DETAILED ACTION
Notice of 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 .
Response to Amendment
The amendment filed 2026-06-09 has been entered and fully considered.
Response to Arguments
Applicant’s arguments, see pages 1-3, filed 2026-06-09, with respect to the rejection of claims 1, 7, and 12 under 35 U.S.C. § 101 have been fully considered but they are not persuasive.
In response to applicant’s argument that the claimed invention passes Step 2A, prong 1, Step 2A, prong 2, and Step 2B, the Examiner respectfully disagrees.
Applicant first argues that the claims are not directed to an abstract idea because the claims are not a result-oriented recitation of a desired outcome; but that it is (allegedly) rather a concretely specified computational architecture with defined training methodology, defined model structure, and defined functional behavior at each tier. The Examiner respectfully disagrees. First, the Examiner notes that the claim does not actually positively recite the layered, multi-modal machine learning system as an element of the claimed system. Instead, it merely claims it as a tool being used by the system. Further note that the alleged “specific technical architecture” is claimed at the highest level of generality – for example, claiming a “specialized model” without providing structure of this specialization. Thus, the claims are merely using a computer as a tool to perform the concept; See MPEP § 2106.04(a)(2)(III)(C).
Applicant then argues that the claims integrate that idea into a practical application constituting a concrete improvement to computer-implemented scam detection technology. Applicant first alleges that conventional scam detection systems do not open or read the attachments to analyze the actual content embedded within; however, this is demonstrably false, as seemingly every spoof or phishing detection system analyzes the content of a message (the Examiner would be impressed and disturbed to find phishing-detection software that did not analyze content). Second, applicant notes that training a general ML model on a corpus of known legitimate and fraudulent communications, then training a separate specialized model using a segmented approach across multiple distinct scam categories, and dynamically routing a communication through both tiers to produce a calibrated risk score is not a process of human observation, evaluation, or judgment. The Examiner notes that, one, a human can perform this evaluation on a very limited scale (scale of training is not claimed), and two, the claims do not require any training of the datasets of the LLM. That is, similar to the claim, a human can (and in a very trivial fashion) use an LLM as a tool, but such use does not per se equate to a practical application.
Finally, applicant argues that the claimed combination constitutes an inventive concept well beyond generic computer implementation, as the Examiner allegedly only considered the elements individually and not as a whole. The Examiner notes that the rejection considered the general concept as claimed – generating a scam risk score based on an aggregation of deterministic checks and probabilistic analyses on attributes of a communication. The Examiner further notes the claim limitations are not “significantly more” than the abstract idea, as the individual limitations provide almost no further clarity or limitation. They’re effectively a bunch of nondescript checks or analysis, e.g. “performing a series of deterministic checks” and “performing a series of probabilistic analyses”, that are aggregated and scored in a nondescript fashion. The most limiting feature of the claim is the “multi-modal machine learning mode”, and that’s just a tool being used and not even an element of the system itself. Thus, there’s no support to the allegation that the nondescript concept is not routine, conventional, or well-understood.
Thus, the Examiner respectfully submits that the 35 U.S.C. § 101 rejection of claims 1, 7, and 12 is proper.
Applicant’s arguments, see pages 3-4, filed 2026-06-09, with respect to the claim amendments overcoming the cited prior art references of the rejection of claims 1, 7, and 12 under 35 U.S.C. § 102(a)(1) have been fully considered and are persuasive. Therefore, the rejection has been withdrawn; however, upon further search and consideration, a new grounds of rejection – as necessitated by amendment – is made.
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, 7, and 12 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea (35 U.S.C. 101 Judicial Exception) without significantly more. The claims recite generating a scam risk score based on an aggregation of deterministic checks and probabilistic analyses on attributes of a communication, a form of observation, evaluation, judgment, and/or opinion, which is a concept performed in the human mind and thus grouped as Mental processes. This judicial exception is not integrated into a practical application because the generically recited computer elements do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, when considered separately and in combination, do not add significantly more to the abstract idea, as they are well-understood, routine, conventional computer functions as recognized by the courts.
Based upon consideration of all the relevant factors with respect to the claimed invention as a whole, the claims are determined to be directed to an abstract idea without significantly more. The rationale for this determination is explained infra:
The following are Principles of Law:
A patent may be obtained for “any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof”; 35 U.S.C. § 101. The Supreme Court has consistently held that this provision contains an important implicit exception: laws of nature, natural phenomena, and abstract ideas are not patentable; See Alice Corp. v. CLS Bank Int’l, 134 S. Ct. 2347, 2354 (2014); Gottschalk v. Benson, 409 U.S. 63, 67 (1972) (“Phenomena of nature, though just discovered, mental processes, and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work.”). Notwithstanding that a law of nature or an abstract idea, by itself, is not patentable, an application of these concepts may be deserving of patent protection; See Mayo Collaborative Servs. v. Prometheus Labs., Inc., 132 S. Ct. 1289, 1293–94 (2012). In Mayo, the Court stated that “to transform an unpatentable law of nature into a patent-eligible application of such a law, one must do more than simply state the law of nature while adding the words ‘apply it.’” Mayo, 132 S. Ct. at 1294 (citation omitted).
