DETAILED ACTION
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 .
Claim Rejections - 35 USC § 112
Claim 1, 17 and 19 and (3-16) are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. In the claims the additional component of a “authenticated communication channel” is not described. The dependent claims are rejected based on their dependencies
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 20 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the claims read on a transitory signal.
Claims 1, 3-16 , 17 and 19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) the abstract idea of generating a credit score . This judicial exception is not integrated into a practical application and is not sufficient to amount to significantly more than the judicial exception for the reasons that follow.
Eligibility Analysis, Step 1
Regarding claims 1-20 the claims are each directed to one of the four statutory categories of invention, namely a method, system and computer readable medium. As such, the analysis proceeds to Step 2. The 2019 Patent Subject Matter Eligibility Guidance (“2019 PEG”) sets forth a revised Step 2A analysis which includes a two-prong inquiry.
Eligibility Analysis, Step 2A Prong One
Prong one consists of determining if the claims recite a judicial exception, which includes abstract ideas, laws of nature, and natural phenomenon. Groupings of abstract ideas may include mathematical concepts, mental processes, and certain methods of organizing human activity. Here, representative independent claim 1 recites the following:
collecting, via a data collection system, social network data from one or more social networks, wherein the data collection system is configured to automatically extract the social network data using platform-specific queries;receiving, from a computing device, a credit voucher from a first entity of the one or more social networks, wherein the credit voucher assigns a first credit score to a second entity of the one or more social networks;
analyzing, via the data collection system, the social network data to identify a key actor within a community of the one or more social networks based on one or more measurable engagement metrics comprising a follower count, an engagement rate, a posting rate, a comment rate, or a combination thereof;
sending, via a community-based credit evaluation system and via an authenticated communication channel, a credit-vouching request to the key actor to assign a second credit score to the second entity of the one or more social networks;
receiving, from the key actor and via the authenticated communication channel, a second credit voucher that assigns the second credit score to the second entity;
generating a community-based credit score for the second entity of the one or more social networks based on an analysis of the social network data, [[and]] the first credit score, and the second credit score;
receiving, via an application programming interface (API), a request for the community- based credit score sent by a request or requesting computing device; and providing, via the API, the community-based credit score to the request or requesting computing device.
The bolded steps A), B), C), D) , E) and F) above describe a fundamental economic practice, commercial interactions, and managing interactions between people, and therefore a certain method of organizing human activity. Further, the limitations, as drafted, describe a process that, under its broadest reasonable interpretation, covers performance of the limitation by a human analog but for the recitation of generic computer components. That is, other than the data collection system, nothing in the claims precludes the steps from practically being performed by a human analog. For example, but for this language, the claim encompasses generating a credit score - a human analog. Here, the mere nominal recitation of the generic computer components does not take the claim limitation out of the “certain methods of organizing human activity” grouping. As such, the claims recite an abstract idea under prong one. The analysis proceeds to Step 2A Prong Two.
Eligibility Analysis, Step 2A Prong Two
Prong two consists of determining whether the claim recites additional elements that integrate the judicial exception into a practical application. The claim recites the following additional elements:
1) a data collection system
2) the API
3) requesting computing device
4) a requesting channel
The additional element in the claims amount to no more than mere instructions to apply the exception using generic computer components. They do not integrate the judicial exception into a practical application because they do not impose any meaningful limits on practicing the abstract idea. As such, the claims are directed to the abstract idea. The analysis proceeds to Step 2B.
Eligibility Analysis, Step 2B
Step 2B consists of determining whether the claim provides an inventive concept by considering whether the additional elements go beyond what is well-understood, routine, and conventional activity.
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106; see also USPTO: July 2015 Update: Subject Matter Eligibility):
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) (“Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result‐‐a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink.” (emphasis added));
ii. Performing repetitive calculations, Flook, 437 U.S. at 594, 198 USPQ2d at 199 (recomputing or readjusting alarm limit values); Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012) (“The computer required by some of Bancorp’s claims is employed only for its most basic function, the performance of repetitive calculations, and as such does not impose meaningful limits on the scope of those claims.”);
iii. Electronic recordkeeping, Alice Corp., 134 S. Ct. at 2359, 110 USPQ2d at 1984 (creating and maintaining “shadow accounts”); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log);
iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93;
In the case of the instant claims, the generic application of the computing device similarly does not make the invention patent-eligible. Note that the disclosure recites general computer products which are suitable to perform the claimed method (see eg. para. 0048). Moreover, the specification does not contribute any technically-specific computer algorithm or code, but rather merely states that the claimed steps may be performed by the generic modules with the expectation that one of ordinary skill in the art would be capable of implementation without further instruction. The use of computing devices in this manner is merely what computers do, ie. performing repetitive calculations, receiving, processing, and storing data, and automating mental tasks, and does not change the analysis. Whilst the implementation of such a solution may include the use of generic technical features, these merely serve their well-understood functions as would be recognized by one of ordinary skill in the art in the technical field under consideration. As such, the claims' invocation of the computer merely amounts to the limiting of the use of the abstract idea to a particular technological environment.
