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 Status
Claims 21-39, and 41 are currently pending and are presented for examination on the merits.
Claim objection
Double Patenting
**This rejection is being held under abeyance, until further prosecution, per Applicant’s request.**
Claims 21-39, and 41 of this application is patentably indistinct from claims 1-20 of Application No. 16/136,387 (US Patent 11783422). Although the claims at issue are not identical, they are not patentably distinct from each other because the broader instant claims recite the same limitations contained in the narrower claims of the parent applications. As such, the instant claims are obvious in light of the parent claims.
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In reLongi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Omum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(1)(1) - 706.02(1)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/ AIA / 26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An e-Terminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
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 21-39, and 41 are rejected under 35 U.S.C. § 101, because they recite non-patentable subject matter under MPEP § 2106. The claimed invention is directed to a judicial exception (e.g., an abstract idea, etc.) without practical application or significantly more.
More particularly, when considering subject matter eligibility under 35 U.S.C. 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter. If the claim does fall within one of the statutory categories, it must then be determined whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea), and if so, it must additionally be determined whether the claim is a patent-eligible application of the exception. If an abstract idea is present in the claim, any element or combination of elements in the claim must be sufficient to ensure that the claim amounts to significantly more than the abstract idea itself. Broad categories of abstract ideas include fundamental economic practices, certain methods of organizing human activities, an idea itself, and mathematical relationships/formulas. See, generally Alice Corporation Pty. Ltd. v. CLS Bank International, et al., 573 U.S. __ (2014) (citing Mayo Collaborative Servs. v. Prometheus Labs., Inc.,132 S. Ct. 1289, 1294, 1297-98 (2012)); Federal Register notice titled 2014 Interim Guidance on Patent Subject Matter Eligibility (79 FR 74618), which is found at: http:// www. gpo.gov/fdsys/pkg/FR-2014-12-16/pdf/2014-29414.pdf; 2015 Update to the Interim Guidance; the 2019 Revised Patent Subject Matter Eligibility Guidance, Fed. Reg., Vol. 84, No. 4, January 7, 2019; and associated Office memoranda.
Under the 2019 PEG, step 2a-prong 1, Claims 21-39, and 41 recite a judicial exception(s), including a method of organizing human activity (e.g. fundamental economic principle and commercial/legal interaction). More particularly, the entirety of the method steps are directed towards classifying data, determining a loss event, and determining an amount associated therewith, and more particularly, to using a neural network trained by historical data to label data according to a category (i.e., a classification model), and using an image recognition model to determine a loss event, validate said loss, and generate an amount associated therewith. This is a long-standing commercial practice previously performed, among other things, by human adjusters. Here, the neural network supplants the human brain and the image recognition model supplants human eyes and brain. It is understood, for example, that the human brain learns, in part, by undergoing training with historical data (to gain experience).
Under step 2a-prong 2, the claims fail to recite a practical application of the exception, because the extraneous limitations (e.g., an image recognition model, a neural network (broadly construed at [0072] of the specification), computer processors, applying hash values, etc.) merely add insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g), and/or generally link the use of the judicial exception to a particular technological environment or field of use, e.g., life claims (MPEP 2106.05(h)). The claims generally instruct an artisan to apply the method across generic computing technology (e.g., neural networks, computers (see Spec [0126];[0142], etc.). More particularly, the claims fail to recite an improvement to the functioning of a computer or technology (under MPEP § 2106.05(a)), the use of a particular machine (under § 2106.05(b)), effect a transformation or reduction of a particular article (§ 2106.05(c)), or apply the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment (§ 2106.05(e)).
