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 the Claims
Claims 1-20 are all the claims pending in the application.
Claims 1, 8, and 15 are amended.
Claims 1-20 are rejected.
The following is a Final Office Action in response to amendments and remarks filed Jan. 2, 2026.
Response to Arguments
Regarding the 103 rejections, the rejections are withdrawn because the cited references do not teach reaching a threshold of accumulated account activity. Please see below for the new 103 rejections of the claims as amended.
Please note, Applicant asserts Monegan does not teach accessing real-time transaction account activity. Examiner respectfully does not find this assertion persuasive because Monegan explicitly contemplates using data sources including recent transactions, ¶¶[0026]-[0028].
In response to arguments in reference to any depending claims that have not been individually addressed, all rejections made towards these dependent claims are maintained due to a lack of reply by Applicant in regards to distinctly and specifically pointing out the supposed errors in Examiner's prior office action (37 CFR 1.111). Examiner asserts that Applicant only argues that the dependent claims should be allowable because the independent claims are unobvious and patentable over the prior art.
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 (i.e., changing from AIA to pre-AIA ) 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.
Claim(s) 1-5, 8-12, 15-17, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Monegan et al, US Pub. No. 2014/0044243, herein referred to as “Monegan”, in view of Appel et al, US Pub. No. 2017/0351962, herein referred to as “Appel”, further in view of Patel, US Pub. No. 2016/0309032, herein referred to as “Patel”.
Regarding claim 1, Monegan teaches:
accessing, by the at least one computing device, real-time transaction account activity data associated with a user (uses multiple data sources including recent transactions from the same number and email communications from the same customer, ¶¶[0026]- [0030]; see also e.g., ¶¶[0054]-[0057] and Fig. 4 discussing computer system);
generating, by the at least one computing device using the predictive computer model, a ranking of a plurality of intent insights associated with the communication according to one or more of a plurality of intent prediction rules based at least in part on the accumulation of account activity data of the user reaching the specified threshold of account activity (where multiple intents are possible, the algorithm orders intents based on likelihood, ¶[0036], and determines an intent prediction based the date being within a certain number of days from an aspect of the bookings, ¶¶[0039], [0041]; see also ¶[0007] noting customer intent is predicted),
selecting, by the at least one computing device, a ranked intent insight as an intent prediction alert, wherein the intent prediction alert comprises a predicted reason for the communication (determines most likely reason for customers call, ¶[0038]);
transmitting, by the at least one computing device to a client device of the user, the ranking of the plurality of intent insights and a user feedback inquiry comprising an accuracy inquiry to confirm whether individual ones of the plurality of intent insights are accurate (caller is asked a proactive question to validate predicted intent, e.g., “Are you calling to about your upcoming trip to Boston?” ¶[0035]; see also ¶[0053] noting customer communication occurs using cellular telephone).
However Monegan does not teach but Appel does teach:
training a predictive computer model of at least one computing device to determine a ranking of intent insights based on prior servicing interactions with users (trains supervised learning algorithm, ¶¶[0027], [0054]-[0055]; see also e.g., ¶[0032] and Abstract discussing predicting user questions; and ¶¶[0059]-[0060] discussing computer system);
wherein the ranking of the plurality of intent insights is further based at least in part on one or more social media posts on a social network related to a transaction account of the user (collects user provided content from social media to make predictions, ¶¶[0026], [0056]);
and retraining the predictive computer model of the at least one computing device based on the user feedback (collects feedback on predictions to retrain machine learning algorithm, ¶[0030]).
Further, it would have been obvious before the effective filing date of the claimed invention, to combine the customer intent prediction of Monegan with using machine learning to predict customer intent as taught by Appel because known work in one field of endeavor may prompt variations of it for use in the same field based on design incentives, see MPEP 2143.I.F. That is, one of ordinary skill would have recognized the intent prediction in Monegan would likely be improved by using machine learning (e.g., in situations where there is sufficient training data to benefit from using machine learning) and accordingly would have modified Monegan to use machine learning, e.g., as taught by Appel.
