Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/17/2025 has been entered.
Claims 1-21 have been canceled and claims 22-41 newly added.
Claims 22-41 are currently pending and have been examined.
Response to Arguments
Applicant argues that conventional subrogation claims are rarely identified as reversible claims and that the rules governing subrogation vary by jurisdiction and are continually changing, such that conventional methods are insufficient. Applicant further argues that the claimed system provides a technological approach for automatically identifying and evaluating subrogation claims based on claim characteristics and jurisdictional rules.
These arguments have been considered but are not persuasive.
Under Step 2A, Prong One, the claims recite receiving insurance claim information, retrieving claim attributes (e.g., claim characteristics), accessing jurisdiction databases containing subrogation rules, evaluating the claim against those rules, and generating a recommendation regarding recovery actions. These limitations describe collecting information, analyzing the information using rules, and generating a recommendation, which fall within the abstract idea of insurance claim evaluation and legal recovery determination, a method of organizing human activity.
Under Step 2A, Prong Two, the claims do not integrate the abstract idea into a practical application. The additional elements, including an input module, rules module, validation module, output module, user interface, and databases, merely perform conventional data processing functions such as receiving data, storing rules, retrieving information, and generating output.
Applicant’s arguments regarding the complexity of subrogation rules and the volume of insurance data do not demonstrate tat the claims provide a technological improvement. Instead, the claims merely automate the evaluation of insurance claims using rules and data, which constitutes the implementation of the abstract idea on generic computer components.
Under Step 2B, the claims do not include additional elements that amount to significantly more than the abstract idea. The recited modules and databases represent well-understood, routine, and conventional computer components performing their typical functions.
Accordingly, Applicant’s arguments have been fully considered but are not persuasive, and the rejections under 35 USC 101 is maintained.
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 22-41 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (abstract idea) without significantly more.
Under Step 1, Claims 22-41 are directed to computer-implemented systems and methods for identifying reversible subrogation claims.
Under Step 2A, Prong 1, of the 2019 Revised Patent Subject Matter Eligibility Guidance, the claims recite a judicial exception.
Specifically, the claims recite steps including:
receiving electronic data comprising subrogation demand information,
retrieving characteristic tags associated with insurance claims,
accessing jurisdiction databases containing subrogation rules,
evaluating the subrogation demand against the rules to determine a demand status, and
generating a recommendation regarding recovery or litigation actions.
These limitations describe collecting information, analyzing the information according to rules, and providing a recommendation, which falls within the abstract idea category of certain methods of organizing human activity, such as insurance claim evaluation and legal recovery determination, and mental processes, because such determinations could be performed by a human using rules and available claim information.
Accordingly, the claims recite an abstract idea.
Under Step 2A, Prong 2, the claims do not integrate the abstract idea into a practical application.
The additional claim elements recite generic computer components including:
an input module,
a rules module,
an update module,
a validation module,
an output module,
a user interface,
databases and data stores.
These elements merely perform conventional computer functions such as:
receiving data,
storing rules,
retrieving information from databases,
applying rules to data,
generating recommendations.
The claims use generic computer components to implement the abstract idea but do not improve the functioning of the computer itself or another technological field.
For example:
retrieving jurisdiction rules from databases,
applying those rules to insurance claim data,
determining claim status, and
generating recovery recommendations
are data processing and decision-making activities related to insurance claim management, rather than technological improvements to computing systems.
Additionally, the claimed modules merely perform generic data processing functions, and the claims do not recite specific technological mechanisms for how the modules improve computer performance, database retrieval techniques, or system architecture.
Therefore, the claims merely apply the abstract idea using generic computer components and do not integrate the exception into a practical application.
Under Step 2B, the claims do not include additional elements that amount to significantly more than the abstract idea.
The additional elements, including the recited modules, databases, and interfaces, represent well-understood, routine, and conventional computer components performing conventional activities such as data retrieval, rule evaluation, and output generation.
The ordered combination of these elements similarly does not add any incentive concept because the claims merely implement the abstract idea using conventional computing components to automate the evaluation of insurance subrogation rules and generation of recommendations.
Accordingly, the claims do not amount to significantly more than the abstract idea itself.
Even when considered individually and in combination with their respective base claim, each dependent claim merely adds field-of-use limitations, generic data acquisition, generic automation, or additional business/legal outcome recommendations, which do not integrate the abstract idea into a practical application and do not amount to significantly more.
Claim 23 recites that the update module retrieves a plurality of changes to the jurisdiction status automatically. This limitation merely automates the retrieval of updated information merely automates the retrieval of updated information and constitutes routine data gathering, which is insignificant extra-solution activity.
Claim 24 recites retrieving changes via automated scraping of jurisdiction databases. Automated scraping is a generic technique for collecting information from databases and does not represent a technological improvement to a computer functionality.
Claim 25 recites retrieving a characteristic tag from a secondary information source different from the information source. This merely expands the sources from which information is gathered and represents routine data collection.
