided is a computer-implemented method, comprising: receiving, with at least one processor, an authorization request from at least one of a merchant system or an acquirer system; generating, with the at least one processor, based on the authorization request and a machine learning model, a first score associated with a likelihood of a first transaction amount in the authorization request matching a second transaction amount in at least one clearing message corresponding to the authorization request; inserting, with the at least one processor, the first score into at least one field of the authorization request to provide an enhanced authorization request; and communicating, with the at least one processor, the enhanced authorization request to an issuer system.);
However, Kan does not expressly disclose:
based on the interaction data, generating, by the processor server computer, an indicator, wherein the indicator indicates a likelihood that the interaction amount in the authorization request message will equal a clearing amount for the interaction;
generating, by the processor server computer, a modified authorization response message comprising the indicator;
generating, by the processor server computer, a clearing message based on the indicator and at least a subset of the interaction data; and
transmitting, by the processor server computer to the authorization computer or the transport computer, the clearing message, thereby causing clearing and settlement of the interaction.
In a similar field of endeavor, Banerjee discloses:
based on the interaction data, generating, by the processor server computer, an indicator, wherein the indicator indicates a likelihood that the interaction amount in the authorization request message will equal a clearing amount for the interaction (Banerjee, [0049] – Upon receiving the authorization response message from the authorizing entity computer 112, the transaction processing network computer 110 stores information associated with the upgraded transaction at a database 210. For example, the information may include an indicator that the transaction has been already finalized (e.g. settled) by the authorizing entity computer 112. The transaction processing network computer 110 also generates and sends an authorization response message in the first format to the transport computer 108. The authorization response message in the first format includes the authorization decision of the authorizing entity computer 112.);
generating, by the processor server computer, a modified authorization response message comprising the indicator (Banerjee, [0041] – The upgrade of the initial authorization request message of the transport computer 108 may be unbeknownst to the transport computer. That is, the transport computer may be entirely unaware that the transaction processing network computer upgraded the authorization request message to a single message system and that the transaction is already finalized (e.g. settled). Accordingly, since the trans-port computer 108 functions on the first message format (e.g. the dual message system), the transport computer 108 may send a second message (e.g. a clearing and settlement message) to the transaction processing network computer 110 to finalize the transaction after the transaction has been authorized by the authorizing entity (that, unbeknownst to the transport computer, has already settled the transaction with the transaction processing network computer). Upon receiving the second message from the transport computer, the transaction processing network computer 110 may retrieve the data (e.g. the settlement data received from the authorizing entity computer) associated with the transaction from the database, confirm that the transaction is finalized (e.g. settled), and notify the transport computer 108.);
generating, by the processor server computer, a clearing message based on the indicator and at least a subset of the interaction data (Banerjee, [0045] – The score may indicate the likelihood that the amount remain consistent through authorization, settlement and clearing of the transaction. For example, a low score may indicate a low amount certainty and a high score may indicate a high amount certainty. In some embodiments, the AI-based scoring processor 208 may determine the likelihood based on past transaction data. The AI-based scoring processor 208 may execute a machine learning algorithm to determine the score for the transaction. The AI-based scoring processor 208 may return the score to the transaction processing network computer 110. In some embodiments, the AI-based scoring processor 208 may determine a score for a transaction for each authorization request message received at the transaction processing network computer 110.); and
transmitting, by the processor server computer to the authorization computer or the transport computer, the clearing message, thereby causing clearing and settlement of the interaction (Banerjee, [0050] – The upgrading of the authorization request message from the first format to the second format is unbeknownst to the transport computer 108. Since the transport computer 108 communicates in the first format, a certain amount of time after receiving the authorization response message from the transaction processing network computer 110, the transport computer 108 generates and sends a second message 206 (e.g. a clearing and settlement message) in the first format to finalize the transaction. Upon receiving the second message, a reconciliation module 212 of the transaction processing network computer 110 identifies the transaction, retrieves the information associated with the transaction from the database 210, determines that the transaction has been finalized by the authorizing entity computer 112, and informs the transport computer 108 that the transaction has been finalized.).
Therefore, in light of the teachings of Banerjee, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify the method of Kan, motivation according to one KSR Exemplary Rationale where a known technique is used to improve similar methods and systems in the same way by providing a server computer configured or programmed to receive, from a transport computer, an authorization request message associated with a transaction between an account holder and a resource provider, wherein the authorization request message requires a second message in addition to the authorization request message to finalize the transaction upon authorization; assign a score to the transaction; compare the score to a predetermined threshold; and upgrade the authorization request message into an upgraded authorization request message that is configured for authorizing and finalizing the transaction at the same time prior to receiving the second message from the transport computer.