Here, the involvement of the generic computer products does not amount to significantly more than the abstract idea because the mere recitation of a generic computer cannot transform a patent-eligible abstract idea into a patent-eligible invention. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. The computer components are recited at a high level of generality and are recited as performing generic computer functions routinely used in computer applications. Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system. The use of generic computer components in this manner does not impose any meaningful limit on the computer implementation of the abstract idea. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation.
As discussed with respect to Step 2A Prong Two, the additional elements in the claims amount to no more than mere instructions to apply the exception using generic computer components. The additional elements are recited at a high level of generality, as discussed above. The same analysis applies here in Step 2B, i.e., mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Independent claims 17 and 19 recite substantially similar limitations as independent claim 1 and is rejected accordingly. Dependent claims 3-10, 13-16, do not remedy the deficiencies of the independent claims and are rejected accordingly. In this case, all claims have been reviewed and are found to be substantially similar and linked to the same abstract idea (see Content Extraction and Transmission LLC v. Wells Fargo (Fed. Cir. 2014)
Claims 11-12 include a distributed ledger but this additional component is claimed and described at a high level of generality and are recited as performing generic computer functions routinely used in blockchains. Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system.
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.
Claim(s) 1,3-6,9-10,13,15-20 are rejected under 35 U.S.C. 103 as being unpatentable over Malek 20200286167 in view of Mawji 20160277424 and Stewart 20130185189.
As to claims 1, 17 and a method and system and computer readable medium, comprising:
collecting, via a data collection system, social network data from one or more social networks; wherein the data collection system is configured to automatically extract the social network data using platform-specific queries. See Figure 1 p[0136] a first processor receiving name of a first person from a first social website; said first processor receiving a first score for said first person related to said first social website, from said first social website; wherein said first score for said first person related to said first social website is related to risk factor, reputation, reliability, credibility, and creditworthiness of said first person; wherein said first score for said first person is obtained from a subset of members of said first social website who are directly connected to or befriended with said first person, based on said risk factor, reputation, reliability, credibility, and creditworthiness of said first person, produced through a second processor at said first social website.
Receiving from a computing device a credit voucher from a first entity of the one or more social networks, wherein the credit voucher assigns a credit score to a second entity of the one or more social networks wherein the credit voucher assigns a first credit score to a second entity of the one or more social networks; [0136] wherein said first score for said first person related to said first social website is related to risk factor, reputation, reliability, credibility, and creditworthiness of said first person; wherein said first score for said first person is obtained from a subset of members of said first social website who are directly connected to or befriended with said first person, based on said risk factor, reputation, reliability, credibility, and creditworthiness of said first person, produced through a second processor at said first social website. [0048] In one embodiment, one can see how much his friend has borrowed in the past year from all friends/family/circle. The score/report/history/performance/opinions can also be sold to others or as subscription or as per request. Of course, the person who needs the loan would waive/permit for such a disclosure, beforehand, with no liability for bad score. [0141] combining or supplementing a second score from a third social website with said first score. [0157] vouching for a friend on said first social website
analyzing, via the data collection system, the social network data to identify a key actor within a community of the one or more social networks based on one or more measurable engagement metrics comprising a follower count, an engagement rate, a posting rate, a comment rate, or a combination thereof; [0032] where key actors read on family / friends etc. [0194] From the get-go, a member can ask family and friends to rate him in this regard, in advance of any loans being discussed. This could be all or a select few friends, who make such ratings or provide references. Their identities are verified, and their comments can be altered or removed by them or by either party. This is to serve as building blocks of a reputation based on which future transactions can be decided, as an example sending a credit vouching request to the key actor to assign the credit score to the second entity; and
receiving from the key actor the credit voucher based on the credit vouching request, wherein the first entity comprises the key actor. [195] A person cannot see who said what in rating them, as an example. Only they can see a final rating. In the alternative, Mawji teaches of identifying a key actor (a person or entity that the system finds to be credentialed to opine. See Mawji [0009] It would have been obvious to one skilled in the art at the time to have combines to two related refences to find the person most suitable (Key Actor) to rate the credit worthiness as so called “references” most suitable to define the character of the borrower is a common factor in the art of lending.