However the combination of Monegan and Appel does not teach but Patel does teach:
determining, by the at least one computing device from the real-time transaction account activity data, that an accumulation of account activity data of the user has reached a specified threshold of accumulated account activity (rules specify caller profiles with a ranking exceeding a threshold be accorded a different response, ¶[0039] and rankings are based on accumulations like frequency of social network messages, or a large number of followers on one or more social networks, ¶[0029]; see also ¶[0027] discussing using caller profile to predict an issue)
Further, it would have been obvious before the effective filing date of the claimed invention, to combine the customer intent prediction using machine learning of Monegan and Appel with the personalize rules of Patel because Patel suggests doing so to avoid losing important calls at a customer contact centers, see ¶[0003] of Patel; see also MPEP 2143.I.G.
Regarding claim 2, the combination of Monegan, Appel and Patel teaches all the limitations of claim 1 and Monegan further teaches:
receiving an accuracy response from the user via a wireless communication channel, the accuracy response being entered via an electronic input (caller provides validation of the proactive intent, ¶[0035]).
Regarding claim 3, the combination of Monegan, Appel and Patel teaches all the limitations of claim 1 and Monegan further teaches:
routing a communication from the user to a service system based on the intent prediction alert (provides accelerated service if the intent prediction is validated or personalized service if the intent prediction is not validated, ¶[0035]).
Regarding claim 4, the combination of Monegan, Appel and Patel teaches all the limitations of claim 1 and Monegan further teaches:
determining a priority insight of the plurality of intent insights (positive and negative points are awarded based on recentness of events, ¶[0038]);
and adjusting the ranking of the plurality of intent insights based at least in part on the priority insight such that the priority insight is a highest ranking intent insight of the plurality of intent insights (prediction of intent is determined to be the most recent event, ¶[0038]).
Regarding claim 5, the combination of Monegan, Appel and Patel teaches all the limitations of claim 1 and Monegan further teaches:
wherein generating the ranking of the plurality of intent insights is based at least in part on a chronological order (positive and negative points are awarded based on recentness of events and prediction of intent is determined based on recentness of events, ¶[0038]).
Regarding claims 8 and 15, claims 8 and 15 recite similar limitations as claim 1 and further recite “a processor; a memory; and instructions stored in the memory and executable by the processor” and a “non-transitory computer-readable medium storing instructions executable in a processor”, respectively. These concepts are taught by Monegan in ¶¶[0054]-[0055]. Accordingly, claims 8 and 15 are rejected for similar reasons as claim 1.
Regarding claims 9-12, 16, 17, and 20, claims 9-12, 16, 17, and 20 recite similar limitations as claims 2-5 and accordingly are rejected for similar reasons as claims 2-5.
Claim(s) 6, 7, 13, 14, 18, and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Monegan, Appel and Patel further in view of Spencer et al, US Pub. No. 2010/0076895, herein referred to as “Spencer”.
Regarding claim 6, the combination of Monegan, Appel and Patel teaches all the limitations of claim 1 and does not teach but Spencer does teach:
wherein the ranking of the plurality of intent insights is further based at least in part on a fraud alert communicated to the user regarding the transaction account of the user (fraud alert, pg. 14, Rule i.d. 20, 21).
Further, it would have been obvious before the effective filing date of the claimed invention, to combine the customer intent prediction using machine learning and personal rules of Monegan, Appel and Patel with the fraud alerts of Spencer because known work in one field of endeavor may prompt variations of it for use in the same field based on design incentives, see MPEP 2143.I.F. That is, one of ordinary skill would have recognized noting fraud alerts would likely be useful when predicting a caller’s intent.
Regarding claim 7, the combination of Monegan, Appel and Patel teaches all the limitations of claim 1 and does not teach but Spencer does teach:
wherein the accumulation of activity data comprises an accumulation of late fees for the user (accounts delinquency, pgs. 11-12, Rule i.d. 5, 6) .
Further, it would have been obvious before the effective filing date of the claimed invention, to combine the customer intent prediction using machine learning of Monegan, Appel and Patel with the account delinquency of Spencer because known work in one field of endeavor may prompt variations of it for use in the same field based on design incentives, see MPEP 2143.I.F. That is, one of ordinary skill would have recognized noting account delinquency would likely be useful when predicting a caller’s intent.
Regarding claims 13, 14, 18 and 19, claims 13, 14, 18 and 19 recite similar limitations as claims 6 and 7 and accordingly are rejected for similar reasons as claim 6 and 7.
Conclusion
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 BRENDAN S O'SHEA whose telephone number is (571)270-1064. The examiner can normally be reached Monday to Friday 10 - 6.
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/BRENDAN S O'SHEA/Examiner, Art Unit 3626