DETAILED ACTION
Acknowledgements
This Office Action is in response to Applicant’s response/application filed on 02/05/2026.
The Examiner notes that citations to United States Patent Application Publication paragraphs are formatted as [####], #### representing the paragraph number.
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 .
Status of Claims
Claims 1, 11 have been amended.
Claims 7-9, 17-19 have been canceled.
No claims have been added.
Claims 1-6, 10-16, 20-24 are currently pending and have been examined.
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.
As per claims 1-6, 10-16, 20-24, the claimed invention is directed to an abstract idea without significantly more because:
• Claim 1 recites:
receiving, by a receiver of a processing server, transaction data for a plurality of electronic transactions, where the transaction data includes at least a geographic location, a fraud determination and/or an approval determination, and one or more data values for the respective electronic transaction, wherein the plurality of electronic transactions include payment transactions from one or more payment networks and blockchain transactions from one or more blockchain networks;
identifying, by a processor of the processing server, a geographic location for each of the plurality of electronic transactions;
applying, by a processor of the processing server, a first rule of a plurality of rules to the plurality of electronic transactions to identify a first subset of the plurality of electronic transactions having a first geographic location that satisfy the first rule and include a fraud determination indicative of fraud;
filtering, by the processor of the processing server, the first subset of the plurality of electronic transactions having a first geographic location out of the plurality of electronic transactions;
repeating, by processor of the processing server, the application step and filtering step using additional rules of the plurality of rules until a threshold criterion is met; and
generating, by the processor of the processing server, a rule order for the first rule and the additional rules of the plurality of rules based on at least a size of the first subset of the plurality of electronic transactions having a first geographic location identified using the respective rule of the plurality of rules; and
repeating, by the processor of the processing server, the application step, the filtering step, the repeating step, and the generating step for a second subset of the plurality of the electronic transactions having a second geographic location,
wherein applying the first rule of the plurality of rules to the plurality of electronic transactions further identifies a third subset of the plurality of electronic transactions having the first geographic location that satisfy the first rule and include an approval determination indicative of approval,
wherein filtering the first subset of the plurality of electronic transactions out of the plurality of electronic transactions includes further filtering the third subset of the plurality of electronic transactions having the first geographic location out of the plurality of electronic transactions, and
wherein generating the rule order includes generating a fraud rule order for the first rule and the additional rules of the plurality of rules based on at least a size of the first subset of the plurality of electronic transactions having the first geographic location identified using the respective rule of the plurality of rules and generating an approval rule order for the first rule and the additional rules of the plurality of rules based on at least a size of the third subset of the plurality of electronic transactions having the first geographic location identified using the respective rule of the plurality of rules.
• Under Step 1 of the Section 101 analysis, the claim(s) is/are directed to a method, a system, and a manufacture, which are statutory categories of invention.
• Under Step 2A Prong One of the 2019 Revised Patent Subject Matter Eligiblity Guidance, the claimed invention as drafted includes language (see underlined language above) that recites an abstract idea of applying rules to a plurality of transactions to filter transactions and generating a rule order based on the size of the filtered transactions (a certain method of organizing human activity such as a commercial or legal interactions) but for the recitation of additional claim elements, because it is common to analyze transaction information to prevent fraud in sales activities/behaviors. Claims 11 recites similar abstract idea. That is, other than reciting “receiver”, “processing server”, “processor”, nothing in the claim precludes the language from being considered as performed by a person.
• Under Step 2A Prong Two of the 2019 Revised Patent Subject Matter Eligiblity Guidance, the additional claim element(s), considered individually, do not apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception and in a manner that integrates the exception into a practical application of the exception. The additional claim elements(s) merely add the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. For example, the additional elements of “receiver”, “processing server”, “processor”, merely use a generic computer device and/or generic computer components as a tool to perform an abstract idea.
• Under Step 2A Prong Two, the additional claim element(s), considered in combination, do not apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception and in a manner that integrates the exception into a practical application of the exception. The combination of elements is no more than the sum of their parts. Unlike the eligible claims in Diehr and Bascom, in which the elements limiting the exception taken together improve a technical field, the instant claim lacks an improvement to the functioning of a computer or to any other technology or technical field.
• Under Step 2B, the additional claim element(s), considered individually and in combination, do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself for similar reasons outlined under Step 2A Prong Two.