Claim 26 recites that the characteristics tag includes gross vehicle weight, unladen weight, and multiple vehicle loss status. This limitation specifies the type of information analyzed, which does not change the abstract nature of the data analysis.
Claim 27 recites determining an insurance claim type. Determining a claim type is part of the insurance claim evaluation process and constitutes an abstract business determination.
Claim 28 recites generating a recommendation to pursue proactive subrogation if a subrogation demand has not been fulfilled. Generating a recommendation regarding legal recovery is part of the abstract insurance claim evaluation process.
Claim 30 recites retrieving changes to jurisdictional status automatically. As with claim 23, this merely automates routine data retrieval.
Claim 31 recites retrieving changes via automated scraping of jurisdiction databases. As discussed in claim 24, scraping represents generic data collection.
Claim 32 recites relates to claim 25 and represents routine data gathering. Claim 33 relates to claim 26 and specifies types of claim data being analyzed. Claim 34 relates to claim 27 and remains part of the abstract claim evaluation process.
Claim 35 recites generating a recommendation to pursue proactive subrogation when a subrogation demand has not been fulfilled. This constitutes a business recommendation resulting from the abstract claim evaluation process.
Claim 37, as with claims 23 and 30, merely automates data retrieval. Claim 38 as with claims 24 and 31, represents generic data collection. Claim 39, as with claims 25 and 32, represents routine data gathering.
Claim 40 recites that the list of subrogation demands includes fields such as subrogee identity, claim type, jurisdiction, loss amount, and settlement payment amount. These limitations merely specify additional information fields used in the analysis.
Claim 41 recites generating a recommendation to pursue proactive subrogation when certain conditions are met. This constitutes an output recommendation based on the abstract claim evaluation process.
Therefore, claims 22-41 are directed to a judicial exception without significantly more. the additional elements do not integrate the abstract idea into a practical application and do not amount to significantly more than the abstract idea itself. Accordingly, claims 22-41 are rejected under 35 USC 101.
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.
Claims 22-41 are rejected under 35 U.S.C. 103 as being unpatentable over Bostic et al. (USPN 10,650,460 B2, herein Bostic) in view of Canovi et al. (US Patent Publication 2014/0156315 A1, herein Canovi).
As per claim 22, Bostic teaches a computer-implemented system for identifying reversible subrogation claims, comprising:
an input module, connected to a user interface, configured to receive electronic data comprising at least one subrogation demand for an insurance claim from an information source, wherein the input module is configured to retrieve at least one characteristic tag of the insurance claim (Bostic ¶ [29] teaches receiving insurance claim information from claim submissions and data sources; ¶¶ [50-52] teach retrieving claim attributes such as loss data, loss cause, fault rating, damage type, location, salvage category, etc., which correspond to characteristic tags of the insurance claim.),
a rules module configured to access a plurality of jurisdiction databases comprising jurisdictional statues with at least one subrogation rule, wherein the rules module stores the plurality of subrogation rules in a data store (Bostic ¶ [26] teaches an insurance claim processing system including tools that assist claim handles in complying with jurisdiction-based regulations when processing insurance claims; ¶ [27] further describes system architecture interacting with data storage 110, indicating that jurisdiction-based regulatory rules and associated claim-processing data may be stored in and accessed from the system data storage),
an update module configured to update the data store based on at least a change in the plurality of subrogation rules (Bostic ¶ [53] teaches updating stored recovery reserve information when values change, indicating that stored claim-related information in the system may be updated when underlying claim or recovery information changes; and ¶¶ [59 & 61] teach that the risk transfer database may be created and updated based on insurance claim information received),
the rules module automatically searches and retrieves the subrogation rules based on the at least one characteristic tag of the insurance claim (Bostic ¶¶ [21, 40 & 42] teach automated claim processing logic, system architecture retrieving claim-related information and processing rules applied to claim data, indicating the system automatically processes claim information and applies applicable rules based on the claim attributes),
Although Bostic does not explicitly disclose determining a demand status of a subrogation demand using a validation module, Canovi teaches:
a validation module, connected to the input module and the rules module, configured to determine a demand status of the subrogation demand (Canovi ¶ [56] teaches a settlement evaluation module that evaluates insurance claims and subrogation situations using statistical models and ¶ [57] teaches providing evaluation results for subrogated claims indicating recovery likelihood and claim outcome assessments), and
an output module connected to the validation module and the user interface (Canovi ¶¶ [39 & 56] teach inquiry portal provides user interface for viewing claim status and evaluation results returned to the portal),
wherein
the validation module evaluates the at least one subrogation demand against the subrogation rules, by applying the at least one characteristic tag of the insurance claim against the subrogation rules, to determine whether demand status of the subrogation demand is proper or improper (Canovi ¶¶ [54-57] teach evaluating insurance claims and determining recovery outcomes using statistical models), and
the output module generates a recommendation based on the demand status (Canovi ¶¶ [54 & 62] teach providing predicted recovery outcomes and recovery strategies based on the evaluation results).
