DETAILED ACTION
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
2. This action is in response to amendment filed on 1/26/2025, in which claim 1 was amended, and claim 1, 3 – 7, and 9 - 11 was presented for further examination.
3. Claims 1, 3 – 7, and 9 - 11 are now pending in the application.
Response to Arguments
4. Applicant's arguments filed 7/16/2025 have been fully considered but they are not persuasive. (see Remarks below).
Remarks
5. As per claim 1, applicant argues in substance in pages 1 – 4 that Hansen et al (US 10,706,026 B1), Copes (US 2014/0330789 A1), Tiku et al (US 2018/0329940 A1), and Golani et al (US 2011/0099170 A1) does not disclose purging all records of the marked clients from the one or more customer-information databases and related alerts for accounts related to each marked client when open Suspicious Activity Monitoring (SAM) alert for accounts related to client condition has been selected, via a batch process. a computerized-method for reducing data inconsistency when purging inactive client records, in Financial Institute (FI) databases, when the inactive client records exceed retention period, to adhere to General Data Protection Regulation (GDPR), validations of records in the plurality of databases which are related to customer ID having inactive records in a database, by checking related entities in the other databases in the plurality of customer-information databases, based on received conditions via a UI.
Examiner respectfully disagrees.
In response to applicant’s argument, examiner respectfully responds that the combine teaching of Hansen et al (US 10,706,026 B1), Copes (US 2014/0330789 A1), Tiku et al (US 2018/0329940 A1), and Golani et al (US 2011/0099170 A1) fully disclose each and very feature of claim 1 including the features of purging all records of the marked clients from the one or more customer-information databases and related alerts for accounts related to each marked client when open Suspicious Activity Monitoring (SAM) alert for accounts related to client condition has been selected, via a batch process. a computerized-method for reducing data inconsistency when purging inactive client records, in Financial Institute (FI) databases, when the inactive client records exceed retention period, to adhere to General Data Protection Regulation (GDPR), validations of records in the plurality of databases which are related to customer ID having inactive records in a database, by checking related entities in the other databases in the plurality of customer-information databases, based on received conditions via a UI (Copes: para.[0011], para.[0004], and para.[0035] – para.[0036]; Tiku: para.[0019]; Golani: para.[0002] and para.[0040]).
Copes discloses maintenance of record in a database based on a rule associated with an event. The database may include information associated with customer financial account. When an event occurs, the event may be related to updating a data in the database, where updating may include adding or removing records from the database. The event is compared with some rule for maintaining the record of the database, update is performed based on the outcome of the comparison (see para.[0004] and para.[0011]). The management rules consider both internal and external events such as misappropriation of account client loss, etc. The account customer account is analyzed to identify records for deletion. The records are flagged (i.e. marked) and placed in a queue for validation before deletion. The status of each record in the queue are checked and purged based on the outcome (see para.[0035] – para.[0036]).
Tiku disclose various criteria that may be considered before deleting an account, the criteria may include a client closing an account, predetermine duration after client inactivity on the account, etc. (see para.[0019]).
Golani discloses various information included in the customer database and process for deleting records from customer data (see para.[0002] and para.[0040]).
Since Copes discloses records flagging (i.e. marking) and placing on the queue for validation before purging, Tiku discloses some addition criteria for purging a record in a financial database, Golani discloses customer database structure and record deletion. It is obvious to one of ordinary skill in the art to combine the cited references for purpose of deleting records from customer database and checking all other criteria to make sure the reference data are deleted based on inconsistency or security issue in all available databases.
5.2 Thus, the rejection is maintained.
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.
6. Claims 1, 3 – 7, and 9 - 11 are rejected under 35 U.S.C. 103 as being unpatentable over Hansen et al (US 10,706,026 B1), in view of Copes (US 2014/0330789 A1), in view of Tiku et al (US 2018/0329940 A1), and further in view of in view of Golani et al (US 2011/0099170 A1).