A similar analysis can be applied to dependent claims 2, 5-6, 12, 15-16, 21-24 which further recite the abstract idea without any extra additional elements.
A similar analysis can be applied to dependent claims 3, 4, 10, 13, 14, 20, which include additional claim elements that merely add the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. For example, “transmitter”. Furthermore, the additional claim elements(s) such as “blockchain”, “cryptocurrency” generally link the use of the judicial exception to a particular technological environment or field of use of blockchain.
Therefore, claims 1-6, 10-16, 20-24 are rejected under 35 U.S.C. §101.
Claim Rejections - 35 USC § 103
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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103(a) 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.
Claim(s) 1-4, 6, 10-14, 16, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Qu (US 20220391911), in view of Vijayaraghavan (US 20230035321), further in view of Lee (US 20220405477).
Regarding claim(s) 1 and 11, Qu discloses:
a receiver receiving transaction data for a plurality of electronic transactions, where the transaction data includes at least a geographic location, a fraud determination and one or more data values for the respective electronic transaction (By disclosing, “historical transaction data is received by a transaction service provider system 110 (block 302). The historical transaction data may include one or more transactions associated with an issuer system 102 during a period of time.” ([0095], Fig. 3-4); “According to some non-limiting embodiments described herein, at the outset, rule sets may be generated based on one or more identifiable factors (e.g., whether transactions occur at certain times during the day, whether the transactions occur in a particular location, and/or the like).” ([0075], [0096], [0100]); “The transaction service provider system 110 may tag or otherwise associate an indication that each transaction associated with the historical transaction data was non-fraudulent and/or fraudulent (block 306)” ([0098], Fig. 3); and “the merchant system 108 may communicate transaction data to the transaction service provider system 110, including transaction parameters associated with transactions initiated by the user device 104. Non-limiting examples of transaction parameters include a personal account number (PAN), a transaction amount, a transaction date and/or time, a conversion rate of currency, a merchant type, a merchant identification number, a type of currency, and/or the like.” ([0080]); and
a processor
applying a first rule of a plurality of rules to the plurality of electronic transactions to identify a first subset of the plurality of electronic transactions that satisfy the first rule and include a fraud determination indicative of fraud (By disclosing, “determine at least one primary rule and at least one set of secondary rules associated with the at least one primary rule [(first rule)] based on relationships between correlated features associated with the plurality of non-fraudulent transactions and the plurality of fraudulent transactions,”; “According to some non-limiting embodiments described herein, at the outset, rule sets may be generated based on one or more identifiable factors (e.g., whether transactions occur at certain times during the day, whether the transactions occur in a particular location, and/or the like). The rule sets may then be analyzed, and sub-rule sets therefrom selected that efficiency and accurately identify non-fraudulent and fraudulent transaction data.” ([0013], [0075], [0087], [0099]-[0100], [0107]-[0108], Fig. 3-4));
filtering the first subset of the plurality of electronic transactions out of the plurality of electronic transactions; repeating the application step and filtering step using additional rules of the plurality of rules until a threshold criterion is met (By disclosing, “The initial set of decision trees may include decision trees, each of which include a root node to be associated with a primary rule and one or more child nodes operably coupled to the root node, the child nodes associated with unique secondary rules [(additional rules)]….the transaction service provider system may identify additional correlations across feature values associated with transactions identified as possibly and/or likely fraudulent when compared in view of the classification of transactions by a primary rule, these additional correlations identified as secondary rules” ([0099]-[0103], [0107]-[0108], Fig. 3-4); and “a depth limit may be set to a predetermined depth [(threshold criterion)] (e.g., decision trees may be generated and/or initialized as having seven or fewer decision levels (parent/child groups), and/or the like). This depth limit may be determined based on the amount of transactions associated with the historical transaction data, a predetermined limit, and/or a limit set by a user providing input at the issuer system 102 and/or the transaction service provider system 110.” ([0099]));