Under part 2b, the additional elements (a neural network, image recognition model, etc.) recite insignificant extra-solution activity, and applies the abstract idea across generic computing technology. As such, the claim limitations taken individually and as a whole, do not amount to significantly more than the abstract idea itself. This is because no one claim effects an improvement to another technology or technical field, an improvement to the functioning of a computer itself, or move beyond a general link of the use of the abstract idea to a particular technological environment. Viewing the limitations as an ordered combination does not add anything further than looking at the limitations individually. Under Alice, merely applying or executing the abstract idea on one or more generic computer system (e.g., a computer system comprising a generic database; a generic element (NIC) for providing website access, etc.; a generic element for receiving user input; and a generic display on the computer, in any of their forms) to carry out the abstract idea more efficiently fails to cure patent ineligibility. See, e.g., Content Extraction, 776 F.3d at 1347 (claims reciting a “scanner” are nevertheless directed to an abstract idea); Mortg. Grader, Inc. v. First Choice Loan Serv. Inc., 811 F.3d 1314, 1324–25 (Fed. Cir. 2016) (claims reciting an “interface,” “network,” and a “database” are nevertheless directed to an abstract idea).
Courts have recognized the following computer functions to be well‐understood, routine, and conventional functions when they are claimed in a merely generic manner: performing repetitive calculations, receiving, processing, and storing data, electronically scanning or extracting data from a physical document, electronic recordkeeping, automating mental tasks, and receiving or transmitting data over a network, e.g., using the Internet to gather data. MPEP 2106.05(d)
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.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 21, 22, 24, 25, 27, 32, 36, and 38 are rejected under § 103 as being unpatentable over US 2008/0077451 to Anthony et al., in view of US 2016/0055589 to Billings.
With respect to Claims 21, 32, and 36, Anthony teaches a non-transitory computer readable medium (FIG. 1, memories), a claims handling user device comprising one or more processors and memories configured to perform (FIG. 1), a computer-implemented method of claims handling ([0018];[0041]) based upon image data and text-based content, and using an image recognition model ([0019-20]), comprising: receiving, by a processor and from an electronic device, a life claim ([0018]), the life claim comprising claim first data including at least one of image data or audio data ([0019]); extracting, by the processor text-based content from the first data ([0020]); generating, by the processor, and based at least in part on the text-based content, a label ([0027]) representing a category associated with the text-based content ([0019-20]); determining, by the processor and using an image recognition model ([0019]), a loss event based at least in part on the image data ([0041]); validating, by the processor, the loss event using an Application Programming Interface (API) ([0004], see verification throughout; [0008], detecting fraud is validating; [0056], GUI over the internet); and based at least in part on validating the loss event, generating, by the processor, and based at least in part on the text-based content and the label, an amount corresponding to the loss event ([0027-28];[0041]). The system in Anthony is configured to perform the recited steps of the invention, however, it does not use the exact same language. Please note that the applied reference(s) need not use the same terminology, or disclose the limitation verbatim. Anthony teaches a different set of components/method steps collectively operable to perform insurance claim settlement prediction. The set of engines are a simple substitute for the recited first and second neural networks (i.e., image recognition model, etc.). See, KSR international Co. v. Teleflex Inc. Moreover, teaching insurance settlement, includes the current state of the laws for same, including making an offer, communicating the offer, to a user device (e.g., smart phone, etc.). Finally, in so far as any claim limitation recites calculation of a hash value as a unique identifier, and automating previously manual steps have been deemed obvious under § 103 analysis. St. Regis Paper Co. v. Bemis Co., 193 USPQ 8. See also, MPEP § 2144.05 which states: In re Harza, 274 F.2d 669, 124 USPQ 378 (CCPA 1960). As such, it would have been obvious to one of ordinary skill in the art to modify Anthony to include the specified verbiage and specific set of models.
Anthony fails to expressly teach, but Billings teaches wherein validating the loss event includes: executing, by the processor, a link in the first data, execution of the link causing the processor to retrieve reference data corresponding to the loss event, through the API, from a database. ([0029-30], SQL database;[0063], linked). Billings discusses the need to better manage claims and formulate plans to mitigate claims costs. [0004-05] As such, it would have been obvious to one of ordinary skill in the art to modify Anthony to include this limitation as taught by Billings in order to better manage the claim.
With respect to Claim 22, Anthony teaches wherein the first data corresponds to a life insurance policy ([0018]).