Re: Claim 2, Kan in view of Banerjee discloses the method of claim 1,
wherein the clearing of the interaction is performed in less than an hour from transmitting the modified authorization response message (Banerjee, [0050] – The upgrading of the authorization request message from the first format to the second format is unbeknownst to the transport computer 108. Since the transport computer 108 communicates in the first format, a certain amount of time after receiving the authorization response message from the transaction processing network computer 110, the transport computer 108 generates and sends a second message 206 (e.g. a clearing and settlement message) in the first format to finalize the transaction. Upon receiving the second message, a reconciliation module 212 of the transaction processing network computer 110 identifies the transaction, retrieves the information associated with the transaction from the database 210, determines that the transaction has been finalized by the authorizing entity computer 112, and informs the transport computer 108 that the transaction has been finalized.). The rationale for support of motivation, obviousness and reason to combine see claim 1 above.
Re: Claim 3, Kan in view of Banerjee discloses the method of claim 1,
wherein the indicator is generated using a machine learning model trained to predict the likelihood that the interaction amount in the authorization request message will equal the clearing amount for the interaction (Banerjee, [0045] – The score may indicate the likelihood that the amount remain consistent through authorization, settlement and clearing of the transaction. For example, a low score may indicate a low amount certainty and a high score may indicate a high amount certainty. In some embodiments, the AI-based scoring processor 208 may determine the likelihood based on past transaction data. The AI-based scoring processor 208 may execute a machine learning algorithm to determine the score for the transaction. The AI-based scoring processor 208 may return the score to the transaction processing network computer 110. In some embodiments, the AI-based scoring processor 208 may determine a score for a transaction for each authorization request message received at the transaction processing network computer 110.). The rationale for support of motivation, obviousness and reason to combine see claim 1 above.
Re: Claim 4, Kan in view of Banerjee discloses the method of claim 3, further comprising:
training the machine learning model using historical interaction data (Banerjee, [0055] – At step 308, the AI-based transaction scoring server 208 determines a likelihood that a final value of the transaction (when the transaction is finalized) will be same as an initial value of the transaction identified in the authorization request message. The AI-based transaction scoring server 208 assigns a score to the transaction based on the likelihood that the final value will be same as the initial value. According to various embodiments, the AI-based transaction scoring server 208 assigns the score using a machine learning algorithm that takes into account one or more of characteristics of the resource provider, characteristics of the transaction, a transaction history of the account holder, a transaction history of the resource provider, or a characteristic of the transaction, among other data available to the AI-based transaction scoring server 208.). The rationale for support of motivation, obviousness and reason to combine see claim 1 above.
Re: Claim 5, Kan discloses the method of claim 3,
wherein:
the machine learning model comprises a multi-task learning model having a plurality of layers (Kan, [0024] – According to some non-limiting embodiments or aspects, provided is a computer-implemented method, comprising: receiving, with at least one processor, an authorization request from at least one of a merchant system or an acquirer system; generating, with the at least one processor, based on the authorization request and a machine learning model, a first score associated with a likelihood of a first transaction amount in the authorization request matching a second transaction amount in at least one clearing message corresponding to the authorization request; inserting, with the at least one processor, the first score into at least one field of the authorization request to provide an enhanced authorization request; and communicating, with the at least one processor, the enhanced authorization request to an issuer system.).
Re: Claim 6, Kan in view of Banerjee discloses the method of claim 1,
wherein the processor server computer transmits the clearing message to both the authorization computer and the transport computer (Banerjee, [0067] – According to various embodiments, the computer readable medium 412 may comprise code, executable by the one or more processor(s) 414, for performing a method comprising receiving, from a transport computer, an authorization request message associated with a transaction between an account holder and a resource provider, wherein the authorization request message requires a second message in addition to the authorization request message to finalize the transaction upon authorization; assigning a score to the transaction; comparing the score to a predetermined thresh-old; upgrading the authorization request message into an upgraded authorization request message that is configured for authorizing and finalizing the transaction at the same time prior to receiving the second message from the trans-port computer. In some embodiments, the method may also comprise transmitting the upgraded authorization request message to an authorizing entity computer; and receiving an authorization response message in from the authorizing entity computer, wherein the authorizing response message includes an indication about whether the transaction is authorized or declined, and additional information required for finalizing the transaction, wherein the authorization response message finalizes the transaction.). The rationale for support of motivation, obviousness and reason to combine see claim 1 above.