As per claim 1, Hansen et al (US 10,706,026 B1) discloses,
A computerized-method for reducing data inconsistency when purging inactive client records, in Financial Institute (FI) databases (col.2 lines 41 – 46; “a system for the selective purging of data ……… data records comprise records with personally identifiable information, personnel records, computer records, financial records” and col.3 lines 1 – 2; “maintaining database integrity of the data”).
when the inactive client records exceed retention period, to adhere to General Data Protection Regulation (GDPR) (col.3 lines 14 – 16; “Data attributes on personnel records may be required to be purged for a number of reasons, including regulations, company policies, or other reasons” and col.4 lines 47 – 49; “compliance with privacy laws can require specific data to be removed within specific time requirements”).
the computerized-method comprising: in a computerized-system comprising: one or more processors, one or more customer-information databases and an application associated thereto (col.1 line 67 and col.2 lines 1 – 3; “an apparatus; a system; a composition of matter; a computer program product embodied on a computer readable storage medium; and/or a processor, such as a processor configured to execute instructions stored”).
said one or more processors are operating a purge-request module (col.2 lines 9 – 13; “a component such as a processor or a memory described as being configured to perform a task may be implemented as a general component that is temporarily configured to perform the task at a given time or a specific component that is manufactured to perform the task”).
said purge-request module comprising: a. receiving a file including one or more customer identifications (ID)s for purge of corresponding inactive client records from the one or more customer-information databases (col.3 lines 37 – 40; “report listing data records from the data audit memory is generated, matching the requestor's criteria. The requestor then selects data attributes to be purged from the data records listed in the report”, col.4 lines 1 – 4; “executing a purge capability comprises receiving a selection of a population that is eligible for having data to be purged and one or more data types to selectively purge”, col.6 lines 42 – 43; “embodiments, data records comprise records with personally identifiable information”, andcol.7 lines 11 – 12; “display is establishing the data colunms to retrieve from a database”).
wherein the one or more customer-information databases are the FI databases (NOTE: col.2 lines 44 – 46; “data records comprise records with personally identifiable information, personnel records, computer records, financial records”).
b. configuring a Graphical User Interface (GUI) of the application to present a list of one or more conditions and to receive a selection of one or more conditions for validation before purging (col.2 lines 33 – 36; “system comprises an interface and a processor. The interface is to receive a selection of one or more data types for selective purging”, col.5 lines 21 – 22; “data that is allowed to be purged from the system can be verified and audited”, col.8 lines 7 – 9; “interface of a system using checkboxes to configure a selective purging of data attributes from data records”, and col.10 lines 39 – 67; “determined whether a user has access to data to be removed …….. determined whether the data is subject of an exception … determined whether relation(s) is/are purgeable …”).
Hansen does not specifically disclose wherein the one or more customer-information databases are the FI databases, checking each received selected condition based on the one or more tables populated with customer details, and wherein when the received selected conditions for validation before purging are met, marking the client for batch process purging and inserting the customer ID to a purge stack, and wherein when the received selected conditions for validation before purging are not met, the client is not marked for the batch process purging, purging all records of the marked client which are in the purge stack from the one or more customer-information databases via a batch process, and e. purging related alerts for accounts related to each marked client in the purge stack, when the condition of open Suspicious Activity Monitoring (SAM) alert for accounts related to client has been selected via the GUI, via the batch process.
However, Copes (US 2014/0330789 A1) in an analogous art discloses,
wherein the one or more customer-information databases are the FI databases (para.[0002]; “financial documents related to customer accounts” and para.[0059]; “the datastore 438 may store information relating to at least one of the user, the user's financial institution account”).
checking each received selected condition based on the one or more tables populated with customer details (para.[0035]; “compares the information relating to the event to one or more rules”).
and wherein when the received selected conditions for validation before purging are met (para.[0035]; “the one or more rules may relate to rules or instructions executable by the system for …….. placing information in the archives related to the event in a queue for purging”).
marking the client for batch process purging and inserting the customer ID to a purge stack (para.[0035]; “the one or more rules may relate to rules or instructions executable by the system ………. for placing information in the archives related to the event in a queue for purging, ……… flagging information in the archives that require specific validation prior to deletion ………analyze the information relating to the event for identifying the customer or for identifying account information of the customer”).
and wherein when the received selected conditions for validation before purging are not met, the client is not marked for the batch process purging (para.[0035]; “the one or more rules may relate to rules or instructions executable by the system for ………. flagging information in the archives that require specific validation prior to deletion” and para.[0036]; “updating the status of the information to place a temporary hold on the information to avoid purging”).
purging all records of the marked client which are in the purge stack from the one or more customer-information databases via a batch process (para.[0035]; “one or more rules may relate to rules or instructions executable by the system …….. for placing information in the archives related to the event in a queue for purging, for removing information related to the event from a queue for purging…….. analyze the information relating to the event for identifying the customer or for identifying account information of the customer”).
and e. purging related alerts for accounts related to each marked client in the purge stack, when the condition of open Suspicious Activity Monitoring (SAM) alert for accounts related to client has been selected via the GUI, via the batch process (para.[0032]; “management rules taking into account external and internal events that occur, such as ……… misappropriation of an account and/or account information, client loss, and the like”, where misappropriation of an account and/or account information is interpreted as “Suspicious Activity Monitoring (SAM)” and para.[0035]; “one or more rules may relate to rules or instructions executable by the system for deleting or purging information related to the event”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate account maintenance and management rule of the system of Copes into selective purging of data of the system of Hansen to allow a financial institution to properly and efficiently maintain financial information.