With respect to Claim 24, Anthony teaches wherein the life claim first data corresponds to one or both of (1) a worker’s compensation insurance policy, and (11) a disability insurance policy ([0018]).
With respect to Claims 25, and 38, Anthony teaches inputting, by the processor, the text-based content to a neural network; and executing, by the processor, the neural network to generate the label representing the category associated with the text-based content ([0005];[0041]), wherein the neural network is trained using a set of labeled historical data, wherein each labeled historical data in the set of labeled historical data corresponds to an amount corresponding to a historical loss event and a historical label. ([0005];[0041])
With respect to Claim 27, Anthony teaches generating, by the processor and based upon the claim settlement prediction amount corresponding to the loss event, a settlement offer, wherein the settlement offer includes at least one of (1) a lump sum payment, or (11) a series of installment payments (FIG. 4; [0034];[0041], lump sums and installment payments were the state of the art at the time of filing).
Claims 23 and 41 are rejected under § 103 as being unpatentable over Anthony, in view of Billings, and further in view of US 2017/0046806 to Haldenby et al.
With respect to Claims 23, and 41, Anthony fails to expressly teach, but Haldenby teaches wherein the first data includes a photograph of a death certificate of a deceased person under an insurance policy ([0172]) related to the first data, and the computer-implemented method further comprises: determining, by the processor and using a machine learning model, authenticity of the death certificate ([0172]), wherein the machine learning model outputs a result indicative of the authenticity ([0172]); associating, by the processor, a hash value with the result, and storing, by the processor, the hash value with the result ([0065]). Haldenby discusses the need for increased data security. [0002-03] It would have been obvious to one of ordinary skill in the art to modify Anthony to consider images of death certificates when dealing with life claims, and authenticating and associating with additional information such as a hash value, in order to increase data security.
Claim 26 is rejected under § 103 as being unpatentable over Anthony, in view of Billings, and further in view of US 7664662 to Binns et al.
With respect to Claim 26, Anthony fails to expressly teach, but Binns teaches wherein the claim settlement amount corresponding to the loss event is an inflation-adjusted amount (col 12, ln 40-47). Binns discusses the need to provide reliable estimates in group insurance determination of severity (cost) of an event (col 1, ln 15-30). As such, it would have been obvious to one of ordinary skill in the art to modify Anthony to include inflation-adjustment as taught by Binns when estimating cost of an insurance event, in order to increase reliability.
Claim 28-31, 33-35, 37, and 39 are rejected under § 103 as being unpatentable over Anthony, in view of Billings, and further in view of US 2001/0037204 to Horn et al.
With respect to Claim 28, Anthony fails to expressly teach, but Horn teaches transmitting, by a processor, a settlement offer to the electronic device, wherein receiving the settlement offer activates an application executing on the electronic device to generate a user interface to cause the settlement offer to display via the user interface (FIG. 1; [0027];[0069]). Horn discusses the dissatisfaction and high cost associated with resolving insurance related disputes. [0007-09] As such, it would have been obvious to one of ordinary skill in the art to modify Anthony to include presentment of settlement offers to a interface of a device application, in order to reduce costs and increase satisfaction.
With respect to Claim 29, 33, 34, 37, and 39, Anthony fails but Horn teaches receiving, by the processor and based on an input received via the user interface of the application, a manifestation of acceptance of the settlement offer ([0096]); transmitting to the user device, the settlement offer, wherein receiving the settlement offer activates an application executing on the user device to generate a user interface ([0027]); and based on the manifestation of acceptance, generating, by the processor, a payment to a beneficiary indicated in an insurance policy associated with the first data ([0101]; [0007] “third party claimant”). Under the same rationale as Claim 28, it would have been obvious to one of ordinary skill in the art to modify Anthony to include this limitation taught by Horn.
