DETAILED ACTIONStatus of Claims
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . This action 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.
Independent Claim 20, which is illustrative of the independent claim 1 recites:
20. A method comprising:
obtaining, by a computer device, data indicative of financial transactions associated with one or more customer accounts with a financial institution;
performing, by the computer device, at least one data transformation operation on descriptions of the financial transactions in the obtained data table identification of recurring transactions, including grouping the financial transactions based on a similarity of the descriptions;
combining, by the compute device, determinations from multiple analysis algorithms executed on a group of the financial transactions to obtain a confidence score indicative of whether the group of transactions represents a recurring transaction; and
presenting, by the compute device and in response to a determination that the confidence score indicates that the group of financial transactions represents a recurring transaction, a predicted amount and date for a recurrence of the recurring transaction.
Taking the broadest reasonable interpretation, the invention is directed to a method of organizing human activity that is commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); of determining an account profile based on historical patterns or and activity (see claims obtaining, by a computer device, data indicative of financial transactions associated with one or more customer accounts with a financial institution;
performing, by the computer device, at least one data transformation operation on descriptions of the financial transactions in the obtained data table identification of recurring transactions, including grouping the financial transactions…)
The evaluation of data from a variety of data sources is based on if certain pre-defined conditions are satisfied.
Besides reciting the abstract idea, the remaining claim limitation is the compute device which is described in terms that suggest it comprises generic computer components (see App Spec. para. 0015-0018; see also Fig. 2).
Further, the dependent claims 2-19, recite additional details about the information used in the determination as to whether a transaction is recurring; For example, claims 2-4 describe the segmenting of the data and descriptive details about the data and functional feature of the data. However, the recited abstract idea is not integrated into a practical application. In particular, the invention as claimed recites a generic computer for obtaining, performing, combining and presenting steps of the invention as recited.
App Spec. para. 0015
includes a compute engine 210, an input/output (I/O) subsystem 216, communication circuitry 218, and one or more data storage devices 222. In some embodiments, the transaction prediction compute device 110 may include one or more display devices 224 and/or one or more peripheral devices 226 (e.g., a mouse, a physical keyboard, etc.). In some embodiments, one or more of the illustrative components may be incorporated in, or otherwise form a portion of, another component. The compute engine 210 may be embodied as any type of device or collection of devices capable of performing various compute functions described below. In some embodiments, the compute engine 210 may be embodied as a single device such as an integrated circuit, an embedded system, a field-programmable gate array (FPGA), a system-on-a-chip (SOC), or other integrated system or device. Additionally, in the illustrative embodiment, the compute engine 210 includes or is embodied as a processor 212 and a memory 214. The processor 212 may be embodied as any type of processor capable of performing the functions described herein. For example, the processor 212 may be embodied as a single or multi-core processor(s), a microcontroller, or other processor or processing/controlling circuit. In some embodiments, the processor 212 may be embodied as, include, or be coupled to an FPGA, an application specific integrated circuit (ASIC), reconfigurable hardware or hardware circuitry, or other specialized hardware to facilitate performance of the functions described herein.
These 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. Therefore, the claim is directed to a judicial exception that is an 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 element is a compute device and amount to no more than mere instructions to apply the abstract idea using generic computer components.
In conclusion, merely “applying” the exception using generic computer components cannot provide an inventive concept. Therefore, Independent claims 1 and 20 and the dependent claims 2-19 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 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) 1-3, 7-20 rejected under 35 U.S.C. 102(a)(1) as being anticipated by Borysek, USP Pub. No. 20240161110.
As to claim 1(Currently Amended) Borysek discloses A compute device comprising: circuitry configured to:
obtain data indicative of financial transactions associated with one or more customer accounts with a financial institution; perform at least one data transformation operation on descriptions of the financial transactions in the obtained data to enable identification of recurring transactions, including grouping the financial transactions based on a similarity of the descriptions(Borysek, paras. 0003-0005, 0014-0017, 0040-0045; Figs. 5B-C);
combine determinations from multiple analysis algorithms executed on a group of the financial transactions to obtain a confidence score indicative of whether the group of transactions represents a recurring transaction(Borysek, paras.0014-0017 – see para. 0014- classification of given transaction as a recurring transaction… may involve (a) comparing the score for the given transaction to a score threshold, and (b) based on the comparison, either (i) “determine that the given transaction is classified as a recurring charge if the score meets or exceeds the score threshold or (ii) determine that the given transaction is classified as a non-recurring charge if the score is below the score threshold” see also paras. 0040-0045; Figs. 1, 3, 5B-C);
and present, in response to a determination that the confidence score indicates that the group of financial transactions represents a recurring transaction, a predicted amount and date for a recurrence of the recurring transaction (Borysek, paras. 0003-0005, 0014-0017, 0040-0045; Figs. 5B-C).
As to claim 2, Borysek discloses the compute device of claim 1, wherein to obtain data indicative of financial transactions comprises to exclude data indicative of transactions occurring more than a predefined number of times in a predefined time period(Borysek, para. 0060-0066, Figs. 5B-C).