Neither Copes nor Hansen specifically disclose wherein the one or more conditions are selected from at least one of: (i) no active transactions; the client is part of a Logical Entity (LE) or a Party Group (PGR); (iii) active primary account of the client is associated with an active party; (iv) open Suspicious Activity Monitoring (SAM) alert for accounts related to the client; and (v) open SAM alert for the client.
However, Tiku et al (US 2018/0329940 A1) in an analogous art discloses,
wherein the one or more conditions are selected from at least one of: (i) no active transactions; the client is part of a Logical Entity (LE) or a Party Group (PGR); (iii) active primary account of the client is associated with an active party; (iv) open Suspicious Activity Monitoring (SAM) alert for accounts related to the client; and (v) open SAM alert for the client (para.[0019]; “publishing deletion rules applicable to an SOR 106 in a particular market (Step 1). Accounts may be eligible for deletion in response to a client closing an account, a predetermined duration passing without account activity, a predetermined duration passing since a client closing an account, an individual or entity requesting deletion, or other criteria resulting in data deletion. Accounts may also be eligible for deletion at varying times based in part on account status, for example, if the account was closed in good standing, if payments have been made on the closed account, or if the account is in legal collections ….deletion rules applicable to SOR 106 may comprise a list of accounts to be deleted, a list of deletion rules for identifying accounts for deletion, or other suitable descriptions identifying data to be deleted” and para.[0035]; “SOR may also identify …… PII to be deleted from subscribed SORs, applications, and/or third parties”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate data deletion schedules of the system of Tiku into account maintenance and management rule of the system of Copes to remove customer data that match deletion criteria at regular intervals for reducing the system workload by deleting a set of records at once, thereby preventing the system from repeating the deletion process for records that have already been removed from the system.
Neither Hansen nor Copes nor Tiku specifically disclose c. for each client with a customer ID in the one or more customer IDs, in the received file: (i) retrieving references and links from the one or more customer-information databases to automatically populate one or more tables with customer details based on the customer ID, and f. dropping the automatically populated one or more tables with customer details.
However, Golani et al (US 2011/0099170 A1) in an analogous art discloses,
c. for each client with a customer ID in the one or more customer IDs, in the received file: (i) retrieving references and links from the one or more customer-information databases to automatically populate one or more tables with customer details based on the customer ID (para.[0002]; “manipulate the customer data, authenticate the customer data, add to the customer data, or delete the customer data from a system or database holding the customer data”, para.[0040]; “load process 320 loads the customer data, on a table-wise basis”, para.[0056]; “the load engine may determine which files should be purged from the existing tables”, and para.[0057]; “load engine may also link customer data across existing and merged data, by associating a customer ID”).
and f. dropping the automatically populated one or more tables with customer details (para.[0056]; “load engine may create table-wise purge files, split into separate
partitions. The load engine may partition the purge files in the same manner as the original load files, such that files to be purged may be easily removed from the database. ……….. partitioned purge files 806 may be removed from the existing database(s) partitions 808 and the respective database groups”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate customer data loading of the system of Golani into data deletion schedule of the system of Tiku and account maintenance and management rule of the system of Copes to load necessary compromise customer records across various databases, thereby providing complete customer data requires for verification before purging in the system of Hansen.
As per claim 3, the rejection of claim 1 is incorporated, and further Tiku et al (US 2018/0329940 A1) discloses,
wherein the purge-request module further comprising presenting a progress of each batch process (para.[0016]; “monitor deletion progress and alert compliance officers using compliance reporting and dashboards”).
Therefore, it would have been obvious to one of ordinary skill in the art at the time the invention was filed to incorporate data deletion schedules of the system of Tiku into customer data loading of the system of Golani to understand when records set for deletion begin and complete.