sending, via a community-based credit evaluation system and via an authenticated communication channel, a credit-vouching request to the key actor to assign a second credit score to the second entity of the one or more social networks; [0032] where key actors read on family / friends etc. and/or Sewart [0010] When the connections between participants of online social networking services are mapped, a social networking graph results (herein after referred to as "social graph"). Social graph is a term ascribed to scientists working in the social areas of graph theory. Coupling the abstract concept from discrete mathematics of a graph with the relationships between individuals online, the social links a person has can be traced through the Internet activity. The social graph is geared toward the relationships a person has online as opposed to the relationships in the real world, which describes the concept of a social network. It would have been obvious to use the tools of Stewart to Identify Key as both references are directed to a common goal of finding the person best to rate the credit worthiness of a borrower.
receiving, from the key actor and via the authenticated communication channel, a second credit voucher that assigns the second credit score to the second entity; 0032] where key actors read on family / friends etc.
generating a community-based credit score for the second entity of the one or more social networks based on an analysis of the social network data, [[and]] the first credit score, and the second credit score;
; [0136] aid first processor receiving a first score [0138] Other options/variations are: [0139] getting FICO score or another equivalent score from a bank or credit card company. [0140] combining or supplementing FICO score or another equivalent score from a bank or credit card company with said first score. In the alternative, Steward teaches the step of identifying community members via a social graph. Stewart [0010] When the connections between participants of online social networking services are mapped, a social networking graph results (herein after referred to as "social graph"). Social graph is a term ascribed to scientists working in the social areas of graph theory. Coupling the abstract concept from discrete mathematics of a graph with the relationships between individuals online, the social links a person has can be traced through the Internet activity. The social graph is geared toward the relationships a person has online as opposed to the relationships in the real world, which describes the concept of a social network.
providing the community-based credit score to the requestor. [0194] [0194] From the get-go, a member can ask family and friends to rate him in this regard, in advance of any loans being discussed. This could be all or a select few friends, who make such ratings or provide references. Their identities are verified, and their comments can be altered or removed by them or by either party. This is to serve as building blocks of a reputation based on which future transactions can be decided, as an example.
The reference fails to expressly teach the step of:
receiving, via an application programming interface (API), a request for the community- based credit score sent by a request a requesting computing device; and
providing, via the API, the community-based credit score sent by a requesting computing device.; It does however teach the following p[0137] second person or entity responding to said request by said first person, regarding said line of credit or loan through said second website; said second person or entity negotiating terms and conditions of said line of credit or loan with said first person, through said second website; both said first person and said second person or entity accepting said negotiated terms and conditions of said line of credit or loan, through said second website; said first person receiving said line of credit or loan, from said second person or entity; said second processor calculating and updating said first score for said first person, based on performance of said first person on said received line of credit or loan, with respect to said negotiated terms and conditions of said line of credit or loan. The second processor reporting said updated first score for said first person and said performance of said first person on said received line of credit or loan, to said first social website or to some or selected members of said first social website.
It would have been obvious to one skilled in the art to have included a step where the lender requests the score of the borrower as this is the art recognized equivalent to having the lender have access to the score without an express step of requesting it.
The reference fails to tech of step of claim 3. The method of claim 1, wherein analyzing the social network data to identify the key actor comprises identifying the key actor based on a follower count, an engagement rate, a posting rate, and a comment rate [0050] For example, if somebody has a good reputation and high score, [0103] So, for example, the borrower offers a few reputable friends or peers as references, and in case of an agreed upon degree of default on loan repayment, the same peers will be notified, thus, the borrower losing face with them. Or, he can offer all his friends on FaceBook or Twitter or Linkedin or other social media or his contacts on his smartphone or all of the above or a few of the above, as a subset. These contacts can be notified in a variety of ways. It would have been obvious to one skilled in the art at the time to seek a credit score from a family member or the like based on the factors claimed as each is a well known factor by which to weigh the merit of a poster on a social network system and the use thereof for their intended purpose (credibility) is obvious.