generating a rule order for the first rule and the additional rules of the plurality of rules based on at least a size of the first subset of the plurality of electronic transactions identified using the respective rule of the plurality of rules (By disclosing, “The final rules may then be ordered (block 316) …While the ordering of final rules is determined to be inefficient, either by not having analyzed the portion of the historical data in a predetermined amount of time (as a fixed amount of time or ratio of time to transaction data volume) and/or by having too high of an error rate when characterizing the transactions (“NO” at block 318), the ordering of final rules is altered (block 316). For example, the ordering of the final rules may be randomly shuffled or final rules associated with a higher classification error rate than final rules with a lower classification error rate may be placed lower in the ordering and/or removed altogether from the ordering.” ([0102]-[0104], [0107]-[0108], Fig. 3-4)); and
repeating, by the processor of the processing server, the application step ([0013], [0075], [0087], [0099]-[0100], [0107]-[0108], Fig. 3-4), the filtering step ([0099]-[0103], [0107]-[0108], Fig. 3-4), the repeating step ([0099]-[0103], [0107]-[0108], Fig. 3-4), and the generating step ([0102]-[0104], [0107]-[0108], Fig. 3-4) for a second subset of the plurality of the electronic transactions having a second geographic location,
wherein applying the first rule of the plurality of rules to the plurality of electronic transactions further identifies a third subset of the plurality of electronic transactions having the first geographic location that satisfy the first rule and include a fraud determination indicative of approval,(By disclosing, “According to some non-limiting embodiments described herein, at the outset, rule sets may be generated based on one or more identifiable factors (e.g., whether transactions occur at certain times during the day, whether the transactions occur in a particular location, and/or the like). The rule sets may then be analyzed, and sub-rule sets therefrom selected that efficiency and accurately identify non-fraudulent and fraudulent transaction data.” ([0075]); “The transaction service provider system 110 may tag or otherwise associate an indication that each transaction associated with the historical transaction data was non-fraudulent and/or fraudulent (block 306).” ([0098]); “If the transactions are classified as non-fraudulent transactions when compared to the first subset of final rules, the transactions may be approved without comparison to the transaction to the second subset of final rules.” ([0105])).
Qu does not expressly disclose, but Vijayaraghavan teaches:
the plurality of electronic transactions include payment transactions from one or more payment networks and blockchain transactions from one or more blockchain networks (By disclosing, “Subsequently, at process flow 304A-B, updates made to the transaction identified and stored in the one or more blockchain networks (e.g., blockchain network for transaction events and disputes 372) may be observed and/or received by state observer 354 and 382 [(acquirer and issuer payment networks)], respectively.” ([0081], Fig. 3A); and “In some embodiments, the state observers may periodically or continually retrieve the latest data of stored in one or more of the blockchain networks and/or the shared ledgers of the one or more of the blockchain networks (e.g., shared ledger 216A, shared ledger 212A, and shared ledger 218A)” ([0060]));
identifying, by a processor, a geographic location for each of the plurality of electronic transactions; filtering the first subset of the plurality of electronic transactions having a first geographic location out of the plurality of electronic transactions; and further filtering a subset of the plurality of electronic transactions having a first geographic location out of the plurality of electronic transactions (By disclosing, “For example, the attributes of the transaction may include, but are not limited to, e.g., …, geographical and/or temporal information of the transaction 604E” ([0144], Fig. 6A); “Step 610 may include searching one or more blockchain networks (e.g., blockchain network for transaction events and disputes) and/or their shared ledgers for one or more other transactions involving one or more of the selected attribute(s) and/or dispute information.” ([0147]-[0148])).
Therefore, it would have been obvious to one of ordinary skill in the art at the effective filing date of the present application to modify the invention of Qu in view of Vijayaraghavan to include receiving electronic transactions include payment transactions from one or more payment networks and blockchain transactions from one or more blockchain networks; identifying, by a processor, a geographic location for each of the plurality of electronic transactions; filtering the first subset of the plurality of electronic transactions having a first geographic location out of the plurality of electronic transactions; and further filtering a subset of the plurality of electronic transactions having a first geographic location out of the plurality of electronic transactions. Doing so would result in an improved invention because this would allow the system to analyze the transactions based on geographic location, thus improving the functionality of the claimed invention.
Qu in view of Vijayaraghavan does not expressly disclose, but Lee teaches:
generating an approval rule order; and an approval determination indicative of approval.(By disclosing, “The authorizer server 160 conducts 380 a real-time transaction approval process for the pending transaction using the transaction rule, the parsed data fields, and the reduced volume of data. …. The authorizer server 160 in turn determines the nature of the transaction and provides an approval or denial of the transaction” ([0056] of Lee)).