As per claim 4, the rejection of claim 3 is incorporated, and further Tiku et al (US 2018/0329940 A1) discloses,
wherein the purge-request module further comprising generating a statistics report for each completed batch process (para.[0032]; “generate purge files 306 in response to deleting records from the SOR. The purge files 306 may be generated on a per-applicable-rule basis containing unique identifiers of records deleted in response to the applicable rule. Purge files 306 may also be generated on a per-record basis, a per-data-transaction bases, or based on any other suitable dividing criteria. Purge files may identify records purged and/or rules applied in purging records”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate data deletion schedule of the system of Tiku into customer data loading of the system of Golani to identify a set of records that have been deleted and detects a pattern within the deleted records.
As per claim 5, the rejection of claim 4 is incorporated, and further Tiku et al (US 2018/0329940 A1) discloses,
wherein the statistic report is in tabular format or in pie-chart format (para.[0026]; “Deletion history 114 may be a file, table, or other suitable data storage format for retaining records of deleted data”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate data deletion schedule of the system of Tiku into customer data loading of the system of Golani to identify a set of record that have been deleted and detects a pattern within the deleted records.
As per claim 6, the rejection of claim 5 is incorporated, and further Tiku et al (US 2018/0329940 A1) discloses,
wherein the statistics report in tabular format includes: unique sequence number of the batch process, start timestamp, end timestamp, number of records processed and one or more customers purged (para.[0026]; “store a unique identifier associated with deleted records in deletion history 114 (Step 5). For example, the unique identifier may include an account number, account open date, account close data, and/or a deletion date”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate data deletion schedule of the system of Tiku into customer data loading of the system of Golani to identify a set of record that have been deleted and detects a pattern within the deleted records.
As per claim 7, the rejection of claim 5 is incorporated, and further Tiku et al (US 2018/0329940 A1) discloses,
wherein the statistics report in pie-chart format includes: count of related parties, accounts, alerts, number parties purged by the application (para.[0024]; “deletion lists may be published in the form of a deletion file 120 or deletion file 116 identifying records and/or accounts for deletion” and para.[0032]; “Purge files may identify records purged and/or rules applied in purging records”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate data deletion schedule of the system of Tiku into customer data loading of the system of Golani to identify a set of record that have been deleted and detects a pattern within the deleted records.
As per claim 9, the rejection of claim 1 is incorporated, and further Tiku et al (US 2018/0329940 A1) discloses,
wherein the purge-request module further comprising purging related alerts of each marked client, when open SAM alert for the client condition has been selected (para.[0004]; “The record may be deleted from a system of record based on the unique identifier. The system may broadcast a deletion message containing the unique identifier. The deletion message may trigger a purge of data associated with the unique identifier by a subscribing entity such as, for example, an application or third party”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate data deletion schedule of the system of Tiku into customer data loading of the system of Golani to define various criteria for deleting unwanted customer records.
As per claim 10, the rejection of claim 1 is incorporated, and further Tiku et al (US 2018/0329940 A1) discloses,
wherein the one or more customer-information databases include at least one of (i) application database; (ii) landing database; (iii) audit database: and (iv) profile database (para.[0055]; “The phrases consumer, customer, user, account holder, account affiliate, cardmember or the like shall include any person, entity, business, government organization, business, software, hardware, machine associated with a transaction account, buys merchant offerings offered by one or more merchants using the account and/or who is legally designated for performing transactions on the account, regardless of whether a physical card is associated with the account” and para.[0063]; “a plurality of databases. Various databases used herein may include: client data; merchant data; financial institution data; and/or like data useful in the operation of the system”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate data deletion schedule of the system of Tiku into customer data loading of the system of Golani to provide a different type of storage for storing customer records.
As per claim 11, the rejection of claim 1 is incorporated, and further Tiku et al (US 2018/0329940 A1) discloses,
wherein the purging of all marked clients via the batch process further includes marking the retrieved references and links which are related to all marked clients as not part of detection and alert distribution process of associated Anti Money Laundering (AML) system (para.[0016]; “monitor deletion progress and alert compliance officers using compliance reporting and dashboards”, para.[0023]; “Data deletion trigger utility 108 may track exceptions and notify the applications at the appropriate time”, and para.[0041]; “An alert may be generated in response to failure of a periodic audit”).
Therefore, it would have been obvious to one of ordinary skill in the art before the invention was filed to incorporate data deletion schedule of the system of Tiku into customer data loading of the system of Golani to define various criteria for deleting unwanted customer records.
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 AUGUSTINE K. OBISESAN whose telephone number is (571)272-2020. The examiner can normally be reached Monday - Friday 8:30am - 5:00pm.
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/AUGUSTINE K. OBISESAN/
Primary Examiner
Art Unit 2156
10/29/2025