4. The method of claim 1, wherein generating the community-based credit score for the second entity based on the analysis of the social network comprises:
generating a social network credit score based on the analysis of the social network; and
combining, via a weighing equation, the social network credit score with the first credit score to derive a combined weighted credit score, wherein the community-based credit score comprises the combined weighted credit score. [0138] Other options/variations are: [0139] getting FICO score or another equivalent score from a bank or credit card company. [0140] combining or supplementing FICO score or another equivalent score from a bank or credit card company with said first score
5. The method of claim 4, wherein generating the social network credit score based on the analysis of the social network comprises analyzing a monetary transaction and a non-monetary transaction to determine the social network credit score. p[104][129]
6. The method of claim 5, wherein analyzing the monetary and a non-monetary transaction to determine the social network credit score comprises analyzing the non-monetary transaction to derive a monetary value and combining the monetary value with the monetary transaction to determine the social network credit score. [0164] 0164] So, the general idea is to have a reputation-based lending and borrowing platform for money, and many more items in the future, including cars, furniture, and useful stuff that is sitting in storage/garage/attic most of the year. Other alternatives to the “StreetCred” name may be “Reputation”, “Rep”, or “StreetRep”. So, you can carry your reputation, and that enables many things happen, which otherwise, would not be possible, as described here. [0157] vouching for a friend on said first social website.
9. The method of claim 1, wherein the social network data includes at least one of a social network post, a social network comment, a social network like, a share, a group membership in the one or more social networks, or an interaction pattern between entities of the one or more social networks. Malek[0035]
10. The method of claim 9, wherein the interaction pattern comprises a barter transaction, a loan request, a loan provisioning, a loan payment (monetary payment and/or non-monetary payment), a borrowing of a tool, a request for a product, a delivery of the product, a review of the product, a request for a service, a delivery of the service, a review of the service, or a combination thereof. Malek P[104]
13. The method of claim 1, further comprising:
receiving a request to provide a financial product, a financial service, or a combination thereof, to the second entity;
deriving a risk assessment for providing the financial product, the financial service, or the combination thereof, to the second entity based on the community-based credit score; and
delivering the financial product, the financial service, or the combination thereof; when a risk metric included in the risk assessment is higher than a minimum risk value. P{0175]
15. The method of claim 1, wherein the second entity comprises an unbanked entity of the one or more social networks that does not have a bank account. P[0186] while this limitation is nonfunctional descriptive language, the reference teaches targeting the unbanked
16. The method of claim 1, wherein the second entity comprises a member of the one or more social networks that does not have a credit history. P[0022] StreetCred is an environment where one can build credit among his peers similar to how credit is established with financial institution.
Claim(s) 7 and 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Malek 202000286167 in view of Mawji 20160277424 further in view of Stewart 8694401
The teaching of Malek and Mawji set forth in the rejection of claim 1 is incorporated by reference. Malek fails to teach the following:
Claim 7. The method of claim 6, wherein analyzing the non-monetary transaction to derive a monetary value comprises:
identifying a good, a service, or a combination thereof, being provided via the non-monetary transaction; Stewart p[19]
determining a fair market value (FMV) for the good, the service, or the combination thereof; and
assigning the FMV as the monetary value. Stewart doesn’t teach of assigning a FMV to the Barter but it would have been obvious for one skilled in the art to have places a FMV to the transaction as FMV of bartered transactions are routine to those skilled in the art.
8. The method of claim 5, wherein the non-monetary transaction comprises a barter transaction, a tool-lending transaction, a time banking transaction, a service transaction, or a combination thereof. Stewart p[0019]
It would have been obvious for one skilled in the art at the time to have combined the references as they are directed to a credit and lending.
Claim(s) 11-12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Malek 202000286167 in view of in view of Mawji 20160277424 further in view of Gilliam 20200258158
The teaching of Malek at set forth in the rejection of claim 1 is incorporated by reference. Malek fails to teach the following:
11. The method of claim 1, further comprising encapsulating the community-based credit score in a smart contract and entering the smart contract in a distributed digital ledger. Gilliam [0007] In various embodiments, the present invention is directed to a system and method utilizing artificial intelligence and blockchain technology to automate, maintain, and regulate lending networks, cryptocurrency exchanges, savings accounts, and credit repair intervention mechanisms through a mobile savings platform that is connected to a financial institution and can be used as an instrument for credit repair or to save, borrow, and lend money amongst a network of individuals. The present invention also utilizes blockchain and artificial intelligence to verify and protect data and information shared with participants and financial institutions.
