Prosecution Insights
Last updated: April 19, 2026
Application No. 18/939,870

Technologies for Efficient Detection of Money Laundering

Non-Final OA §101§102
Filed
Nov 07, 2024
Examiner
OJIAKU, CHIKAODINAKA
Art Unit
3696
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
The PNC Financial Services Group, Inc.
OA Round
1 (Non-Final)
45%
Grant Probability
Moderate
1-2
OA Rounds
3y 3m
To Grant
54%
With Interview

Examiner Intelligence

Grants 45% of resolved cases
45%
Career Allow Rate
207 granted / 456 resolved
-6.6% vs TC avg
Moderate +8% lift
Without
With
+8.2%
Interview Lift
resolved cases with interview
Typical timeline
3y 3m
Avg Prosecution
46 currently pending
Career history
502
Total Applications
across all art units

Statute-Specific Performance

§101
35.1%
-4.9% vs TC avg
§103
31.7%
-8.3% vs TC avg
§102
7.1%
-32.9% vs TC avg
§112
17.0%
-23.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 456 resolved cases

Office Action

§101 §102
DETAILED ACTION Status of the Claims The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . The following is in response to an application dated November 7, 2024. Claims 1-20 are pending. All pending claims are examined. 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 a judicial exception (abstract idea) without significantly more. The claim recites abstract idea of organizing human activities. This judicial exception is not integrated into a practical application and the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Analysis The claims are directed to one or more of the following statutory categories: a process, a machine, a manufacture, and a composition of matter. Claim 10 which is illustrative of the independent claims including claims 1 and 20 and recites: As to claim 10. A method comprising: obtaining, by a compute device, financial account data pertaining to multiple individuals; defining, by the compute device, a coordinate space in which to map the individuals associated with the obtained data, including performing a dimensionality reduction on the obtained data; mapping, by the compute device, each individual according to the coordinate space; defining, by the compute device, one or more centroids in the coordinate space as a function of features of individuals previously flagged as having a defined characteristic; and flagging, by the compute device, each mapped individual that satisfies a distance threshold from a corresponding centroid in the coordinate space or that is within a defined number of closest individuals to the corresponding centroid as having the defined characteristic. The invention as claimed recites an abstract idea of fraud detection which is a method of organizing human activity that is a fundamental economic practice whereby a financial transaction is evaluated for fraud. Besides reciting the abstract idea, the remaining claim limitations recite generic computer components (see App. specification, paras. 0019-0027; Fig. 2). In particular, the claim only recites generic computer components to receive based on predefined instructions (App. Spec.Fig. 2). Therefore, the claim is directed to an abstract idea. The additional elements are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using generic computer components. 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 claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply the abstract idea using generic computer components. Dependent claims 11-19 provide additonal details about how the predefined rules are applied to the to the data being evaluated based on the user defined criteria and do not address the issues raised in the independent claims. For example, dependent claims 11-12 provides additional descriptive details about the transaction data evaluated, and therefore do not amount to a technical improvement or an integration of a practical application. In conclusion, merely “applying” the exception using generic computer components cannot provide an inventive concept. Therefore, claims 1-20 are not patent eligible under 35 USC 101. Claim Rejections - 35 USC § 102 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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. Claim(s) 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Baker, USP Pub. No. 20100145836. As to claim 10, Baker discloses A method comprising: obtaining, by a computer device, financial account data pertaining to multiple individuals (Baker, paras. 0007-0012) defining, by the compute device, a coordinate space in which to map the individuals associated with the obtained data, including performing a dimensionality reduction on the obtained data(Baker, paras. 00017-0023); mapping, by the compute device, each individual according to the coordinate space(Baker, paras. 00017-0023); defining, by the computer device, one or more centroids in the coordinate space as a function of features of individuals previously flagged as having a defined characteristic(Baker, paras. 00017-0023); and flagging, by the computer device, each mapped individual that satisfies a distance threshold from a corresponding centroid in the coordinate space or that is within a defined number of closest individuals to the corresponding centroid as having the defined characteristic (Baker, paras. 00031-0034; 0047-0051); As to claim 11, Baker discloses the method of claim 10, wherein performing a dimensionality reduction on the obtained data comprises performing a principal component analysis to identify features that account for the largest amount of variance between individuals in the obtained data (Baker, Fig. 4, paras.0033-0045) As to claim 12, Baker discloses the method of claim 10, wherein flagging each mapped individual that satisfies a distance threshold from a corresponding centroid comprises flagging each mapped individual satisfying the distance threshold as a suspected money launderer (Baker, paras. 00031-0034; 0047-0051) As to claim 13, Baker discloses The method of claim 10, further comprising standardizing, by the computer device, the obtained data to remove differences in scale by: (i) standardizing the obtained data comprises dividing values represented in the obtained data for each feature by a standard deviation for each feature; and/or (ii) standardizing the obtained data comprises standardizing the data with a correlational matrix (Baker, Figs. 4-6). As to claim 14, Baker discloses the method of claim 10, wherein defining one or more centroids comprises: (i) defining a centroid for each of multiple nodes; (ii) defining a centroid based on an average of multiple individuals previously flagged as having the defined characteristic(Baker, paras. 0045-0052;Figs. 4-6). As to claim 15, Baker discloses the method of claim 10, further comprising performing an analysis to identify an elbow in a curve charted based on a number of clusters versus a percentage of variance accounted for by the clusters (Baker, paras. 0023-0024). As to claim 16, Baker discloses the method of claim 10, wherein flagging each mapped individual that satisfies a distance threshold from a corresponding centroid comprises flagging each mapped individual satisfying a defined Mahalanobis distance from the corresponding centroid(Baker, paras. 0027, 0040-0042; Figs. 2-6). As to claim 17, Baker discloses the method of claim 10, further comprising: obtaining, by the computer device, feedback indicative of an accuracy of the compute device; and storing, by the compute device, the feedback for future identification of individuals having the defined characteristic (Baker, paras. 0027, 0042-0053; Figs. 2-6). As to claim 18, Baker discloses the method of claim 17, wherein obtaining feedback comprises: (i) obtaining feedback indicative of individuals having the defined characteristic that were not flagged by the compute device as having the defined characteristic; and/or (ii) obtaining feedback indicative of individuals that were flagged by the compute device as having the defined characteristic and that were later determined to not actually have the defined characteristic(Baker, paras. 0042-0053; Figs. 2-6). As to claim 19, Baker discloses the method of claim 10, wherein obtaining financial account data comprises obtaining data pertaining to individuals that were previously flagged as suspected money launderers(Baker, paras. 0042-0053; Figs. 4-6).As to claims 1-9 and 20 recite limitations similar to claims 10-19 and are rejected in like manner. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHIKA OJIAKU whose telephone number is (571)270-3608. The examiner can normally be reached Monday - Friday: 8.30 AM -5:00 PM EST. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matthew Gart can be reached at 571 272-3955. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /CHIKAODINAKA OJIAKU/Primary Examiner, Art Unit 3696
Read full office action

Prosecution Timeline

Nov 07, 2024
Application Filed
Nov 01, 2025
Non-Final Rejection — §101, §102 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
45%
Grant Probability
54%
With Interview (+8.2%)
3y 3m
Median Time to Grant
Low
PTA Risk
Based on 456 resolved cases by this examiner. Grant probability derived from career allow rate.

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