Prosecution Insights
Last updated: May 29, 2026
Application No. 18/417,757

SYSTEM AND METHOD FOR REAL-TIME SPOT PRICE VOLATILITY SURFACE PREDICTION

Final Rejection §101
Filed
Jan 19, 2024
Examiner
LIU, CHIA-YI
Art Unit
3692
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Jpmorgan Chase Bank N A
OA Round
2 (Final)
27%
Grant Probability
At Risk
3-4
OA Rounds
2y 3m
Est. Remaining
48%
With Interview

Examiner Intelligence

Grants only 27% of cases
27%
Career Allowance Rate
85 granted / 315 resolved
-25.0% vs TC avg
Strong +21% interview lift
Without
With
+21.1%
Interview Lift
resolved cases with interview
Typical timeline
4y 8m
Avg Prosecution
13 currently pending
Career history
341
Total Applications
across all art units

Statute-Specific Performance

§101
20.8%
-19.2% vs TC avg
§103
68.3%
+28.3% vs TC avg
§102
1.4%
-38.6% vs TC avg
§112
8.2%
-31.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 315 resolved cases

Office Action

§101
Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . DETAILED ACTION This action is in response to the amendment filed 4/14/2026. Applicant has amended claims 1, 8 and 15 and cancelled claims 4, 11 and 18. Accordingly, claims 1-3, 5-10, 12-17 and 19-20 are pending for examination. 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 1-3, 5-10, 12-17 and 19-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1, 8 and 15 recite the abstract idea of “calculating spot sensitivity data of derivative element based on volatility surface deformation data and conduct transaction with respect to the derivative instrument” and plotting strike price and implied volatility using mathematical equation”, which is grouped under “Certain Methods of Organizing Human Activity” such as “fundamental economic principles or practices” (hedging, mitigating risk; managing transactions) and “”mathematical concepts (mathematical formulas or equations; mathematical calculations). (MPEP 2016.04(a)). Specifically, claims 1, 8 and 15 recite “… stores a plurality of historical data and … data corresponding to a derivative instrument”, “…. model with the historical data and the … data corresponding to the derivative instrument for time-series data prediction”, “learning, in response to …., volatility surface deformation data over time corresponding to the derivative instrument”, “calculating spot sensitivity data of the derivative instrument based on the volatility surface deformation data ……model”, “displaying the spot sensitivity data onto ….” and “receiving… to conduct a transaction with respect to the derivative instrument”, “implementing a feedback loop to allow strike-wise dynamic corresponding to the derivative instrument”, “inputting variable length sequences as the input data, wherein at an input layer, a fixed tenor volatility smile, which is a graph resulting from plotting a strike price and implied volatility of a group of options with same underlying asset and expiration date, includes: x = (equation) and xi = (equation) where xi is a vector of features and fij is one of the features”, “sorted by strike form lowest to highest” ,” xi is the features of ith strike (equation)”. Claims 2-3, 5-7, 9-10, 12-14, 16-17 and 19-20 are dependent on claims 1, 8 and 15 and include all the limitations of claims 1, 8 and 15. Therefore, claims 2-3, 5-7, 9-10, 12-14, 16-17 and 19-20 recite the same abstract idea of “calculating spot sensitivity data of derivative element based on volatility surface deformation data and conduct transaction with respect to the derivative instrument” and plotting strike price and implied volatility using mathematical equation”. The limitations recited in the depending claims (For example, the capturing and storing steps and the specific types of service, data and model used) are further details of the abstract idea and not significantly more. As such, the description in claims 1-3, 5-10, 12-17 and 19-20 of calculating spot sensitivity data of derivative element based on volatility surface deformation data and conduct transaction with respect to the derivative instrument” and plotting strike price and implied volatility using mathematical equation is an abstract idea. This judicial exception is not integrated into a practical application because, when analyzed under prong two of step 2A (MPEP 2106.04II), the additional elements of claims 1, 8 and 15 such as “accessing a database”, “receiving user input”, “output”, displaying and receiving via “user interface”, “processor (claims 8 and 15), “memory operatively connected to the processor via communication interface (claim 8), “non-transitory computer readable medium configured to store instructions” (claim 15) represent the use of a computer as a tool to perform an abstract idea and/or does no more than generally link the abstract idea to a particular technological environment or field of use. With respect to the claimed “implementing an artificial intelligence deep learning (model)” and “training