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 .
Priority
Acknowledgement is made this application claims priority to Provisional Application # 18/984,289 filed on 12/19/2023.
Claim Rejections - 35 USC § 112
1. The following is a quotation of the second paragraph of 35 U.S.C. 112:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
2. Claim 30 is rejected under 35 U.S.C. § 112, second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which applicant regards as the invention.
Claim 30 is not sufficiently precise due to the combining of two separate statutory classes (computer program product and process of invention in a single claim.
Claim Rejections - 35 USC § 101
1. 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.
2. Claims 30 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to non-statutory subject matter.
35 USC 101 requires that in order to be patentable the invention must be a "new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof" (emphasis added).
3. The applicants claims mentioned above are intended to embrace or overlap two different statutory classes of invention as set forth in 35 USC 101.
Claim 30 recites “a hybrid product/process” comprising two statutory classes of invention in a single claim.
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 1-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
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. Examples of abstract ideas include fundamental economic practices; certain methods of organizing human activities; and mathematical relationships/formulas. Alice Corporation Pty. Ltd. v. CLS Bank International, et al., 573 U.S. ____ (2014).
In the instant case, claims 1-30 are directed to system and method generating a side-by-side comparison of the plurality of augmented entities and the plurality of clauses against quote asks across insurance documents based on comparison of the insurance documents.
The claims 1-30 are analyzed to see if claims are statutory category of invention, recites judicial exception and the claims are further analyzed to see if the claims are integrated into practical application if the judicial exception is recited and the claims provides an inventive as per 2019 Revised Patent Subject Matter Eligibility Guidance (2019 PEG, October 2019 Update: Subject Matter Eligibility and 2024 Guidance Update on Patent Subject Matter Eligibility, including Artificial Intelligence as set forth below:
Analysis:
Step 1: Statutory Category? This part of the eligibility analysis evaluates whether the claim falls within any statutory category. MPEP 106.03.
Claim 1 is directed to a system comprising at least a memory device and a processor, for analyzing insurance document. The claimed system is therefore directed to a statutory category, i.e., a machine (a combination of device) (Step 1: YES).
Claim 16 is directed to a process; i.e., a series of a computer-implemented method steps or acts, for analyzing insurance document. A process is one of the statutory categories of invention (Step 1: YES).
Claim 30 is directed to a computer program product, which is a manufacture. The claim, thus a statutory category of invention (Step 1: YES).
Step 2A - Prong 1: Judicial Exception Recited? This part of the eligibility analysis evaluates whether the claim recites a judicial exception. As explained in MPEP 2106.04(II) and the October 2019 Update, a claim “recites” a judicial exception when the judicial exception is “set forth” or “described” in the claim. There are no nature- based product limitations in this claim, and thus the markedly different characteristics analysis is not performed. However, the claim still must be reviewed to determine if it recites any other type of judicial exception.
Claims 1, 16 and 30 are similar and they are then analyzed to determine whether it is directed to a judicial exception. The claim recite plurality of steps of “receiving two or more insurance documents associated with insurance products, determining a plurality of entities from each insurance document, augmenting the plurality of entities using data from third part data sources, contextualizing and summarizing contents of a plurality of clauses of the two or more insurance documents;, and comparing a plurality of augmented entities and the plurality of clauses across the two or more insurance documents.”
The limitations of “receiving insurance documents, determining a plurality of entities from each insurance document, augmenting the plurality of entities using data, contextualizing and summarizing contents of a plurality of clauses and comparing a plurality of augmented entities and the plurality of clauses across the two or more insurance documents”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “memory and processor,” nothing in the claim element precludes the step from practically being performed in the mind and thus fall within the “mental processes” grouping of abstract idea set forth in the 2019 PEG. 2019 PEG Section I, 84 Fed. Reg. at 52. For example, but for the “by processor” language, “receive, determining, augmenting, contextualizing and comparing”, in the context of this claim encompasses the user manually perform recited steps. The recitation of a “processor/server” in this claim does not negate the mental nature of these limitations because the claim here merely uses the AI as a tool to perform the otherwise mental processes. See October Update at Section I(C)(ii). Thus, the above limitations of recite concepts that fall into the “mental process” grouping of abstract ideas. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas (YES).
