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 action is in response to the application filed on 4/16/2026.
Priority
Acknowledgment is made of applicant's claim for prior priority date of U.S. Provisional Patent Application 63/384,101 11/17/2022
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.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
The claims are directed to a system which are/is one of the statutory categories of invention. (Step 1: YES).
The Examiner has identified independent system Claim 6 (herein called the Primary Independent Claim) as the claim that represents the claimed invention for analysis and is similar to independent claims currently restricted out (herein called Additional Independent Claims). The Primary Independent Claim recites the limitations of:
A settlement card system, comprising: a plurality of settlement cards issued by a card issuer, each settlement card comprising one of a physical or virtual settlement card and each assigned to a specific card customer, each settlement card having security that locks the respective settlement card for authorized use with a single card specific merchant per transaction, and each settlement card having secure, stored settlement card data identifying a) the respective customer to which the settlement card is assigned, b) the card issuer, c) the card specific merchant, and d) a card payment service of the settlement card;
a first computing system comprising a processor and memory operated by the card issuer, said processor configured to pull past financial transaction data and associated business data for the settlement card customer from public and private data sources and extract customer data features as decision values for each respective settlement card, said first computing system further comprising a rules database storing a set of transaction rules that are specific for each settlement card for a single transaction involving the respective settlement card, and a rules engine module operative with the rules database, wherein upon a single transaction by a customer involving its respective settlement card, the rules engine module retrieves from the rules database the current set of transaction rules specific for the settlement card and applies a machine learning approval model to the respective customer decision values using the retrieved set of transaction rules and determines a transaction monetary limit and customer payment terms for that current transaction;
a second computing system configured to receive from the card specific merchant the stored card data of the settlement card and an authorization request for approval of the transaction when the customer presents its settlement card to the card specific merchant to effect the transaction, wherein said second computing system is configured to identify the settlement card issuer and customer from the stored settlement card data and forward the authorization request to the first computing system, wherein the first computing system is and rules engine module determines if the transaction is within the monetary limit determined for the customer, and if no, reject the transaction, if yes, accept the transaction and determine customer payment terms for that transaction;
a third computing system operated by the card payment service, said third computing system configured to make payment to the authorized merchant for the transaction after receiving a payment authorization from the first computing system, and in response, the first computing system transfers a payment to the third computing system in the amount of the transaction;
said first computing system further comprising a cache associated with the processor and rules engine module, wherein the processor after a transaction involving the respective settlement card from the customer pulls recent financial transaction data and associated business data and processes the pulled data to update and form updated decision values associated with that respective customer settlement card and stores the updated decision values within the memory, and upon a subsequent single transaction by the customer involving its settlement card, the rules engine module:
a) retrieves the set of transaction rules for the respective settlement card from the rules database,
b) caches the retrieved set of transaction rules within the cache,
c) retrieves the updated decision values from memory and stores the updated decision values within the cache,
d) determines a new set of transaction rules that are optimized for the subsequent transaction of the customer based on updated decision values,
e) applies the machine learning model to updated decision values using the new set of transaction rules that are optimized for the subsequent transaction to determine a new customer monetary limit and payment terms for the subsequent, single transaction of the settlement card by the customer, and
f) stores the updated decision values within memory and the new set of transaction rules for the customer settlement card within the rules database.
These limitations, under their broadest reasonable interpretation, cover performance of the limitation as “Certain Methods of Organizing Human Activity”. The limitation of at least “updates decision values and applies the machine learning model and a set of new rules to the updated decision values and determine a new customer monetary limit and payment terms for the subsequent, single transaction by the customer” recites a fundamental economic practice. If a claim limitation, 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.