Therefore, it would have been obvious to one of ordinary skill in the art at the effective filing date of the present application to modify the invention of Qu and Vijayaraghavan, in view of Lee to include generating an approval rule order; and an approval determination indicative of approval. Doing so would result in an improved invention because this would increase the accuracy of identifying fraudulent transaction when the transactions are identified non-fraudulent at a first step.
Regarding claim(s) 2 and 12, Qu discloses:
receiving, by the receiver of the processing server, transaction data for a new electronic transaction; and applying, by the processor of the processing server, the first rule and the additional rules of the plurality of rules to the new transaction data using the generated rule order to generate a new fraud determination for the new electronic transaction (By disclosing, “determining a subset of rule sets from the ordered plurality of rule sets against which subsequently received transactions are compared against to determine if the subsequent transactions are fraudulent” (Abstract and claim 2)).
Regarding claim(s) 3 and 13, Qu discloses:
determining, by the processing server, the new electronic transaction is fraudulent based on the application of the first rule and the additional rules of the plurality of rules (By disclosing, “once the set of final rules are selected for activation, the issuer system 102 and/or the transaction service provider system 110 may compare subsequently-received transactions to the selected set of final rules and classify the subsequently-received transactions as non-fraudulent transactions or fraudulent transactions. Once classified, the issuer system 102 and/or the transaction service provider system 110 may approve or deny the subsequently-received transactions based on the classification.” ([0104], [0003])); and
transmitting, by a transmitter of the processing server, the fraud determination to a third-party for approval or denial and/or one or more parties of the new electronic transaction (By disclosing, “In some non-limiting embodiments, the merchant system 108 may communicate with the transaction service provider system 110 to process a transaction and, more particularly, initiate a transaction by transmitting a transaction authorization request generated during a transaction to the transaction service provider system 110. … The merchant system 108 may receive a response code from the transaction service provider system 110 including an indication that the transaction is approved and/or disapproved, stolen, not to be honored, partially approved, is for an amount exceeding a maximum permitted amount, is associated with an account having insufficient funds, included an incorrect PIN, and/or the like.” ([0080])).
Regarding claim(s) 4 and 14, Qu discloses:
determining, by the processing server, the new electronic transaction is not fraudulent based on the application of the first rule and the additional rules of the plurality of rules (By disclosing, “once the set of final rules are selected for activation, the issuer system 102 and/or the transaction service provider system 110 may compare subsequently-received transactions to the selected set of final rules and classify the subsequently-received transactions as non-fraudulent transactions or fraudulent transactions. Once classified, the issuer system 102 and/or the transaction service provider system 110 may approve or deny the subsequently-received transactions based on the classification.” ([0104], [0003])); and
transmitting, by a transmitter of the processing server, the fraud determination to a third-party for approval or denial one or more parties of the new electronic transaction (By disclosing, “In some non-limiting embodiments, the merchant system 108 may communicate with the transaction service provider system 110 to process a transaction and, more particularly, initiate a transaction by transmitting a transaction authorization request generated during a transaction to the transaction service provider system 110. … The merchant system 108 may receive a response code from the transaction service provider system 110 including an indication that the transaction is approved and/or disapproved, stolen, not to be honored, partially approved, is for an amount exceeding a maximum permitted amount, is associated with an account having insufficient funds, included an incorrect PIN, and/or the like.” ([0080])).
Regarding claim(s) 6 and 16, Qu discloses:
wherein the threshold criteria is a fraud rate for identification of electronic transactions with a positive fraud determination based on a percentage of electronic transactions filtered out from the plurality of electronic transactions (By disclosing, “In some non-limiting embodiments, each node of the decision trees, and by extension each corresponding primary and/or secondary rule associated with each node, may be evaluated (either in isolation or based on classifications of earlier nodes) to determine one or more efficiency characteristics associated with classification of transactions with each node. …. Evaluation may include determining that a given node accurately classifies transactions as either fraudulent or non-fraudulent beyond a predetermined threshold (e.g., with inaccurate identifications accounting for less than a predetermined threshold), the ratio of accurate identifications to inaccurate identifications exceeds a predetermined threshold, and/or that a given node has a false-positive identification rate less than a predetermined false-positive threshold.” ([0102]-[0103])).