With respect to Claim 30, Anthony fails to expressly teach, but Horn teaches wherein sending the settlement offer comprises displaying a first offer of a lump sum payment (FIG. 1), and a second offer of a series of installment payments, each of the first offer and the second offer having a respective time period for acceptance (FIG. 1), the computer-implemented method further comprising: receiving, by the processor and based on an input received via the user interface of the application, an acceptance of one of the first offer or the second offer ([0101]); determining, by the processor, that a time period corresponding to the acceptance has expired ([0027], and based on determining that the time period corresponding to the acceptance has expired ([0027]), scheduling, by the processor and through the application installed on the electronic device, a payment to a beneficiary (“third party claimant”) indicated in an insurance policy associated with the first data. Under the same rationale as Claim 1, it would have been obvious to one of ordinary skill in the art to modify Anthony to include this limitation taught by Horn.
With respect to Claim 31, Anthony teaches generating, by the processor and through the application installed executing on the electronic device, an automatic payment of money corresponding to the claim settlement prediction amount corresponding to the loss event to a beneficiary indicated in an insurance policy associated with the first data. ([0041], “settlement” teaches making the payment as well)
With respect to Claim 35, Anthony teaches receiving additional information from the user interface, and transmitting the additional information to a remote server (FIG. 1)
Response to remarks
Applicant’s remarks submitted on 12/23/2025 have been fully considered, but are not persuasive, where objections/rejections are maintained. The Double Patenting rejection is held in abeyance per Applicant’s request. The instant amendments to the independent primarily claims broaden the scope where it deletes recitation to a neural network (moving said limitations to Claim 25 and the like), but adds “wherein validating the loss event includes . . . from a database”. Anthony and others teach one of ordinary skill in the art, armed with the state of the art, validation of a determination made by a model, involving executing a link to retrieve reference data (for comparison) through an API, from a database. The amendment fails to overcome patent ineligibility by itself, because it does not introduce an innovative concept or significantly more than the enumerated abstract idea(s). The § 101 rejection is maintained, because the claims continue to recite the application of an abstract idea across generic computing technology (using one or more neural networks, image recognition model, and NLP model to make an insurance claim prediction, effect payment etc., etc.) trained to do what humans have long performed. That is to say, humans have long recognized life claims categories based on text-based content, extracted from visual input, and then predicted settlement outcomes and payment amounts. As such, extracting text-based content from an image recognition model (or NLP model), and inputting same to a neural network(s) to supplant human mental processing to predict an outcome (e.g., claim settlement prediction), fails to cure patent ineligibility. This remains an example of applying the enumerated abstract idea across generic computing technology, wherein the extraneous limitations fail to offer an innovative concept or significantly more than the abstract idea. Claim 28 fails to cure patent ineligibility because while transmitting the settlement offer causes an application to present the settlement offer via an interface, it is not time sensitive material. As per Claim 29, generating a payment to a beneficiary account upon a manifestation of acceptance also fails to recite an innovative concept or significantly more on its own. The remaining dependent claims fail to effect a cure. Upon traversal, Applicant is asked to pinpoint the practical application or limitations that effect a practical application or significantly more than the abstract idea identified. A hash value is extraneous limitation unnecessary to the abstract idea, but by itself fails to offer a practical application, as such was known in the art at the time (see prior art references of record, including Haldenby).
As per the prior art rejections, the § 103 rejection is maintained. Billings has been added to teach validating a loss event including executing, by the processor, a link in the first data, and causing the processor to retrieve reference data corresponding to the loss event, through the API, from a database (e.g., [0029-30], SQL database;[0063], linked). An SQL database tool teaches a specialized language protocol that would be accessed through an API. Anthony teaches a predictive engine for predicting insurance claim settlement parameters that teach the limitation of the broadest independent claims, though not in the same terms. Horn teaches causing a settlement offer to display on a user device. Please note that the applied reference(s) need not use the same terminology, or disclose the limitation verbatim, and also that the entirety of a prior art reference is to be applied to the respective claim(s), such that the pinpoint citations above are exemplary and provided for Applicant’s benefit; other locations within the applied reference(s) may further support the rejection. MPEP 2141.02(VI).
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 WILLIAM J JACOB whose telephone number is (571)270-3082. The examiner can normally be reached on M-F 8:00-5:00, alternating Fri. off.
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/WILLIAM J JACOB/Examiner, Art Unit 3696