The limitation of at least “a first second and third computing system” in the Primary Independent Claim is just applying generic computer components to the recited abstract limitations. The recitation of generic computer components in a claim does not necessarily preclude that claim from reciting an abstract idea. The Additional Independent Claims are also abstract for similar reasons. (Step 2A-Prong 1: YES. The claims recite an abstract idea)
This judicial exception is not integrated into a practical application. The examiner did not find any additional elements that would cause further analysis. The computer hardware/software is/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. 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 and are at a high level of generality. Therefore, all the independent claims 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 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 element of using a computer hardware and software per se amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. See MPEP 2106.05(f) where applying a computer as a tool is not indicative of significantly more as well as MPEP 2106.05(d). Accordingly, these additional elements, do not change the outcome of the analysis, when considered separately and as an ordered combination. Thus, all independent claims are not patent eligible. (Step 2B: NO. The claims do not provide significantly more)
Dependent claims further define the abstract idea that is present in their respective independent claims, and thus correspond to Certain Methods of Organizing Human Activity and hence are abstract for the reasons presented above. The dependent claims do 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. Therefore, the dependent claims are directed to an abstract idea. Thus, all the claims 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, 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-20 listed below are rejected under 35 U.S.C. 103 as being unpatentable over Ganti (U.S. Patent Pub 20120158585) in view of Carrott (U.S. Patent Pub 20020069177)
Re claim 1: Ganti discloses:
A settlement card system, comprising: a plurality of settlement cards issued by a card issuer, each settlement card comprising one of a physical or virtual settlement card and each assigned to a specific card customer, each settlement card having security that locks the respective settlement card for authorized use with a single card specific merchant per transaction, and each settlement card having secure, stored settlement card data identifying a) the respective customer to which the settlement card is assigned, b) the card issuer, c) the card specific merchant, and d) a card payment service of the settlement card; (see Ganti Figure 1-5 +11)
a first computing system comprising a processor and memory operated by the card issuer, said processor configured to pull past financial transaction data and associated business data for the settlement card customer from public and private data sources and extract customer data features as decision values for each respective settlement card, said first computing system further comprising a rules database storing a set of transaction rules that are specific for each settlement card for a single transaction involving the respective settlement card, and a rules engine module operative with the rules database, wherein upon a single transaction by a customer involving its respective settlement card, the rules engine module retrieves from the rules database the current set of transaction rules specific for the settlement card and applies a machine learning approval model to the respective customer decision values using the retrieved set of transaction rules and determines a transaction monetary limit and customer payment terms for that current transaction; (see Ganti para 0054 +Figure 9 + Figure 11 item 1120 + Fig 7 item 710-740 + Figure 13 “traveltoday.com” is merchant + Figure 6 + Figure 2 item 230 + Fig 4 item 420 + fig 5 item 520)
a second computing system configured to receive from the card specific merchant the stored card data of the settlement card and an authorization request for approval of the transaction when the customer presents its settlement card to the card specific merchant to effect the transaction, wherein said second computing system is configured to identify the settlement card issuer and customer from the stored settlement card data and forward the authorization request to the first computing system, wherein the first computing system is and rules engine module determines if the transaction is within the monetary limit determined for the customer, and if no, reject the transaction, if yes, accept the transaction and determine customer payment terms for that transaction; (see Ganti para 0054 +Figure 9 + Figure 11 item 1120 + Fig 7 item 710-740 + Figure 13 “traveltoday.com” is merchant + Figure 6 + Figure 2 item 230 + Fig 4 item 420 + fig 5 item 520)
a third computing system operated by the card payment service, said third computing system configured to make payment to the authorized merchant for the transaction after receiving a payment authorization from the first computing system, and in response, the first computing system transfers a payment to the third computing system in the amount of the transaction; (see Ganti Figure 9 + Figure 11 item 1160-1190 + + Fig 7 item 740-750 + Figure 12 “accept” + Figure 1-4 + Figure 6 + fig 5 item 510)
said first computing system further comprising a cache associated with the processor and rules engine module, wherein the processor after a transaction involving the respective settlement card from the customer pulls recent financial transaction data and associated business data and processes the pulled data to update and form updated decision values associated with that respective customer settlement card and stores the updated decision values within the memory, and upon a subsequent single transaction by the customer involving its settlement card, the rules engine module: (see Ganti para 0055 + 0086 “single transaction rules” + 0105 +Figure 6 “620-p” = infinitive rules updated + Figure 7-9, 11 + Figure 12-14)
a) retrieves the set of transaction rules for the respective settlement card from the rules database, (see Ganti para 0054 +Figure 9 + Figure 11 item 1120 + Fig 7 item 710-740 + Figure 13 “traveltoday.com” is merchant + Figure 6 + Figure 2 item 230 + Fig 4 item 420 + fig 5 item 520)
b) caches the retrieved set of transaction rules within the cache, (see Ganti para 0054 +Figure 9 + Figure 11 item 1120 + Fig 7 item 710-740 + Figure 13 “traveltoday.com” is merchant + Figure 6 + Figure 2 item 230 + Fig 4 item 420 + fig 5 item 520)
c) retrieves the updated decision values from memory and stores the updated decision values within the cache, (see Ganti para 0055 + 0086 “single transaction rules” + 0105 +Figure 6 “620-p” = infinitive rules updated + Figure 7-9, 11 + Figure 12-14)
d) determines a new set of transaction rules that are optimized for the subsequent transaction of the customer based on updated decision values, (see Ganti para 0055 + 0086 “single transaction rules” + 0105 +Figure 6 “620-p” = infinitive rules updated + Figure 7-9, 11 + Figure 12-14)
e) applies the machine learning model to updated decision values using the new set of transaction rules that are optimized for the subsequent transaction to determine a new customer monetary limit and payment terms for the subsequent, single transaction of the settlement card by the customer, and (see Ganti Figure 8 + Figure 11 item 1130-1160 + + Fig 7 item 710-740 + Figure 12 + Figure 1-2 + Fig 4 item 430 + Figure 6 + fig 5 item 510)
f) stores the updated decision values within memory and the new set of transaction rules for the customer settlement card within the rules database. (see Ganti para 0055 + 0086 “single transaction rules” + 0105 +Figure 6 “620-p” = infinitive rules updated + Figure 7-9, 11 + Figure 12-14)
Although Ganti does not have rules selction explicitly, Carrott claims “Rules selction”
Therefore it would have been obvious to one of ordinary skill in the art at the effect filling date was made to modify Ganti by adapting any features of Carrott. See Carrott Figure 3 item 312-316.