In Alice, the Court reaffirmed the framework set forth previously in Mayo “for distinguishing patents that claim laws of nature, natural phenomena, and abstract ideas from those that claim patent-eligible applications of these concepts.” Alice, 134 S. Ct. at 2355. The test for determining subject matter eligibility requires a first step of determining whether the claims are directed to a process, machine, manufacture, or composition of matter. If the claims are directed to one of the four patent-eligible subject matter categories, then the Examiner must perform a two-part analysis to determine whether a claim that is directed to a judicial exception recites additional elements that amount to significantly more than the exception. The first part of the second step in the analysis is to “determine whether the claims at issue are directed to one of those patent-ineligible concepts.” Id. If the claims are directed to a patent-ineligible concept, then the second part of the second step in the analysis is to consider the elements of the claims “individually and ‘as an ordered combination”’ to determine whether there are additional elements that “‘transform the nature of the claim’ into a patent-eligible application.” Id. (quoting Mayo, 132 S. Ct. at 1298, 1297). In other words, the second step in the analysis is to “search for an ‘inventive concept’‒ i.e., an element or combination of elements that is ‘sufficient to ensure that the patent in practice amounts to significantly more than a patent on the [ineligible concept] itself.’” Id. (brackets in original) (quoting Mayo, 132 S. Ct. at 1294). The prohibition against patenting an abstract idea “cannot be circumvented by attempting to limit the use of the formula to a particular technological environment or adding insignificant post-solution activity.” Bilski v. Kappos, 561 U.S. 593, 610–11 (2010) (citation and internal quotation marks omitted). The Court in Alice noted that “[s]imply appending conventional steps, specified at a high level of generality,” was not “enough” [in Mayo] to supply an “‘inventive concept.’” Alice, 134 S. Ct. at 2357 (quoting Mayo, 132 S. Ct. at 1300, 1297, 1294).
In the “2019 Revised Patent Subject Matter Eligibility Guidance” (2019 PEG), the USPTO has prepared revised guidance for use by USPTO personnel in evaluating subject matter eligibility based upon rulings by the courts.
The Examiner is bound by and applies the framework as set forth by the Court in Mayo and reaffirmed by the Court in Alice and follows the 2019 PEG for determining whether the claims are directed to patent-eligible subject matter.
Step 1: Are the claims at issue directed to a process, machine, manufacture, or composition of matter?
The Examiner finds that the claims are directed to one of the four statutory categories.
Step 2A – Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon?
The Examiner finds that the claims are directed to the abstract idea of generating a scam risk score based on an aggregation of deterministic checks and probabilistic analyses on attributes of a communication, a form of observation, evaluation, judgment, and/or opinion, which is a concept performed in the human mind and thus grouped as Mental processes.
Step 2A – Prong Two: Does the claim recite additional elements that integrate the Judicial Exception into a practical application?
The abstract idea is not integrated into a practical application because the generically recited computer elements do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer.
In determining whether the abstract idea was integrated into a practical application, the Examiner has considered whether there were any limitations indicative of integration into a practical application, such as:
(1) Improvements to the functioning of a computer, or to any other technology or technical field; See MPEP § 2106.05(a)
(2) Applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition; See Vanda Memo (Recent Subject Matter Eligibility Decision: Vanda Pharmaceuticals Inc. v. West-Ward Pharmaceuticals)
(3) Applying the judicial exception with, or by use of, a particular machine; See MPEP § 2106.05(b)
(4) Effecting a transformation or reduction of a particular article to a different state or thing; See MPEP § 2106.05(c)
(5) Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception; See MPEP § 2106.05(e) and Vanda Memo
The Examiner notes that clam features of: generating a scam risk score based on an aggregation of deterministic checks and probabilistic analyses on attributes of a communication do not improve the functioning of a computer or technical field, do not effect a particular treatment or prophylaxis for a disease or medical condition, do not apply or use a particular machine, do not effect a transformation or reduction of a particular article to a different state or thing, and do not apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
Instead of a practical application, the claim features of generating a scam risk score based on an aggregation of deterministic checks and probabilistic analyses on attributes of a communication merely use a general-purpose computer as a tool to perform the abstract idea (See MPEP § 2106.05(f)) and merely generally link the use of the abstract idea to a field of use (See MPEP § 2106.05(h)). Thus, the Examiner finds that the claimed invention does not recite additional elements that integrate the Judicial Exception into a practical application.