Step 2A - Prong 2: Integrated into a Practical Application? This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception. This evaluation is performed by (a) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (b) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. 2019 PEG Section III(A)(2), 84 Fed. Reg. at 54-55.
Besides the abstract idea as described in Prong 1, the claim recites the additional elements of the computing device performing “generating a side-by-side comparison of the plurality of augmented entities and the plurality of clauses against quote asks across insurance documents based on comparison of the insurance documents.” The processor/server in the step is recited at a high level of generality, i.e., as a generic processor performing a generic computer function automates tracking and displaying. The recitation of processor without further details that represent no more than mere instructions to apply the judicial exception on a computer. These limitations can also be viewed as nothing more than an attempt to generally link the use of technological environment in which the judicial exception is performed. The additional element of “generating a side-by-side comparison of the plurality of augmented entities …” using processor is merely confines the use of the abstract idea to technological environment of processor and thus fails to add inventive concept to the claims . see MPEP 2106.05 (h). It should be noted that because the courts have made it clear that mere physicality or tangibility of an additional element or elements is not a relevant consideration in the eligibility analysis, the physical nature of these computer components does not affect this analysis. See MPEP 2106.05(I) for more information on this point, including explanations from judicial decisions including Alice Corp., Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 224-26 (2014).
An evaluation of whether limitations are insignificant extra-solution activity is then performed. Note that because the Step 2A Prong 2 analysis excludes consideration of whether a limitation is well-understood, routine, conventional activity (2019 PEG Section III(A)(2), 84 Fed. Reg. at 55), this evaluation does not take into account whether or not limitation (a) is well-known. See October 2019 Update at Section III.D. When so evaluated, this additional element represents mere data gathering, displaying and tracking/comparing/relating. The limitation of “generating a side-by-side comparison of the plurality of augmented entities and the plurality of clauses against quote asks across insurance documents based on comparison of the insurance documents “in the claim is an insignificant extra-solution activity.. But the AI is recited so generically without any details that it represents no more than mere instructions to apply the judicial exceptions on a computer. It can also be viewed as nothing more than an attempt to generally link the use of the judicial exceptions to the technological environment of a controller. It should be noted that because the courts have made it clear that mere physicality or tangibility of an additional element or elements is not a relevant consideration in the eligibility analysis, the physical nature of the computer does not affect this analysis. See MPEP 2106.05(I) for more information on this point, including explanations from judicial decisions including Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 224-26 (2014). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application and the claim is directed to the judicial exception (Step 2A: NO).
Step 2B: Claim provides an Inventive concept? This part of the eligibility analysis evaluates whether the claim as a whole amounts to significantly more than the recited exception, i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. MPEP 2106.05.
As explained with respect to Step 2A Prong 2, there are two additional elements.
The first is the processor/device, which is configured to perform all the limitations recited. As explained previously, the processor is at best the equivalent of merely adding the words “apply it” to the judicial exception. Mere instructions to apply an exception cannot provide an inventive concept.
The second additional element is limitation of “generating a side-by-side comparison of the plurality of augmented entities and the plurality of clauses against quote asks across insurance documents based on comparison of the insurance documents”, which as explained previously is extra-solution activity, which for purposes of Step 2A Prong Two was considered insignificant. Under the 2019 PEG, however, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B. 2019 PEG Section III(B), 84 Fed. Reg. at 56. At Step 2B, the evaluation of the insignificant extra-solution activity consideration takes into account whether or not the extra-solution activity is well-known. See MPEP 2106.05(g). Here, the recitation of a processor being configured to generating a side-by-side comparison of the plurality of augmented entities and the plurality of clauses against quote asks across insurance documents based on comparison of the insurance documents” for implementation of applicant’s invention according to the definition that is recited at a high level of generality, and, as disclosed in the specification, is also well-known. This limitation therefore remains insignificant extra-solution activity even upon reconsideration. Thus, limitation (a) does not amount to significantly more. Even when considered in combination, these additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, which do not provide an inventive concept (Step 2B: NO). The claim is not eligible.