Regarding claim(s) 10 and 20, Qu does not disclose, but Vijayaraghavan teaches:
wherein the electronic transactions are cryptographic currency transactions processed via a blockchain (By disclosing, “A blockchain network for settlement 704A may be a real time gross settlement system that records the final transfer of funds, tokens, currency, or cryptocurrency between transacting parties (e.g., issuer 712A and merchant 712B).” ([0152])).
Therefore, it would have been obvious to one of ordinary skill in the art at in view of Vijayaraghavan to include techniques of wherein the electronic transactions are cryptographic currency transactions processed via a blockchain. Doing so would result in an improved invention because this would classify not only the traditional transaction, but also the blockchain transactions, thus extending the scope of the invention.
Claim(s) 5, 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Qu (US 20220391911), in view of Vijayaraghavan (US 20230035321), further in view of Lee (US 20220405477), and Fu (CN 107276805 A).
Regarding claim(s) 5 and 15, Qu does not disclose, but Fu teaches:
wherein the threshold criteria is a number of electronic transactions remaining in the plurality of electronic transactions being below a predetermined threshold value (By disclosing, “a fourth judgment module, used for when the judging result of the third judging module is negative, using the pure cluster judging rule, judging all samples in the cluster whether all belong to the same type, if it is determined that the sub all samples in the cluster are belonging to the same category, then the samples in the cluster from the initial training sample set, if it is determined that all the samples in the cluster does not belong to the same category, then updating the cluster as a second cluster, returning to using the clustering algorithm. performing clustering in the sample to obtain the step of second predetermined number of sub clusters, until judging each sub-cluster in the second cluster number of samples is less than the first preset threshold.” ([0063] of Fu)).
Therefore, it would have been obvious to one of ordinary skill in the art at the effective filing date of the present application to modify the invention of Qu, Vijayaraghavan and Lee, in view of Fu to include techniques of wherein the threshold criteria is a number of electronic transactions remaining in the plurality of electronic transactions being below a predetermined threshold value. Doing so would result in an improved invention because this would allow the sample of the historical transactions to be fully analyzed.
Claim(s) 21-24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Qu (US 20220391911), in view of Vijayaraghavan (US 20230035321), further in view of Lee (US 20220405477), and Ganti (US 20120158540).
Regarding claim(s) 21 and 23, Qu discloses:
receiving, by the receiver of the processing server, transaction data for a new electronic transaction; applying, by the processor of the processing server, the first rule and the additional rules of the plurality of rules to the new transaction data using the generated fraud rule order to generate a new fraud determination for the new electronic transaction; applying, by the processor of the processing server, the first rule and the additional rules of the plurality of rules to the new transaction data using the generated approval rule order to generate a new approval determination for the new electronic transaction (By disclosing, “In some non-limiting aspects or embodiments, once the set of final rules are selected for activation, the issuer system 102 and/or the transaction service provider system 110 may compare subsequently-received transactions to the selected set of final rules and classify the subsequently-received transactions as non-fraudulent transactions or fraudulent transactions” ([0104]));
Qu does not disclose, but Ganti teaches:
transmitting, by a transmitter of the processing server, the fraud determination and the approval determination to a third-party and/or one or more parties of the new electronic transaction for approval or denial (By disclosing, “ The fraud management system may generate fraud information for the transactions and may output the fraud information to merchants A and B to inform merchants A and B whether the transactions potentially involved fraud. The fraud information may take the form of a fraud score or may take the form of an "accept" alert (meaning that the transaction is not fraudulent) or a "reject" alert (meaning that the transaction is potentially fraudulent). Merchants A and B may then decide whether to permit or deny the transaction, or proceed to fulfill the goods or services secured in the transaction, based on the fraud information.” ([0019] of Ganti)).
Therefore, it would have been obvious to one of ordinary skill in the art at the effective filing date of the present application to modify the Invention of Qu, Vijayaraghavan, and Lee in view of Ganti to include transmitting, by a transmitter of the processing server, the fraud determination and the approval determination to a third-party and/or one or more parties of the new electronic transaction for approval or denial. Doing so would result in an improved invention because this would allow the third party to make a decision by themselves based on the fraud determination.