Re: Claim 7, Kan discloses the method of claim 1, further comprising:
determining, based on the interaction data, that the transport computer is enrolled in a program before generating the indicator, wherein generating the indicator, generating the modified authorization response message comprising the indicator, and generating and transmitting the clearing message are performed responsive to determining the enrollment (Kan, [0043] – Clause 16: The computer-implemented method of clauses 1-15, wherein generating the first score, any of inserting the first score into the at least one field of the authorization request to provide the enhanced authorization request, and communicating the enhanced authorization request are in response to determining that the issuer is enrolled in the program.).
Re: Claim 8, Claim 8 is an apparatus claim corresponding to method claim 1. Therefore, claim 8 is analyzed and rejected as previously discussed with respect to claim 1.
Re: Claim 9, Kan discloses the processor server computer of claim 8, the method further comprising:
receiving the authorization request message from the transport computer prior to transmitting it to the authorizing computer (Kan, [0017] – In some non-limiting embodiments or aspects, the computer-implemented method further includes: the at least one second task comprising at least one of generating, based on the authorization request, a second prediction associated with when the at least one clearing message will be received after the authorization message, generating, based on the authorization request, a third prediction associated with a number of clearing messages of the at least one clearing message, or any combination thereof.).
Re: Claim 10, Claim 10 is an apparatus claim corresponding to method claim 2. Therefore, claim 10 is analyzed and rejected as previously discussed with respect to claim 2.
Re: Claim 11, Claim 11 is an apparatus claim corresponding to method claim 3. Therefore, claim 11 is analyzed and rejected as previously discussed with respect to claim 3.
Re: Claim 12, Claim 12 is an apparatus claim corresponding to method claim 4. Therefore, claim 12 is analyzed and rejected as previously discussed with respect to claim 4.
Re: Claim 13, Claim 13 is an apparatus claim corresponding to method claim 5. Therefore, claim 13 is analyzed and rejected as previously discussed with respect to claim 5.
Re: Claim 14, Claim 14 is an apparatus claim corresponding to method claim 7. Therefore, claim 14 is analyzed and rejected as previously discussed with respect to claim 7.
Re: Claim 15, Claim 15 is a method claim corresponding to method claim 1. Therefore, claim 15 is analyzed and rejected as previously discussed with respect to claim 1.
Re: Claim 16, Claim 16 is a method claim corresponding to method claim 2. Therefore, claim 16 is analyzed and rejected as previously discussed with respect to claim 2.
Re: Claim 17, Claim 17 is a method claim corresponding to method claim 3. Therefore, claim 17 is analyzed and rejected as previously discussed with respect to claim 3.
Re: Claim 18, Kan in view of Banerjee discloses the method of claim 15, further comprising:
refraining from generating the clearing message based on the indicator (Banerjee, [0045] – The score may indicate the likelihood that the amount remain consistent through authorization, settlement and clearing of the transaction. For example, a low score may indicate a low amount certainty and a high score may indicate a high amount certainty. In some embodiments, the AI-based scoring processor 208 may determine the likelihood based on past transaction data. The AI-based scoring processor 208 may execute a machine learning algorithm to determine the score for the transaction. The AI-based scoring processor 208 may return the score to the transaction processing network computer 110. In some embodiments, the AI-based scoring processor 208 may determine a score for a transaction for each authorization request message received at the transaction processing network computer 110.). The rationale for support of motivation, obviousness and reason to combine see claim 15 above.
Re: Claim 19, Kan in view of Banerjee discloses the method of claim 18,
wherein the processor server computer generates the clearing message based on the indicator (Banerjee, [0049] – Upon receiving the authorization response message from the authorizing entity computer 112, the transaction processing network computer 110 stores information associated with the upgraded transaction at a database 210. For example, the information may include an indicator that the transaction has been already finalized (e.g. settled) by the authorizing entity computer 112. The transaction processing network computer 110 also generates and sends an authorization response message in the first format to the transport computer 108. The authorization response message in the first format includes the authorization decision of the authorizing entity computer 112.). The rationale for support of motivation, obviousness and reason to combine see claim 15 above.
Re: Claim 20, Kan discloses the method of claim 15, further comprising:
providing, to the processor server computer, configuration data configuring enrollment in a program, wherein receiving the indicator and generating the clearing message based on the indicator and at least a subset of the interaction data are performed responsive to providing the configuration data (Kan, [0043] – Clause 16: The computer-implemented method of clauses 1-15, wherein generating the first score, any of inserting the first score into the at least one field of the authorization request to provide the enhanced authorization request, and communicating the enhanced authorization request are in response to determining that the issuer is enrolled in the program.).
Conclusion
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/John H. Holly/Primary Examiner, Art Unit 3696
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