The concept of “generating a side-by-side comparison of the plurality of augmented entities and the plurality of clauses against quote asks across insurance documents based on comparison of the insurance documents” is similar to “receiving data from plurality of data sources, displaying the data analysis results and diagnosis of events, displaying the concurrent visualization of measurements from the data streams, accumulating and updating visualization measurement from data stream and dynamic stability metrics and deriving a composite indicator of reliability of power grid vulnerability derived from the updated real-time visualization measurement” in Electric Power Group., LLC v. Alstom S.A., 830 F.3d 1350, 1354 (Fed. Cir. 2016). The court in Electric Power Group ruling found that claim focused on the combination of abstract-idea processes process of gathering and analyzing information of a specified content, then displaying the results, and not any particular assertedly inventive technology for performing those functions, and therefore are considered to be directed to an abstract idea. The court further argued that “The claims in this case specify what information in the power-grid field it is desirable to gather, analyze, and display, including in “real time”; but they do not include any requirement for performing the claimed functions of gathering, analyzing, and displaying in real time by use of anything but entirely conventional, generic technology. The claims therefore do not state an arguably inventive concept in the realm of application of the information-based abstract ideas.”
The claims as presented is a formula in isolation and it is not analogous to claims found in eligible Diamond v. Diehr which imposed meaningful limits that apply the formula to improve an existing technological process of transforming raw and uncured rubber to cured molded rubber. The computer in the Diehr precisely determines when to open the press and eject the cured rubber perfectly curing the rubber by repeatedly calculating the rubber cure time from this temperature measurement and comparing the computed cure time to the actual elapsed time. The steps of continuously measuring temperature and repeatedly recalculating the rubber cure time and comparing it to the elapsed time were new steps that were found to be worthy of patent protection in the Diehr, which is not comparable to “generating a side-by-side comparison of the plurality of augmented entities and the plurality of clauses against quote asks across insurance documents based on comparison of the insurance documents” as recited in the instant claims. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims is not patent eligible. (NO).
Dependent Claims:
Examiner further reviewed the dependent claims 2-15 and 17-29 that could be added to the independent claims to make patent eligible. The dependent claims as recited pertains to additional steps which further describes “classify, identifying, comparing, contextualizing, summarizing, differences and similarities, clauses in the documents, recommending optimum insurance coverage, identify coverage gaps, generate certificate of insurance and create accuracy score”, which appear to be a mental process/mathematical formula/relationship using a generic computer component that been found to be an abstract idea as described above. These dependent claims do not provide additional elements significantly more than the purported abstract idea 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 dependent claims as recited would not make the independent claim significantly more by incorporating them into the independent claims. Therefore, claims 1-30 are not patent eligible (NO).
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.
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 non-obviousness.
Claims 1-30 are rejected under 35 U.S.C. 103 as being unpatentable over Lovlie et al., U.S. Pub No. 2008/0222072 (reference A in PTO-892) in view of Ma, Jian , Chinese Application No. CN 114399396A (reference N in attached PTO-892).
