Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
Status of the Claims
The following office action in response to the amendments filed on 3/5/2026.
Claims 1-4, 8-12 and 16-20 are currently amended.
Therefore, claims 1-20 are pending and addressed below.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Claims 1-20 are directed to a system, a method, and a non-transitory computer readable medium and thus a statutory category of invention (Step 1: YES).
Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention recites an abstract idea without significantly more. The claim recites the limitations of “…accumulating a dataset comprising claim files that have been processed to completion, the claim files including reserve estimates and corresponding finalized payout amounts; training a machine learning model using the dataset, including automatically adjusting predictive parameters of the machine learning model based at least in part on discrepancies between the reserve estimates and the finalized payout amounts, the adjusting improving accuracy of reserve-estimate prediction; receiving information corresponding to a claim event; and executing the trained machine learning model on the information corresponding to the claim event”. These recited limitations, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of fundamental economic principles or practices (including insurance, i.e. generating an optimized reserve estimate for an insurance claim event) but for the recitation of generic computer components. If a claim limitation, under its broadest reasonable interpretation, covers concepts of fundamental economic principles or practices but for the recitation of generic computer components, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
The additional limitations (besides those that recite the abstract idea) include the presence in the system claim of a network communication interface, one or more processors, and a memory that are all recited at a high level of generality to perform the functions of “accumulating… a dataset; training …a machine learning model using the dataset, including automatically adjusting…predictive parameters of the machine learning model…, the adjusting improving… accuracy of reserve-estimate prediction; receiving …information; and executing …the trained machine learning model …to generate …an estimate for the claim event”, such that it amounts no more than mere instructions to apply the exception using a generic computer component. Thus, nothing more than specifying the type of data used to train the machine learning models. The machine learning model are merely being used as a tool for analyzing the information to generate the prediction of the claim event. Accordingly, the additional elements do not integrate the abstract idea into a particular application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception or amount to an inventive concept. As discussed above with respect to integration of the abstract idea into a practical application, the additional limitations of the network communication interface, the one or more processors, and the memory that are all recited at a high level of generality to perform the functions of “accumulating… a dataset; training …a machine learning model using the dataset, including automatically adjusting…predictive parameters of the machine learning model…, the adjusting improving… accuracy of reserve-estimate prediction; receiving …information; and executing …the trained machine learning model …to generate …an estimate for the claim event”, such that it amounts no more than mere instructions to apply the exception using a generic computer component. Thus, nothing more than specifying the type of data used to train the machine learning models. The machine learning model are merely being used as a tool for analyzing the information to generate the prediction of the claim event. When viewing the additional elements either individually or as an ordered combination, the claim as a whole does not amount to significantly more than the judicial exception because the claim does not include improvements to another technology or technical field, improvements to the function of the computer itself, and does not provide meaningful limitations beyond general linking the use of an abstract idea to a particular technological environment. In effect, the additional limitations add the words “apply it” (or an equivalent) to the judicial exception, or mere instructions to implement an abstract idea on a computer. Mere instructions to apply an exception using the generic computer component cannot provide an inventive concept. Thus, the claim is not patent eligible.
Independent claims 9 and 17 recite limitations substantially similar to claim 1. Thus, the claims are rejected based on the same reasoning as above in claim 1. Thus, the claims are not eligible.
Dependent claims 2-8, 10-16 and 18-20 are dependent on claims 1, 9 and 17. Therefore, claims 2-8, 10-16 and 18-20 are directed to the same abstract idea of claims 1, 9 and 17. Claims 2-8, 10-16 and 18-20 further recite the limitations that merely refer back to further details of the abstract idea. In addition, the additional limitations (besides those that recite the abstract idea) of the one or more networks included in the dependent claims 8 and 16 that are all recited at a high level of generality to perform the functions of “…transmit… data indicating the optimized reserve estimate to a policy provider corresponding to the claim event” (claims 8 and 16), such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
The dependent claims 2-8, 10-16 and 18-20 does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception or amount to an inventive concept. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to nothing more than an instruction to “apply it” with the judicial exception. In addition, the additional limitations (besides those that recite the abstract idea) of the one or more networks included in the dependent claims 8 and 16 that are all recited at a high level of generality to perform the functions of “…transmit… data indicating the optimized reserve estimate to a policy provider corresponding to the claim event” (claims 8 and 16), above amounts to mere instructions to apply the exception using the generic computer component. When viewing the additional elements either individually or as an ordered combination, the claim as a whole does not amount to significantly more than the judicial exception because the claim does not include improvements to another technology or technical field, improvements to the function of the computer itself, and does not provide meaningful limitations beyond general linking the use of an abstract idea to a particular technological environment. In effect, the additional limitations add the words “apply it” (or an equivalent) to the judicial exception, or mere instructions to implement an abstract idea on a computer. Mere instructions to apply an exception using the generic computer component cannot provide an inventive concept. Thus, when considering the combination of elements and the claimed as a whole, the dependent claims 2-8, 10-16 and 18-20 are not patent eligible.
Response to Arguments
Previous Bib Data Sheet Objection
The previous Bib Data Sheet Objection is withdrawn in the light of Applicant’s clarification.
Previous Claim rejections – 35 USC § 102 and 35 USC § 103
The previous claims rejections under the 35 USC § 102 and 35 USC § 103 have been withdrawn in the light of Applicant’s amendments.