Regarding claim(s) 21 and 24, Qu discloses:
receiving, by the receiver of the processing server, transaction data for a new electronic transaction; applying, by the processor of the processing server, the first rule and the additional rules of the plurality of rules to the new transaction data using the generated fraud rule order to generate a new fraud determination for the new electronic transaction (By disclosing, “In some non-limiting aspects or embodiments, once the set of final rules are selected for activation, the issuer system 102 and/or the transaction service provider system 110 may compare subsequently-received transactions to the selected set of final rules and classify the subsequently-received transactions as non-fraudulent transactions or fraudulent transactions” ([0104]));
applying, by the processor of the processing server, the first rule and the additional rules of the plurality of rules to the new transaction data using the generated approval rule order to generate a new approval determination for the new electronic transaction (By disclosing, “In some non-limiting aspects or embodiments, the set of final rules may be subdivided into one or more subsets of final rules and the subsequently-received transactions compared to the subsets of final rules in a multi-pass approach. For example, the set of final rules may be divided into first and second subsets of final rules. As transactions are received, the transactions may be compared to the first subset of final rules. If the transactions are classified as non-fraudulent transactions when compared to the first subset of final rules, the transactions may be approved without comparison to the transaction to the second subset of final rules. However, in some non-limiting aspects or embodiments, when comparison of transactions to the first subset of final rules results in a classification of the transactions as fraudulent, the transactions may be compared to the second subset of final rules. If upon comparison the transactions remain classified as fraudulent transactions, the transactions may be denied. However, if upon comparison the transaction is classified as non-fraudulent transactions, the transactions may be approved.” ([0105])).
Qu does not disclose, but Ganti teaches:
determining, by the processing server, an overall score based on the fraud determination and the approval determination; and transmitting, by a transmitter of the processing server, the overall score to a third-party and/or one or more parties of the new electronic transaction for approval or denial. (By disclosing, “ The fraud management system may generate fraud information for the transactions and may output the fraud information to merchants A and B to inform merchants A and B whether the transactions potentially involved fraud. The fraud information may take the form of a fraud score or may take the form of an "accept" alert (meaning that the transaction is not fraudulent) or a "reject" alert (meaning that the transaction is potentially fraudulent). Merchants A and B may then decide whether to permit or deny the transaction, or proceed to fulfill the goods or services secured in the transaction, based on the fraud information.” ([0019] of Ganti)).
Therefore, it would have been obvious to one of ordinary skill in the art at the effective filing date of the present application to modify the Invention of Qu, Vijayaraghavan and Lee, in view of Ganti to include determining, by the processing server, an overall score based on the fraud determination and the approval determination; and transmitting, by a transmitter of the processing server, the overall score to a third-party and/or one or more parties of the new electronic transaction for approval or denial. Doing so would result in an improved invention because this would allow the third party to make a decision by themselves based on the fraud determination.
Response to Arguments
Applicant’s arguments with regard to the 35 U.S.C. § 101 rejection have been considered but are not persuasive.
The Applicant argues that the claims are patent eligible because the claims recite a practical application.
The Examiner, respectfully disagrees. The Examiner notes that:
the functions recited in the claim such as “receiving…”, “identifying…”, “applying…”, “filtering…”, “repeating…”, “generating…”, “repeating…” are generic computer functions that can be performed by generic computers;
the functions recited in the claim can also performed manually without any additional elements; and
even if the functions recited in the claim are performed by generic computers and/or generic computer components, generic computers and/or generic computer components are used as a tool to perform the functions. The use of generic computers and/or generic computer components as a tool to implement the functions does not integrate the abstract idea into a practical application because it requires no more than a computer and/or network performing functions that correspond to acts required to carry out the abstract idea.
Accordingly, the present rejection under section 101 will be maintained.
Applicant’s arguments with regard to the 35 U.S.C. § 103 rejection have been considered but are moot in view of new grounds of rejection initiated by applicant’s amendment to the claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 10607228 to Gai for disclosing:
A dynamic rule strategy and fraud detection method for detecting fraud trends is provided. The method includes storing captured transaction data in at least one data warehouse and utilizing a computer server including at least one processor for performing multiple steps. The steps include continuously monitoring the captured transaction data for detecting a concentration of fraud attacks in selected segments; receiving, the selected segments identified and developing a set of fraud detection rules based on the selected segments; and validating and implementing the fraud detection rules.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DUAN ZHANG whose telephone number is (571)272-4642. The examiner can normally be reached Mon - Fri 10 AM-5 PM.
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, Neha Patel can be reached on 571-270-1492. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/DUAN ZHANG/Primary Examiner, Art Unit 3699