Step 2B: Is there something else in the claims that ensures that they are directed to significantly more than a patent-ineligible concept?
The claims, as a whole, require nothing significantly more than generic computer implementation or can be performed entirely by a human. The additional element(s) or combination of element(s) in the claims other than the abstract idea per se amount to no more than recitation of generic computer structure (e.g. processor and memory) that serves to perform generic computer functions (e.g. receive a communication, parse the communication, perform deterministic checks, perform probabilistic analyses, aggregate the results, generate a scam risk score and recommendations, and present the scam risk score and the recommendations) that are well-understood, routine, and conventional activities previously known to the pertinent industry. The claimed communication, communication information, attributes, machine learning models, known legitimate communications, known fraudulent communications, results, scam risk score, recommendations are all numbers, data structures, or datum. Each of these elements are individually dispositive of patent eligibility because of the following legal holdings:
“Data in its ethereal, non-physical form is simply information that does not fall under any of the categories of eligible subject matter under section 101.” Digitech Image Techs., LLC v. Electronics for Imaging, Inc., 758 F.3d 1344, 1350 (Fed. Cir. 2014).
The Supreme Court has also explained that “[a]bstract software code is an idea without physical embodiment,” i.e., an abstraction. Microsoft Corp. v. AT&T Corp., 550 U.S. 437, 449 (2007).
A claim that recites no more than software, logic, or a data structure (i.e., an abstract idea) – with no structural tie or functional interrelationship to an article of manufacture, machine, process or composition of matter does not fall within any statutory category and is not patentable subject matter; data structures in ethereal, non-physical form are non-statutory subject matter. In re Warmerdam, 33 F.3d 1354, 1361 (Fed. Cir. 1994); see Nuijten, 500 F.3d at 1357.
Furthermore, the claimed invention does not have a specific asserted improvement in computer capabilities, nor is it a specific implementation of a solution to a problem in the software arts; See Enfish, LLC v. Microsoft Corp., 822 F.3d 1327 (Fed. Cir. 2016). Rather, the claims are merely directed towards generating a scam risk score based on an aggregation of deterministic checks and probabilistic analyses on attributes of a communication, which is similar to ideas that the courts have found to be abstract, as noted supra, and the claims are without a “practical application” or anything “significantly more”.
Considering each of the claim elements in turn, the function performed by the computer system at each step of the process does no more than require a generic computer to perform a well-understood, routine, and conventional activity at a high level of generality. For example, “receiving a communication” is merely receiving or transmitting data over a network, which has been found by the courts to be a well-understood, routine, conventional activity in computers; See e.g. Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network). Further, “parsing the received communication information”, “performing a series of deterministic checks”, “performing a series of probabilistic analyses”, “aggregating the results”, and “generating recommendations” are merely forms of performing repetitive calculations, which has been found by the courts to be a well-understood, routine, conventional activity in computers; See e.g. Flook, 437 U.S. at 594, 198 USPQ2d at 199 (recomputing or readjusting alarm limit values); Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012) (“The computer required by some of Bancorp’s claims is employed only for its most basic function, the performance of repetitive calculations, and as such does not impose meaningful limits on the scope of those claims.”).
The prohibition against patenting an abstract idea “cannot be circumvented by attempting to limit the use of the formula to a particular technological environment or adding insignificant post-solution activity.” Bilski v. Kappos, 561 U.S. 593, 610–11 (2010) (citation and internal quotation marks omitted). The Court in Alice noted that “[s]imply appending conventional steps, specified at a high level of generality,” was not “enough” [in Mayo] to supply an “‘inventive concept.’” Alice, 134 S. Ct. at 2357 (quoting Mayo, 132 S. Ct. at 1300, 1297, 1294).
Viewed as a whole, the claims simply recite the steps of using generic computer components. The claims do not purport, for example, to improve the functioning of the computer system itself. Nor does it affect an improvement in any other technology or technical field. Instead, the claims amount to nothing significantly more than an instruction to implement the abstract idea using generic computer components. This is insufficient to transform an abstract idea into a patent-eligible invention.
The dependent claims likewise incorporate the deficiencies of a claim upon which they ultimately depend and are also directed to non-patent-eligible subject matter.
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 of this title, 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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
Claims 1, 7, and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Leddy et al. (US Pre-Grant Publication No. 20200067861-A1, hereinafter “Leddy”) in view of Bramberger et al. (US Pre-Grant Publication No. 20190122258-A1, hereinafter “Bramberger”).