Previous Claim rejections – 35 USC § 101
The updated rejections of claims 1-21 in view of Alice have been provided in the light of Applicant’s amendments.
Applicant's arguments filed 3/5/2026 have been fully considered but they are not persuasive.
Argument: Applicant argued that: “…The Office Action alleges that the claims are abstract as being directed to "performance of fundamental economic principles or practices." See Office Action, page 3. Applicant respectfully disagrees… Furthermore, the aforementioned feature does not have a mental equivalent, and it recites an improvement ("... the adjustment improving accuracy of reserve- estimate prediction"). The feature is integral to the claim and is therefore not extra- solution activity. As such, the feature integrates the alleged abstract idea into a practical application…” (Please see the remarks on pages 8-10).
Answer: The Examiner respectfully disagrees.
As the office has explained above that the claim recites the limitations of “…accumulating a dataset comprising claim files that have been processed to completion, the claim files including reserve estimates and corresponding finalized payout amounts; training a machine learning model using the dataset, including automatically adjusting predictive parameters of the machine learning model based at least in part on discrepancies between the reserve estimates and the finalized payout amounts, the adjusting improving accuracy of reserve-estimate prediction; receiving information corresponding to a claim event; and executing the trained machine learning model on the information corresponding to the claim event”. These recited limitations, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of fundamental economic principles or practices (including insurance, i.e. generating an optimized reserve estimate for an insurance claim event) but for the recitation of generic computer components. If a claim limitation, under its broadest reasonable interpretation, covers concepts of fundamental economic principles or practices but for the recitation of generic computer components, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
The additional limitations (besides those that recite the abstract idea) include the presence in the system claim of a network communication interface, one or more processors, and a memory that are all recited at a high level of generality to perform the functions of “accumulating… a dataset; training …a machine learning model using the dataset, including automatically adjusting…predictive parameters of the machine learning model…, the adjusting improving… accuracy of reserve-estimate prediction; receiving …information; and executing …the trained machine learning model …to generate …an estimate for the claim event”, such that it amounts no more than mere instructions to apply the exception using a generic computer component. Thus, nothing more than specifying the type of data used to train the machine learning models. The machine learning model are merely being used as a tool for analyzing the information to generate the prediction of the claim event. Accordingly, the additional elements do not integrate the abstract idea into a particular application because it does not impose any meaningful limits on practicing the abstract idea.
In addition, the MPEP 2106.04(a) states that: “…Examiners should determine whether a claim recites an abstract idea by (1) identifying the specific limitation(s) in the claim under examination that the examiner believes recites an abstract idea, and (2) determining whether the identified limitations(s) fall within at least one of the groupings of abstract ideas listed above. If the identified limitation(s) falls within at least one of the groupings of abstract ideas, it is reasonable to conclude that the claim recites an abstract idea in Step 2A Prong One”. Thus, according to the MPEP 2106.04(a), Examiner (1) identifying the specific limitation(s) (accumulating a dataset comprising claim files that have been processed to completion, the claim files including reserve estimates and corresponding finalized payout amounts; training a machine learning model using the dataset, including automatically adjusting predictive parameters of the machine learning model based at least in part on discrepancies between the reserve estimates and the finalized payout amounts, the adjusting improving accuracy of reserve-estimate prediction; receiving information corresponding to a claim event; and executing the trained machine learning model on the information corresponding to the claim event) falls within the subject matter groupings of abstract ideas of “Certain Methods Of Organizing Human Activity: fundamental economic principles or practices (including insurance, i.e. i.e. generating an optimized reserve estimate for an insurance claim event) in the Applicant’s claim under examination that the examiner believes recites an abstract idea, and (2) determining whether the identified limitations(s) (accumulating a dataset comprising claim files that have been processed to completion, the claim files including reserve estimates and corresponding finalized payout amounts; training a machine learning model using the dataset, including automatically adjusting predictive parameters of the machine learning model based at least in part on discrepancies between the reserve estimates and the finalized payout amounts, the adjusting improving accuracy of reserve-estimate prediction; receiving information corresponding to a claim event; and executing the trained machine learning model on the information corresponding to the claim event) fall within at least one of the groupings of abstract ideas listed above. If the identified limitation(s) falls within at least one of the groupings of abstract ideas, it is reasonable to conclude that the claim recites an abstract idea in Step 2A Prong One”. Therefore, according to the MPEP 2106.04(a), it is reasonable to conclude that the claim recites an abstract idea in Step 2A Prong One”.
Therefore, the claim recites an abstract idea of “Certain Methods Of Organizing Human Activity: fundamental economic principles or practices” and the claim does not integrate the abstract idea into a particular application because it does not impose any meaningful limits on practicing the abstract idea. Thus, Applicant’s arguments are not persuasive.
For the above reasons, it is believed that Appellant's arguments have been fully considered but they are not persuasive and the rejections should be sustained.
Conclusion
THIS ACTION IS MADE FINAL. 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 extension fee 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 Tien C. Nguyen whose telephone number is 571-270-5108. The examiner can normally be reached on Monday-Thursday (6am-2pm EST).
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor,
Bennett Sigmond can be reached on 303-297-4411. The fax phone number for the organization where this application or proceeding is assigned is 571-270-6108.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/TIEN C NGUYEN/Primary Examiner, Art Unit 3694
Prosecution Insights