As per claim 1, Lovlie et al. teach a system for analyzing insurance documents and recommending an optimum insurance product, comprising:
a server comprising: a memory to store one or more modules; and a processor configured to execute the one or more modules (see Fig. 1, Server (101: Fig. 2: paragraph [0014-0016), to perform:
receiving two or more insurance documents associated with insurance products from a user device, wherein the insurance documents is at least one of an insurance quote document, an insurance policy document, an insurance contract, a certificate of insurance (COI) request form, or combination thereof (see abstract, Fig. 4 and 5: paragraph [0020, 0025]; where user select one or more insurance policies to compare each other);
determining a plurality of entities from each insurance document, wherein the plurality of entities correspond to at least one of an quote information, a policy information, an insurance contract information, an insurance request information or combination thereof (see Fig. 4, Compare policies and get quotes; Fig. 8, Insurance Providers (Zurich, Norwich Union,…. Llyod TSB: paragraph [0014]; where best quoted from plurality of insurance provider is obtained by comparison);
augmenting, using an augmentation module, the plurality of entities using data from third part data sources; contextualizing and summarizing, using a contextualizing and summarizing module, contents of a plurality of clauses of the two or more insurance documents at a document level using a clause library and a domain specific prompt library (see Fig. 5: paragraph [002-0023]; Fig. 8, Insurance Provider: Pitfalls, Features and Compare, Compare Selected: paragraph [0028-0029]; where data of plurality of insurance companies policies with regards to pitfalls and policies are augmented, compared and displayed);
comparing, using a comparison module, a plurality of augmented entities and the plurality of clauses by leveraging contextualized and summarized contents of the two or more insurance documents, across the two or more insurance documents; and generating, on a user interface, a side-by-side comparison of the plurality of augmented entities and the plurality of clauses against quote asks across the two or more insurance documents based on comparison of the two or more insurance documents (see Fig. 8, Compare Selected (804), Number of Insurance Company (803): paragraph [0028]; where plurality of different insurance companies displayed in Fig. 8 selected by clicking box 803 in display and results of comparison displayed in section 804).
Lovlie et al. do not each determining a plurality of entities from each insurance document using a combination of one or more machine learning models and one or more large language models.
Ma teaches determining a plurality of entities from each insurance document using a combination of one or more machine learning models and one or more large language models (see page 10, 4th paragraph).
Therefore, it would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to allow determining a plurality of entities from each insurance document using a combination of one or more machine learning models and one or more large language models to Lovlie et al. because Ma teaches including above features would enable to identify insurance entities in the Roberta Large language Model (see page 10, 4th and last paragraph).
As per claim 2, Lovlie et al. teach claim 1 as described above. Lovlie et al. further teach the system, wherein,
after receiving the two or more insurance documents from the user device, the processor is configured to classify, using a classification, transformation and enhancing (CTE) module, each insurance document based on a type and a line of business that each insurance document associated with;
identify, using a context filtering module, one or more pages of each insurance document comprising at least one of a quote data, a policy data, or an insurance contract data, a COI request data, combination thereof; and
trigger, using a triggering module, one or more models for comparison of the two or more insurance documents based on classification of each insurance document and identified pages of each insurance document, wherein the processor is further configured to provide identified pages of each insurance document as an input to triggered one or more models.
As per claim 3, Lovlie et al. teach claim 1 as described above. Lovlie et al. further teach the system, wherein the processor determines the plurality of entities from each insurance document by
identifying, using an entity recognition module, the plurality of entities that are immediately apparent from the two or more insurance documents using the domain specific prompt library (see Fig. 4, Compare Policies: Provider (403), Type (404),Go (405) and Policy Chart: Type (406), Go (407); paragraph [0020]);
determining, using quote and policy models, relationship between identified entities and the plurality of clauses, further, to determine whether changes in clauses impact applicability, values, and interactions of the identified entities within the insurance documents (see Fig. 8, Features and Pitfalls: paragraph [0028]; where relationship of plurality of insurance compared with respect to policy document features); and
contextualizing and extracting, using a contextual extraction module, the plurality of entities that are not be immediately apparent in the two or more insurance documents by leveraging relationship determined by the quote and policy models (see paragraph [0029-0030]).
As per claim 4, Lovlie et al. teach claim 1 as described above. Lovlie et al. further teach the system, wherein the processor is further configured to
color code differences and similarities across the two or more insurance documents with respect to entities and clauses associated with each insurance document (see abstract; Fig. 8, Pitfalls, Features; paragraph [0028-0029]; where color code for positive policy features and pitfalls of policies documents from different insurance companies by indicating strength of each features).
As per claim 5, Lovlie et al. teach claim 1 as described above. Lovlie et al. further teach the system configured to
generate, on the user interface, a side-by-side comparison across source documents of the two or more insurance documents with respect to entities and clauses associated with each insurance document (see Fig. 8, Compare Selected (804), Insurance Company Selection Box (803): paragraph [0022, 0028]; where insurance document with specific features and pitfalls compared and displayed each compared insurance companies).