It is clear that one would be motivated by the teaching in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention. Specifically, both Ganti teaches payment rules in Ganti Figure 6 that is adapted in Carrott system see Carrott Figure 3.
Although Ganti does not have rules selction explicitly, Carrott claims “Rules selction”
Therefore it would have been obvious to one of ordinary skill in the art at the effect filling date was made to modify Ganti by adapting any features of Carrott. See Carrott Figure 3 item 312-316.
It is clear that one would be motivated by the teaching in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention. Specifically, both Ganti teaches payment rules in Ganti Figure 6 that is adapted in Carrott system see Carrott Figure 3.
Re claim 7: see claim 1 +
wherein the third computing system comprises a server network having remote servers operated by the card payment service. (see Ganti Figure 9 + Figure 11 item 1160-1190 + + Fig 7 item 740-750 + Figure 12 “accept” + Figure 1-4 + Figure 6 + fig 5 item 510)
Re claim 8: see claim 1 +
wherein the rules engine module further comprises a reasoner inference engine that optimizes each set of new rules by applying a forward chaining model to the decision values based upon new inferences and applying an expert system as a backward chaining model to the decision values. (see Ganti para 0055 + 0086 “single transaction rules” + 0105 +Figure 6 “620-p” = infinitive rules updated + Figure 7-9, 11 + Figure 12-14)
Re claim 9: see claim 1 +
wherein the reasoner inference engine establishes a syntax tree for each set of new transaction rules. (see Ganti Figure 8 + Figure 11 item 1130-1160 + + Fig 7 item 710-740 + Figure 12 + Figure 1-2 + Fig 4 item 430 + Figure 6 + fig 5 item 510)
Re claim 10: see claim 1 +
wherein the rules engine module cashes the syntax tree that is updated each time the rules engine module applies the machine learning approval model and set of new transaction rules to updated decision values associated with a settlement card. (see Ganti Figure 8 + Figure 11 item 1130-1160 + + Fig 7 item 710-740 + Figure 12 + Figure 1-2 + Fig 4 item 430 + Figure 6 + fig 5 item 510)
Re claim 11: see claim 1 +
wherein said associated business data for the customer comprise a) behavior variables related to business transactions of the customer, b) social characteristics of the customer when interacting with the public, and c) business relationships of the customer with different companies. (see Ganti para 0054 +Figure 9 + Figure 11 item 1120 + Fig 7 item 710-740 + Figure 6 + Figure 2 item 230 + Fig 4 item 420 + fig 5 item 520)
Re claim 12: see claim 1 +
wherein said first computing system comprises a plurality of servers in a cloud network forming a machine learning network as an artificial neural network. (see Ganti para 0054 +Figure 9 + Figure 11 item 1120 + Fig 7 item 710-740 + Figure 6 + Figure 2 item 230 + Fig 4 item 420 + fig 5 item 520)
Re claim 13: see claim 1 +
wherein said rules database comprises a non-relational database that stores transaction rules parameterized in a structured JSON file. (see Ganti para 0054 +Figure 9 + Figure 11 item 1120 + Fig 7 item 710-740 + Figure 6 + Figure 2 item 230 + Fig 4 item 420 + fig 5 item 520)
Re claim 14: see claim 1 +
wherein said non-relational database is mounted on a database hosting service. (see Ganti Figure 3 item 320-325 + Fig 1-5)
Re claim 15: see claims above +
wherein said customer makes payment to the first computing system for the transaction based upon payment terms determined by the first computing system for that specific, single transaction. (see Ganti Figure 9 + Figure 11 item 1160-1190 + + Fig 7 item 740-750 + Figure 12 “accept” + Figure 1-4 + Figure 6 + fig 5 item 510)
Re claim 16: see claims above +
wherein said settlement card comprises a virtual settlement card. (see Ganti Figure 9 + Figure 11 item 1160-1190 + + Fig 7 item 740-750 + Figure 12 “accept” + Figure 1-4 + Figure 6 + fig 5 item 510)
Response to Arguments
Applicant’s arguments have been fully considered and are not persuasive. Answers to the arguments on the amended limitations which change the scope of the claims, will be addressed in the action above. Applicant's art arguments are considered moot due to new grounds of rejection.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Balko et al., U.S. Patent Pub 20130117747, discloses a computer implemented methods for reducing transaction load for process instance completion. One process includes identifying an end event triggered by an initial token of a process instance, determining a type of the end event, performing a search for additional tokens associated with the process instance that are distinct from the initial token, and performing a termination action based on the type of end event and a number of additional tokens identified in the search.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Kirsten Apple whose telephone number is (571)272-5588. The examiner can normally be reached on M-F 9-5.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Michael Anderson can be reached on (571) 270-0508. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/KIRSTEN S APPLE/Primary Examiner, Art Unit 3693
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