As to claim 3, Borysek discloses the compute device of claim 2, wherein to exclude data indicative of transactions occurring more than a predefined number of times in a predefined time period comprises to exclude data indicative of transactions occurring more than 52 times in a year (Borysek, paras. 0094-0098, see also paras. 0014-0017, 0040-0045, 0063; Figs. 5B-C; see also paras. 0129-0130).
As to claim 7, Borysek discloses the compute device of claim 1, wherein the circuitry is configured to group financial transactions based additionally on a corresponding customer account associated with each financial transaction, wherein to perform at least one data transformation operation comprises to determine transaction dates from the descriptions (Borysek, paras. 0014-0017, 0040-0045, 0063; Figs. 5B-C; see also paras. 0129-0130).
As to claim 8, Borysek discloses the compute device of claim 7, wherein to determine transaction dates from the descriptions comprises to determine transaction dates by matching the descriptions to a set of predefined date encoding patterns(Borysek, paras. 0014-0017, 0040-0045, 0063; Figs. 5B-C; see also paras. 0129-0130).
As to claim 9, Borysek disclose the compute device of claim 1, wherein to combine determinations from multiple analysis algorithms comprises one or more of:
(i) to determine an identification score, wherein to determine an identification score comprises to determine the identification score as a function of frequency types and frequency methods; (ii) to determine a median days between transactions score; (iii) to determine at least one of an average days between transactions score or a weeks between transactions score; (iv) to determine a standard deviation of days between transactions score; (v) to determine a standard deviation of day of week score; (vi) to determine a standard deviation of day of month score; (vii) to determine a standard deviation of amount score; (viii) to determine a dominant amount score; (ix) to determine an automated clearing house and payroll score (Borysek, paras. 0128; 0147; see also paras. 0014-0016 – comparison to a baseline value).
As to claim 10, Borysek discloses the compute device of claim 1, wherein the circuitry is further configured to compare the confidence score to a threshold score to determine whether the group of financial transactions represent a recurring transaction(Borysek, paras. 0014-0017, 0040-0045, 0063; Figs. 5B-C; see also paras. 0129-0130).
As to claim 11, Borysek discloses the compute device of claim 1, wherein the circuitry is further configured to perform a recurring transaction recognition operation based on feedback from a consumer indicating that transactions previously identified as recurring transactions are not recurring transactions or that transactions previously not identified as recurring transactions are recurring transactions(Borysek, paras. 0014-0017, 0040-0045, 0063; Figs. 5B-C; see also paras. 0129-0130).
As to claim 12, Borysek discloses the compute device of claim 1, wherein the circuitry is further configured to determine a predicted date for the recurrence of the recurring transaction as a function of a dominant interval indicative of a mode of days between financial transactions associated with the recurring transaction(Borysek, paras. 0014-0017, 0040-0045, 0063; Figs. 5B-C; see also paras. 0129-0130).
As to claim 13, Borysek discloses the compute device of claim 12, wherein the circuitry is further configured to determine a predicted date range for the recurrence of the recurring transaction (Borysek, paras. 0014-0017, 0040-0045, 0059-0065; Figs. 5B-C).
As to claim14, Borysek discloses the compute device of claim 1, wherein the circuitry is further configured to determine, in response to a determination that no dominant interval is present, a predicted date for the recurrence of the recurring transaction as a function of a frequency type associated with the recurring transaction(Borysek, paras. 0014-0017, 0040-0045, 0059-0065; Figs. 5B-C).
As to claim 15, Borysek discloses the compute device of claim 14, wherein to determine the predicted date as a function of a frequency type comprises one or more of: (i) to determine the predicted date as a function of a priority ranking of the frequency types; or (ii) to determine the predicted date as a function of the frequency type comprises to determine a predicted date range for the recurrence(Borysek, paras. 0014-0017, 0040-0045, 0059-0065; Figs. 5B-C).
As to claim 16, Borysek discloses the compute device of claim 1, wherein the circuitry is further configured to determine the predicted price of the recurrence of the recurring transaction, wherein to determine the predicted price comprises one or more of: (i) to determine the predicted price as a function of a dominant amount representing an amount that has occurred a threshold number of times within a predefined time period; or (ii) to determine the predicted price as a function of interquartile ranges(Borysek, paras. 0014-0017, 0040-0045, 0063; Figs. 5B-C; see also paras. 0129-0130).
As to claim 17, Borysek discloses the compute device of claim 1, wherein the circuitry is further configured to present a warning based on a current account balance and a predicted amount of recurring transactions for a remainder of a defined time period(Borysek, paras. 0014-0017, 0040-0045, 0059-0065; Figs. 5B-C).
As to claim 18, Borysek discloses the compute device of claim 17, wherein the circuitry is further configured to present a predicted remaining account balance after payment of the predicted amount(Borysek, paras. 0014-0017, 0040-0045, 0059-0065; Figs. 5B-C).