As per claim 6, Lovlie et al. teach claim 1 as described above. Lovlie et al. further teach the system configured to
wherein the plurality of entities comprises at least one of a name of an insured, an address of the insured, a policy number, a name of a carrier, a location schedule, an agency name and address, terrorism, limits, premium, dates, deductibles, exclusions, endorsements, coverage types, a name of COI requester name, an address of COI requester, a name of COI holder, an address of COI holder, a project information, or combination thereof( see Fig. 8. Name of Carrier: Zurich, Norwich Union…..Its4met).
As per claim 7, Lovlie et al. teach claim 1 as described above. Lovlie et al. further teach the system, wherein the plurality of clauses comprises at least one of
an exclusion clause, an endorsement clause, definitions, coverage terms, conditions, limitations, premium payment terms, a cancellation clause, a renewal clause, a dispute resolution clause, a territorial limits clause, subrogation, co-insurance clause, or a liability clause (see paragraph [0022 and 0029]; where plurality of insurance clauses that are analyzed included exceptions to insurance conditions of insurance, policy high excess for people under certain age, foreign travel coverage etc.).
As per claim 8, Lovlie et al. teach claim 1 as described above. Lovlie et al. further teach the system configured to
summarize, using a summarization module, a comparison data of the two or more insurance documents (see paragraph [0029-0039]; where user receive summarize availability certain coverage user need by comparing insurance document of insurance companies such as whether not coverage provided for foreign travel, high excess for certain age).
Claims 9-15 are rejected under 35 U.S.C. 103 as being unpatentable over Lovlie et al., U.S. Pub No. 2008/0222072 (reference A in PTO-892)in view of Ma, Jian , Chinese Application No. CN 114399396A (reference N in attached PTO-892) further in view of Hopkins, U.S. Patent No. 7,983,938 (reference B in attached PTO-892).
As per claim 9, Lovlie et al. teach claim 1 as described above. Lovlie et al. further teach
when the two or more insurance documents comprise at least one of
two or more insurance quote documents, corresponding two or more insurance policy documents, or combination thereof (see Fig. 4, Compare Policies and Get Quotes),
Lovlie et al. do not teach the processor is further configured to recommend, using a recommendation module, the optimum insurance coverage by leveraging comparison data of the two or more insurance documents.
Hopkins teaches the processor is further configured to recommend, using a recommendation module, the optimum insurance coverage by leveraging comparison data of the two or more insurance documents (see Fig. 3F, Step 348 : Yes; Fig. 8b , Competitive Selective Recommendation (864): column 12, lines 15-23).
Therefore, it would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to allow recommend, using a recommendation module, the optimum insurance coverage by leveraging comparison data of the two or more insurance documents to Lovlie et al. because Hopkins teaches including above features would enable ascertain an optimum balance between appropriate coverage levels and acceptable premium costs (see column 1, lines 50-57).
As per claim 10, Lovlie et al. teach claim 1 as described above. Lovlie et al. further teach
the system, wherein the processor is further configured to
generate placement insights by analyzing a plurality of historical insurance products opted by various customers in different line of business and determining trends and patterns of at least one of purchasing of coverages, limits, premium ranges, and endorsements, purchasing of insurance products, common exclusions, top carriers by premium, top brokers by carrier according to a line of business.
As per claims 10-11, Lovlie et al. teach claim 1 as described above.
Lovlie et al. further do not teach generate placement insights by analyzing a plurality of historical insurance products opted by various customers in different line of business and determining trends and patterns of at least one of purchasing of coverages, limits, premium ranges, and endorsements, purchasing of insurance products, common exclusions, top carriers by premium, top brokers by carrier according to a line of business; recommend at least one of optimum insurance products, insurance carriers, insurance brokers, or an insurance market for a customer based on the placement insights; and obtain the plurality of insurance documents based on recommended insurance products and/or insurance carriers or market, for comparison.