With respect to independent claim 1, Leddy discloses:
one or more processors {para. 0054: “a processor”}.
a memory storing instructions that, when executed by the one or more processors, cause the system to perform operations comprising {para. 0054: “instructions stored on and/or provided by a memory coupled to the processor”}:
receiving a communication comprising communication information {para. 0062: “Messages 162 are obtained”}.
parsing the received communication information to extract attributes of the communication information {para. 0063: “parsing incoming messages and extracting components/features/elements (e.g., phrases, URLs, IP addresses, etc.) from the message”}.
performing a series of deterministic checks on the attributes {paras. 0065-0114: “filter array includes multiple filters, such as URL filter 166 and phrase filter 168”, for example “Is an email internal (i.e., sent from a mail server associated with the same enterprise as the recipient)?”}.
performing a series of probabilistic analyses on the attributes {paras. 0065-0114: “a rule comprises one or more filters along with a threshold or other decision selection method” that can create “a distinct score”}, wherein the probabilistic analyses comprise using a … machine learning model trained on known legitimate communications and known fraudulent communications {paras. 1150-1158: “Supervised learning based on curated examples”, wherein “human reviewers can identify whether messages are scam or not scam”}.
aggregating the results of the deterministic checks and probabilistic analyses to generate a scam risk score {paras. 0065-0114 & 0329: “add a score for” the result of each analysis portion, such that “scores are generated based on the filtering” and the “scores can be used to indicate the likelihood that the message is scam”}.
generating recommendations specific based on the generated scam risk score, deterministic checks, and probabilistic analyses {paras. 0287-0291 & 1869-1888: “platform 1600 would classify message 2300 … based on the two likelihood scores” and “an action determination engine 2624 that generates one or more recommendations of what to do with messages”}.
presenting the scam risk score and the recommendations to a user {paras. 0287-0291 & 1869-1888: providing the alert that “The email you sent us appears to be a scam. Please be careful to *not* respond to scammers, and do not click on links in their emails”}.
Although Leddy teaches performing a series of probabilistic analyses on the attributes using trained filters, Leddy does not explicitly disclose that the trained filter is a layered, multi-modal model; however, Bramberger discloses:
performing a series of probabilistic analyses on the attributes {paras. 0082-0085, 0101, and 0181: “probabilistically assessing” the “transaction records” of user accounts}, wherein the probabilistic analyses comprise using a layered, multi-modal machine learning model trained on known legitimate communications and known fraudulent communications {paras. 0082-0085, 0101, and 0181: “specialized neural networks are trained for specific types of fraud and the use of specialized feature sets”}.
wherein the layered, multi-modal machine learning model comprises a general model applied to the attributes against a broad set of known scam patterns to identify whether the communication resembles any previously flagged fraudulent activity; and a specialized model trained using a segmented approach based on different types of scams {paras. 0080-0085: “artificial intelligence system is configured to be trained, programmed, evolved, or otherwise brought into a state whereby the system is able to detect patterns of fraud as described in various embodiments herein”, e.g., “specialized neural networks are trained for specific types of fraud and the use of specialized feature sets”; the Examiner additionally notes that these limitations do not limit the structure of the claimed system itself and are merely descriptive of the model being utilized, and thus does not limit the scope of the claimed invention itself}.
Leddy and Bramberger are analogous art because they are from the same field of endeavor or problem-solving area of detecting fraud using artificial intelligence. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Leddy and Bramberger before him or her, to modify/develop the filter of Leddy’s system to utilize a layered, multi-modal machine learning model. The suggestion and/or motivation for doing so would have been because it is merely combining prior art elements according to known methods to yield predictable results, e.g., enables the filter to be more robust and accurate in identifying fraud based on the enhanced training. Therefore, it would have been obvious to combine the filter in Leddy’s system with a layered, multi-modal machine learning model to obtain the invention as specified in the instant claim(s). The Examiner notes that this motivation applies to all dependent and/or otherwise subsequently addressed claims.
With respect to dependent claim 7, Leddy discloses wherein the deterministic checks comprise opening and reading content of attachments from the communication to detect embedded scam messages {para. 0090: “scan the contents of the attachment and add a score related to the result”}.
With respect to claim 12, a corresponding reasoning as given earlier in this section with respect to claim 7 applies, mutatis mutandis, to the subject matter of claim 12; therefore, claim 12 is rejected, for similar reasons, under the grounds as set forth for claim 7.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
The reference McKenna et al. (US Pre-Grant Publication No. 20190236695-A1, “Multi-Layer Machine Learning Classifier”) discloses a multi-layer machine learning classifier for risk analysis of different fraud types.
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 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 date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Kevin Bechtel whose telephone number is 571-270-5436. The examiner can normally be reached Monday - Friday, 09:00 - 17:00 ET.
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/Kevin Bechtel/
Primary Examiner, Art Unit 2491
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