As to claim 19, Borysek discloses the compute device of claim 1, wherein the circuitry is further configured to present a summary of aggregate recurring transactions over a defined time period(Borysek, paras. 0040-0045, 0060-0067; Figs. 5B-C; see also paras. 0129-0130).
As to claim 20, Borysek discloses A method comprising:
obtaining, by a compute device, data indicative of financial transactions associated with one or more customer accounts with a financial institution;
performing, by the compute device, at least one data transformation operation on descriptions of the financial transactions in the obtained data to enable identification of recurring transactions, including grouping the financial transactions based on a similarity of the descriptions; combining, by the compute device, determinations from multiple analysis algorithms executed on a group of the financial transactions to obtain a confidence score indicative of whether the group of transactions represents a recurring transaction(Borysek, paras. 0014-0017, see also paras. 0003-0005, 0040-0045; Figs. 5B-C);
and presenting, by the compute device and in response to a determination that the confidence score indicates that the group of financial transactions represents a recurring transaction, a predicted amount and date for a recurrence of the recurring transaction (Borysek, para. 0092 – “…type of merchant-level feature for the given transaction may take the form of a feature that indicates a distribution and/or concentration of the given merchant's historical transactions of a given type (e.g., card-not-present transactions) from some timeframe in the past (e.g., the past 12 months) with respect to the settlement (or authorization) amounts, authorization dates, and/or authorization times of the historical transactions, which may be predictive of whether or not the given transaction is a recurring charge because merchants that use recurring billing tend to follow certain behavioral patterns as it relates to settlement (or authorization) amounts, authorization dates, and/or authorization times of the historical transactions.”; see also paras, 0010, 0072, 0084-0086)
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 4-6, are rejected under 35 U.S.C. 103 as being unpatentable over Borysek, USP Pub. No. 20240161110 in view of Elder, USP Pub. No. 20220245103
As to claim 4, Borysek does not directly disclose but Elder discloses the compute device of claim 1, wherein to perform at least one data transformation operation comprises one or more of (1) to convert the descriptions to uppercase; and/or to remove noise in the descriptions of the financial transactions (Elder, para. 0020 –“… lookup table may include one instance of each merchant key that is identified in the raw transaction records. Accordingly, the data cleansing platform may perform a data deduplication process to remove duplicate instances of a merchant key such that the lookup table includes no more than one instance of each merchant key”, see also Figs. 1-2, 4; para. 0001).
It would have been obvious to one skilled in the art before the effective filing date to modify the recurring transaction evaluation process of Borysek with the data cleaning mechanism of Elder because it would result in an optimization of the data processing environment and ultimately improve the quality of the data that is outputted.
As to claim 5, Borysek does not directly disclose but Elder discloses
the compute device of claim 4, wherein to remove noise comprises: (i) to remove digit and letter combinations; (ii) to remove one or more symbols; (iii) to remove month abbreviations; (iv) to expand predefined abbreviations into corresponding words; and/or (v) to remove repeated spaces(Elder, para. 0020 –“… lookup table may include one instance of each merchant key that is identified in the raw transaction records. Accordingly, the data cleansing platform may perform a data deduplication process to remove duplicate instances of a merchant key such that the lookup table includes no more than one instance of each merchant key”, see also Abstract, Figs. 1-2, 4; paras. 0001, 0014 – see rationale for combination in claim 4).
As to claim 6. Borysek does not directly disclose but Elder discloses the compute device of claim 1, wherein to perform at least one data transformation operation comprises to preserve or reinsert an alphanumeric sequence that satisfies a repetition threshold.( Elder, para. 0020 – “… the data cleansing platform may then use the merchant keys stored in the lookup table to generate an initial cleansed dataset (e.g., a baseline cleansed dataset) based on the raw transaction records obtained from the transaction data source. For example, the data cleansing platform may determine a merchant key in the lookup table that includes a combination of fields (e.g., name, city, state, zip, country, and MCC) that matches a corresponding set of fields in the raw transaction record, and the data cleansing platform may generate a cleansed transaction record in which the raw transaction record is associated with the merchant key and/or enhancement data associated with the merchant key (e.g., a logo, website, phone number, and/or location, among other examples). For example, in some implementations, the data cleansing platform may perform a data join operation to combine and/or reformat information included in the various fields of the raw transaction records based on merchant information that is associated with the merchant keys stored in the lookup table. In this way, the data cleansing platform may generate a cleansed dataset in which each transaction record is associated with a corresponding merchant key and/or related enhancement data that is formatted in a manner that is easily deciphered by a human and/or structured in such a way to enable data analytics tools to query, analyze, and/or otherwise interact with the cleansed transaction data.”, see also Abstract, Figs. 1-2, 4; para. 0001 – see rationale for combination in claim 4).
Conclusion
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/CHIKAODINAKA OJIAKU/Primary Examiner, Art Unit 3696