Hopkins teaches generate placement insights by analyzing a plurality of historical insurance products opted by various customers in different line of business and determining trends and patterns of at least one of purchasing of coverages, limits, premium ranges, and endorsements, purchasing of insurance products, common exclusions, top carriers by premium, top brokers by carrier according to a line of business; recommend at least one of optimum insurance products, insurance carriers, insurance brokers, or an insurance market for a customer based on the placement insights; and obtain the plurality of insurance documents based on recommended insurance products and/or insurance carriers or market, for comparison (see Fig. 8b, Competitive #1, 2, 3, 4 Premium (852, 854 and 856: column 21, lines 27-41; when optimum recommendation based comparison with competitor policy parameter in the insurance documents).
Therefore, it would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to allow above features to Lovlie et al. because Hopkins teaches including above features would enable perform analysis of competitive policies with equivalent coverage and recommend optimum policy choice (see abstract).
As per claim 12, Lovlie et al. teach claim 1 as described above.
Lovlie et al. further do not teach recommend, using the recommendation module, the optimum insurance product based on comparison of the two or more insurance documents as well as based on at least one of the placement insights, north American industry classification system (NAICS) code or standard industrial classification (SIC) code, revenue and other business profile, state or jurisdiction of operations a line of business, and insurer's risk to appetite.
Hopkins teaches recommend, using the recommendation module, the optimum insurance product based on comparison of the two or more insurance documents as well as based on at least one of the placement insights, north American industry classification system (NAICS) code or standard industrial classification (SIC) code, revenue and other business profile, state or jurisdiction of operations a line of business, and insurer's risk to appetite (see Fig. 8b, Competitive #1, 2, 3, 4 Premium (852, 854 and 856: column 21, lines 27-41; where optimum recommendation based comparison with competitor policy coverage descriptions in the insurance documents for a total premium/revenue).
Therefore, it would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to allow recommend, using the recommendation module, the optimum insurance product based on comparison of the two or more insurance documents as well as based on at least one of the placement insights, north American industry classification system (NAICS) code or standard industrial classification (SIC) code, revenue and other business profile, state or jurisdiction of operations a line of business, and insurer's risk to appetite to Lovlie et al. because Hopkins teaches including above features would enable perform analysis of competitive policies with equivalent coverage and recommend optimum policy choice (see abstract).
As per claim 13, Lovlie et al. teach claim 1 as described above. Lovlie et al. further The system, wherein,
when the two or more insurance documents comprise a new insurance policy and at least one of prior year insurance policy (see Fig. 3, paragraph [0017]; where user compare existing policy with any other selected policies), the processor is further configured to
Lovlie et al. do not teach identify at least one of errors and omissions, and any coverage gaps in the new insurance policy over the at least one of prior year insurance policy by leveraging comparison data of the two or more insurance documents; and communicate identified errors and omissions and/or any coverage gaps to corresponding parties to revise quote offering and/or policies, wherein revised quote offering and/or policies are further used for comparison.
Hopkins teaches identify at least one of errors and omissions, and any coverage gaps in the new insurance policy over the at least one of prior year insurance policy by leveraging comparison data of the two or more insurance documents; and communicate identified errors and omissions and/or any coverage gaps to corresponding parties to revise quote offering and/or policies, wherein revised quote offering and/or policies are further used for comparison (see Fig. 6, Coverage Disparity (664), Current Premium (6660, Adjusted Premium (668), Recommended Changes (648), Competitive Quote (684) and Create New Policy (686): column 16, lines 31-50).
Therefore, it would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to allow identify at least one of errors and omissions, and any coverage gaps in the new insurance policy over the at least one of prior year insurance policy by leveraging comparison data of the two or more insurance documents; and communicate identified errors and omissions and/or any coverage gaps to corresponding parties to revise quote offering and/or policies, wherein revised quote offering and/or policies are further used for comparison to Lovlie et al. because Hopkins teaches including above features would enable perform analysis of competitive policies with equivalent coverage and recommend optimum policy choice for claims against bodily inf]jury (see abstract, column 16, lines 31-40).