12. The method of claim 11, wherein the smart contract is configured to automatically execute a smart contract provision based on the community-based credit score having at least a minimum score. [0007] In various embodiments, the present invention is directed to a system and method utilizing artificial intelligence and blockchain technology to automate, maintain, and regulate lending networks, cryptocurrency exchanges, savings accounts, and credit repair intervention mechanisms through a mobile savings platform that is connected to a financial institution and can be used as an instrument for credit repair or to save, borrow, and lend money amongst a network of individuals. The present invention also utilizes blockchain and artificial intelligence to verify and protect data and information shared with participants and financial institutions.
It would have been obvious for one skilled in the art at the time to have combined the references as they are directed to a credit and lending.
Claim(s) 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Malek 202000286167 in view of Gao US Patent Publication 20140365356
The teaching of Malek at set forth in the rejection of claim 1 is incorporated by reference. Malek fails to teach the following:
14. The method of claim 13, wherein deriving the risk assessment comprises:
applying the community-based credit score as input into a risk assessment model; and
executing the risk assessment model to derive the risk assessment metric, wherein the risk assessment model comprises at least one of a logistic regression model, a linear regression model, a Gradient Boosting Machine (GBM) model, a Support Vector Machine (SVM) model, or Neural Networks model.
Gao P [0025] Various types of predictive models can be utilized including, without limitation, scorecard models, logistic regression models, neural network-based models, and the like. Regardless of the type of model, the values that are based on events occurring or not occurring within a time window can be modified based on a shifting of the applicable window to some point in the future. During the shifted time window, in some variations, it is assumed that no material changes to the credit file and/or no adverse events (i.e., events negatively affecting creditworthiness) occur during such time period. In other variations, an average of historical events for the particular category can be utilized/projected going forward rather than assuming that no adverse events occur within the shifted time window.
It would have been obvious for one skilled in the art at the time to have combined the references as they are directed to a credit and lending.
Response to Arguments
The applicant argues 1. Platform-specific automated data extraction: The independent claims recite that "the data collection system is configured to automatically extract the social network data using
platform-specific queries." That is, one or more social platforms are supported, which then
are queried via platform-specific queries to automatically extract the social network data. This new limitation of addressed in the rejection.
2. Computation of measurable engagement metrics to identify a "key actor": The
independent claims recite the use of specific measurable engagement metrics that are
analyzed from large scale social network data to determine a key actor of the social network.
For example, the claims recite "...analyzing... the social network data to identify a key
actor... based on one or more measurable engagement metrics comprising a follower count,
an engagement rate, a posting rate, a comment rate..." This new limitation of addressed in the rejection.
3. Authenticated, system-level communication channels: The amended claims recite
authenticated channel constraints-rooted in secure computing-supported by the
specification's disclosure, for example, of certificates, key exchanges, TLS, and MFA. For
example, the claims recite "sending... via an authenticated communication channel, a
credit-vouching request to the key actor..." and "receiving... via the authenticated
communication channel..." This language while being rejected as new matter when broadly construed is taught by the reference as supportive above.
4. Multi-source credit score synthesis using first and second scores: The amended claims then
recite that the first and second credit scores are combined, to arrive at the community- generated credit score. The multi-source synthesis is addressed in the rejection above.
The rejection under 101
The applicant argues thar the specific technique of graph analysis of social networks is used to determine a credit score, for example, via a key actor determination and authentication renders the claims patent eligible.
The examiner is not persuaded as least for the reason that there is not express teaching as to how this channel operates.
The claims recite the use of graph analysis as applied to social network data to determine a key actor. This argument is not persuasive as it is neither claimed nor described in the specification,
and the key actor is then authenticated to determine a community-generated credit score. More specifically, the claims recite: "analyzing, via the data collection system, the social network data to identify a key actor within a community of the one or more social networks based on one or more measurable engagement metrics comprising a follower count, an engagement rate, a posting rate, a comment rate, or a combination thereof; sending, via a community-based credit evaluation system and via an authenticated communication channel, a credit-vouching request to the key actor to assign a second credit score to the second entity of the one or more social networks; receiving, from the key actor and via the authenticated communication channel, a second credit voucher that assigns the second credit score to the second entity."
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 RICHARD C WEISBERGER whose telephone number is (571)272-6753. The examiner can normally be reached Monday - Thursday 10AM-8PM PCT.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Michael Anderson can be reached at 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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RICHARD C. WEISBERGER
Examiner
Art Unit 3693
/RICHARD C WEISBERGER/ Primary Examiner, Art Unit 3693
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