It would have been obvio9us to a person of ordinary skill in the art to incorporate the evaluation techniques of Canovi into the claim processing system of Bostic in order to evaluate insurance claims and determine recovery outcomes for subrogation demands, thereby improving automated claim evaluation and recovery analysis.
As per claim 23, the combination of Bostic and Canovi teach the computer-implemented system for identifying reversible subrogation claims of Claim 21, Canovi further teaches:
wherein the update module is configured to retrieve a plurality of changes to the jurisdictional status automatically (Canovi ¶¶ [60 & 70-71]).
The motivation to combine the references is the same as seen above in claim 22.
As per claim 24, the combination of Bostic and Canovi teach the computer-implemented system for identifying reversible subrogation claims of Claim 22, Canovi further teaches:
wherein the update module is configured to retrieve the plurality of changes via automated scraping of the jurisdiction databases (Canovi ¶ [60]).
The motivation to combine the references is the same as seen above in claim 22.
As per claim 25, the combination of Bostic and Canovi teach the computer-implemented system for identifying reversible subrogation claims of Claim 21, Bostic further teaches:
wherein the input module is configured to retrieve the at least one characteristic tag of the insurance claim from a secondary information source, wherein the secondary information source is different from the information source (Bostic ¶¶ [29 & 50-52]).
As per claim 26, the combination of Bostic and Canovi teach the computer-implemented system for identifying reversible subrogation claims of Claim 21, Canovi further teaches:
wherein the at least one characteristic tag comprises a gross vehicle weight, unladen weight, and multiple vehicle loss status (Canovi ¶[42]).
The motivation to combine the references is the same as seen above in claim 22.
As per claim 27, the combination of Bostic and Canovi teach the computer-implemented system for identifying reversible subrogation claims of Claim 21, Bostic further teaches:
wherein the input module is configured to determine an insurance claim type for the insurance claim (Bostic ¶¶ [50-52]).
As per claim 28, the combination of Bostic and Canovi teach the computer-implemented system for identifying reversible subrogation claims of Claim 26, Canovi further teaches:
wherein, upon determining the type of insurance claim by the validation module, the output module generates a recommendation to pursue proactive subrogation from the third party for the insurance claim of the at least one subrogation demand that has not been fulfilled (Canovi ¶¶ [54, 56 & 65]).
As per claim 29, the claim is rejected under the same reasons discussed with respect to claim 22. Claim 29 includes limitations similar to those recited in claim 22. The additional limitations include conditions relating to specific types of insurance claims and corresponding recovery recommendations.
Bostic teaches receiving insurance claim information and retrieving claim attributes associated with the insurance claim (see Bostic ¶¶ [29 & 50-52]). Bostic further teaches applying claim-processing rules and retrieving claim-related information from databases to determine claim outcomes (see Bostic ¶¶ [21, 40 & 42]).
Canovi teaches evaluating insurance claims subject to subrogation using statistical models and generating recovery outcomes and strategies (see Canovi ¶¶ [54-56 & 62]).
Canovi further teaches determining recovery strategies for insurance claims based on claim characteristics and recovery likelihood, including selecting settlement, arbitration, or litigation strategies for recovery against an adverse carrier (see Canovi ¶¶ [54, 56 & 65]).
It would have been obvious to a person of ordinary skill in the art to apply the evaluation techniques of Canovi within the claim-processing system of Bostic to determine appropriate recovery actions for subrogation demands based on the characteristics of the insurance claim.
As per Claims 30 & 37, the claims are rejected for the same reasons discussed above with respect to claim 23.
As per Claims 31 & 38, the claims are rejected for the same reasons discussed above with respect to claim 24.
As per Claims 32 & 39, the claims are rejected for the same reasons discussed above with respect to claim 25.
As per Claim 33, the claim is rejected for the same reasons discussed above with respect to claim 26.
As per Claim 34, the claim is rejected for the same reasons discussed above with respect to claim 27.
As per Claims 35 & 41, the claims are rejected for the same reasons discussed above with respect to claim 28.
As per Claim 36, the claim is rejected for the same reasons discussed above with respect to claim 22.
As per Claim 40, the claim is rejected for the same reasons discussed above with respect to claim 36. The additional limitations recites that the list of subrogation demands includes fields such as a subrogee identity, insurance claim type, jurisdiction, loss amount, and settlement payment amount. Bostic teaches retrieving and storing claim attributes associated with insurance claims, including claim details such as loss information, claim type, and related claim data (see Bostic ¶¶ [50-52]). These attributes correspond to the recited information fields.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TONY P KANAAN whose telephone number is (571)272-2481. The examiner can normally be reached Monday- Friday 7:30am - 3:30 pm EST.
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/T.P.K./Examiner, Art Unit 3696
/MATTHEW S GART/Supervisory Patent Examiner, Art Unit 3696