Claims 14 is rejected under 35 U.S.C. 103 as being unpatentable over Lovlie et al., U.S. Pub No. 2008/0222072 (reference A in PTO-892) in view of Ma, Jian , Chinese Application No. CN 114399396A (reference N in attached PTO-892) further in view of Teresi et al., U.S. Pub No. 2023/0119311 (reference C in attached PTO-892).
As per claim 14, Lovlie et al. teach claim 1 as described above.
Lovlie et al. do not teach when the two or more insurance documents comprise
the insurance contract and the COI request form, the processor is configured to generate, using a COI generation module, a certificate of insurance (COI) by leveraging comparison data of the two or more insurance documents, wherein the COI provides a proof of insurance coverage for an insured.
Teresi et al. teach when the two or more insurance documents comprise the insurance contract and the COI request form, the processor is configured to generate, using a COI generation module, a certificate of insurance (COI) by leveraging comparison data of the two or more insurance documents, wherein the COI provides a proof of insurance coverage for an insured (see paragraph [0009-0012 and 0020]).
Therefore, it would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to allow when the two or more insurance documents comprise the insurance contract and the COI request form, the processor is configured to generate, using a COI generation module, a certificate of insurance (COI) by leveraging comparison data of the two or more insurance documents, wherein the COI provides a proof of insurance coverage for an insured to Lovlie et al. because Teresi et al. teach including above features would enable leverages underlying data in continuous fashion to prove insurance coverage (see abstract, column 16, lines 31-40).
Claims 15 is rejected under 35 U.S.C. 103 as being unpatentable over Lovlie et al., U.S. Pub No. 2008/0222072 (reference A in PTO-892) in view of Ma, Jian , Chinese Application No. CN 114399396A (reference N in attached PTO-892) further in view of Fang et al., et al., Chinese Application No. CN 112035688A (reference M in attached PTO-892).
As per claim 15, Lovlie et al. teach claim 1 as described above.
Lovlie et al. do not teach create, using a scoring module, an accuracy score indicating an accuracy of extracted information across the insurance documents and an automation score indicating level of automation achieved in identifying, extracting, comparing, and summarizing data across the insurance documents.
Fang et al. teach create, using a scoring module, an accuracy score indicating an accuracy of extracted information across the insurance documents and an automation score indicating level of automation achieved in identifying, extracting, comparing, and summarizing data across the insurance documents (see page 22, 2nd to 5th paragraph).
Therefore, it would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to allow create, using a scoring module, an accuracy score indicating an accuracy of extracted information across the insurance documents and an automation score indicating level of automation achieved in identifying, extracting, comparing, and summarizing data across the insurance documents to Lovlie et al. because Fang et al. teach including above features would enable improve automation degree of the system (see page 22, 5th paragraph).
As per claim 16, Lovlie et al. teach a computer implemented method for analyzing insurance documents and recommending an optimum insurance product, comprising steps as described in the claim 1 as described above.
As per claims 17-29, Lovlie et al. teach the claim 16 as described above. Lovlie et al. further teach claims 17-29 in the same rational as the claims 2-13 and 15 as described above.
30. As per claims 30, Lovlie et al. teach a computer program product comprising a non-transitory computer-readable storage medium having computer-readable instructions stored thereon, computer-readable instructions being executable by a computerized device comprising processing hardware to execute a method (see Fig. 1, Server (101: Fig. 2: paragraph [0014-0016) comprising steps as described in the claim 1 above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosures. The following are pertinent to current invention, though not relied upon:
Clawson, II et al. (U.S. Patent No. 9,652,805) teach multiple product quoting facilitating purchase of multiple insurance products.
Samarashinghe et al. (2021) teach vehicle insurance policy document summarizer AI insurance agent and on-the-spot claimer.
Fox et al. (U.S. Patent No. 10,032,225) teach augmented reality insurance applications.
Wade et al. (U.S. Patent No. 8,719,063 teach comparing information in a process for issuing insurance policies.
Vocola (U.S. Patent No. 8,615,414) teaches optimizing insurance policies.
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Respectfully submitted,
/BIJENDRA K SHRESTHA/Primary Examiner, Art Unit 3691 05/01/2026
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