the artificial intelligence deep learning (model)”, the claims are directed to the abstract idea of using generic machine learning technique in a particular environment and lack detail regarding how the “implementing” and “training” are performed (MPEP 2106.05(f)(1)). Patents that do no more than claim the application of generic machine learning to new data environments, without disclosing improvements to the machine learning models to be applied, are patent ineligible under 35 U.S.C. 101. The additional elements of claims 2-3, 5-7, 9-10, 12-14, 16-17 and 19-20, such as “implementing an algorithm” and “applying bidirectional gate recurrent unit neural network algorithm” also lack detail regarding how the “implementing” and “applying” are performed (MPEP 2106.05(f)(1)). Therefore, the limitations do not integrate the abstract idea into a practical application as they are no more than “apply it” (MPEP 2106.05(f)(1)). When analyzed under step 2B (MPEP 2106.04II), because the additional elements do no more than represent the use of a computer as a tool to perform an abstract idea and/or does no more than generally link the abstract idea to a particular field of use, they do not provide an improvement to computer functionality, or an improvement to another technology or technical field and, therefore, do not amount to significantly more than the judicial exception itself (MPEP 2106.05(I)(A)(f)&(h)). Hence, claims 1-3, 5-10, 12-17 and 19-20 are not patent eligible. Claims 1-3, 5-10, 12-17 and 19-20 have been searched and reviewed. No prior art has been found that discloses, either expressly or inherently, all of the limitations of the claimed invention. More specifically, the newly added limitations recited in the independent claims 1, 8 and 15, considered as a whole, are not taught by the prior arts found in examiner’s search and STIC search. Therefore, no rejection under 102/103 is made. Related But Not Relied Upon Relevant art cited but not applied: Browne et al. (US 7,440,916 B2), directed to simulating implied volatility surfaces for option pricing. Response to Arguments Applicant's arguments filed 4/14/2026 have been fully considered but they are not persuasive. In response to applicant’s request for confirmation regarding the drawings, it is noted that no objection is made to the drawings as filed and therefore no further action is required at this time. Applicant argues that the claims are statutory under 35 U.S.C. 101 because 1) the claims are directed to specific machine learning-based techniques which is not abstract idea and 2) The combination of inputting sequences, structuring inputs, followed by feedback loop improves the functioning of the model itself and recite inventive concept. The Examiner disagrees. The claims recite the abstract idea of “calculating spot sensitivity data of derivative element based on volatility surface deformation data and conduct transaction with respect to the derivative instrument” and plotting strike price and implied volatility using mathematical equation”, which is grouped under “Certain Methods of Organizing Human Activity” such as “fundamental economic principles or practices” (hedging, mitigating risk; managing transactions) and “”mathematical concepts (mathematical formulas or equations; mathematical calculations). (MPEP 2016.04(a)). The claims merely describe receiving input data, applying generic processing and using a feedback loop, without defining how the feedback is computed, how model parameters are updated or any specific architecture or algorithmic modification. The recitation of “machine learning” or “feedback loop” at a high level of generality does not, by itself, transmit the abstract idea into a patent-eligible practical application. Therefore, applicant’s arguments are not persuasive. Conclusion THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHIA-YI LIU whose telephone number is (571)270-1573. The examiner can normally be reached Mon-Thurs 9-8 pm. 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, RYAN DONLON can be reached at (571) 270-3602. 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. /CHIA-YI LIU/Primary Examiner, Art Unit 3692
Read full office action

Prosecution Timeline

Jan 19, 2024
Application Filed
Jan 23, 2026
Non-Final Rejection mailed — §101
Apr 14, 2026
Response Filed
May 06, 2026
Final Rejection mailed — §101
May 06, 2026
Interview Requested
May 11, 2026
Applicant Interview (Telephonic)
May 11, 2026
Examiner Interview Summary
May 14, 2026
Response after Non-Final Action

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

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Prosecution Projections

3-4
Expected OA Rounds
27%
Grant Probability
48%
With Interview (+21.1%)
4y 8m (~2y 3m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 315 resolved cases by this examiner. Grant probability derived from career allowance rate.

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