System and method for attribute-based transaction categorization
Contents
1. 21901 NOILVZINODZLWO CIAN Lavo 9002 10 10 JAIM LVHL SALNGIMLLY NOILLOWSNVYL 00 amp 0 LNO ONINIG GOO4 ONIL TAN LINO ONINIG GOO4 99894 S d IWNOCOW 6008 10 10 LNAWdINODA SONIHSINYNA ONISNOH SSAYLLVN 2002 1 2 0 200 62 11 8002 12 20 AYVOHLIVAH NATOHLNOS AANA ADVSSVN AYVOHLIVAH AANA ADVSSVI JHY9 IWNOSYAd 800 21 10 YSHLO SNOANVTISOSIN OIGNLS IWAN VHSYVIN 1571 800 12 20 3141 3841 LNNODOV IMS GNVISA01 a NOILOVSNVYL NISVd CNV 1SA0 1 JWVN 5 ddy WALSAS 5 5 JWOH WOO MOTAHSVOYNO Sep 3 2009 Sheet 8 of 8 US 2009 0222364 A1 Patent Application Publication AYOMLAN SCIM MYOMLAN 1904 WIAs 31 J9YJXJLNI SAG 7191140 FOVAYSLNI 08 sna WALSAS 818 SFOVSAYSLNI 51 708 908 LINN 55 20 53115 Vid cm m mD ee eee cee eee eee me emma ci SIINGON PZS NOILYOddY 4 WALSAS 028 3401S SHOW VY 018 508 WOM 808 5 US 2009 0222364 Al SYSTEM AND METH2. action designation according to one implementation 0012 FIG 4 is an attribute based transaction categoriza tion flowchart illustrating an algorithm for associating a trans action designation according to another implementation 0013 FIGS 5 7 are screenshots of example user inter faces for use in an attribute based transaction categorization system according to various implementations of the presently disclosed technology 0014 FIG 8 illustrates a general purpose computer upon which components and functionality of implementations may be implemented DETAILED DESCRIPTION 0015 Attribute based transaction categorization herein after transaction categorization takes much of the user effort out of personal financial management by automatically cat egorizing transactions for a user From the moment the user accesses the transaction categorization system his her effort is focused on understanding their budget reviewing their spending making decisions on how to meet goals and deter mining whether any changes should be made in their behavior manually categorizing each of his her transactions With implementations of the presently disclosed technology users have more time to understand their finances and use the benefits of a corresponding Personal Financial Management PFM application e g budgeting financial analysis and decision making As a result the PFM application accord ingly to the presently disclosed technolog
3. a plurality of processing units commonly referred to as a parallel processing environment The system bus 804 may be any of several types of bus structures including a memory bus or memory controller a peripheral bus a switched fabric point to point connection and a local bus using any ofa variety of bus architectures The system memory 806 includes read only memory ROM 808 and random access memory RAM 810 A basic input output system BIOS 812 containing the basic routines that help to transfer information between elements within the computer system 800 such as during start up is stored in ROM 808 US 2009 0222364 Al cache 814 may be set aside in RAM 810 to provide a high speed memory store for frequently accessed data 0068 A hard disk drive interface 816 may be connected with the system bus 804 to provide read and write access to a data storage device e g a hard disk drive 818 for nonvolatile storage of applications files and data A number of program modules and other data may be stored on the hard disk 818 including an operating system 820 one or more application programs 822 other program modules 824 and data files 826 In an example implementation the hard disk drive 818 may further store a registry of categorization rules and its corre sponding modules The hard disk drive 818 may additionally contain a data store 866 for maintaining the success and failure tables and other database server information descri
4. based transaction categoriza tion flowchart illustrating an algorithm for associating a trans action designation according to one implementation 300 The transaction categorization system first generates a set of des ignation rules relating transaction attributes to a plurality of financial transaction designations 305 The designation rules may be generated by a system administrator based on trans action attributes common to a transaction designation Alter natively the designation rules may be generated by a user and submitted to the system administrator for approval The sys tem administrator may automatically incorporate the user defined designation rules or may utilize an approval and or testing process before incorporating the user defined rules In another implementation the user may manually designate a transaction The system administrator can capture attributes of the manually designated transaction and generate a catego rization rule associating one or more of the transaction attributes with the identified designation 0039 Next the transaction categorization system receives a transaction profile corresponding to a transaction 310 The transaction profile includes transaction attributes including but not limited to payee name transaction description trans action date transaction amount transaction type code account type payment method recurrence period recurrence time demographic information match count and sele
5. designation rules 119 This updating may be accomplished automatically or via a user prompt The retro actively updated designations may be categories payee names or any other designations that a user may make or want a PFM system to make to help organize and analyze the user s financial transactions 0024 In yet another implementation the user 102 may propose new designations and or designation rules 119 asso ciated with the new designations to be included in the trans action categorization system 100 The transaction categori zation system 100 can either automatically incorporate the user s new designation rules 119 and or designations or pro vide a reviewing process to test and approve the user s new designation rules 119 and or designations Further ifthe user 102 merely provides a new designation without a correspond ing designation rule 119 the transaction categorization sys tem 100 can generate designation rules 119 for use with the new designation 0025 FIG 2 illustrates an example transaction categori zation system 200 with multiple users 202 and commercial entities 222 operating over a network 206 in accordance with one implementation of the presently disclosed technology Users 202 interact with the transaction categorization system 200 via a communication network 206 which may be wire line wireless or any combination thereof The users 202 each have a user interface 208 for interfacing with the transaction c
6. network node and typically includes many or all of the elements described above relative to the computer system 800 0074 To connect with a WAN 860 the computer system 800 typically includes a modem 862 for establishing commu nications over the WAN 860 Typically the WAN 860 may be the Internet However in some instances the WAN 860 may be a large private network spread among multiple locations The modem 862 may be a telephone modem a high speed modem e g a digital subscriber line DSL modem a cable modem or similar type of communications device The modem 862 which may be internal or external is connected to the system bus 818 via the network interface 852 In alter nate implementations the modem 862 may be connected via the serial port interface 844 It should be appreciated that the network connections shown are examples and other means of and communications devices for establishing a communica tions link between the computer system and other devices or networks may be used Connection of the computer system 800 with a LAN 854 or WAN 860 allows an intelligent cat egorization application the ability to communicate with an administrator or remote community based budgeting appli cation similarly connected to the LAN 854 or WAN 860 to apply privately developed categorization rules to transactions generated by others in the community 0075 In an example implementation a designation engine transaction formatter rules generat
7. other wise TECHNICAL FIELD 0004 The subject matter discussed herein relates to sys tems and methods for attribute based transaction categoriza tion SUMMARY 0005 Presently disclosed is a system for attribute based transaction categorization hereinafter transaction categori zation that utilizes transaction designation attributes other than or in addition to a payee name e g a merchant name to provide reduced user effort and improved accuracy in the categorization of transactions Further the transaction cat egorization system may retroactively re categorize and or re name previously received and or categorized transactions based on transaction categorizations of subsequently received and or categorized transactions 0006 Transaction categorization collects transaction attributes and uses them to take much of the user effort out of managing user finances by automatically categorizing recog nized transactions More specifically the transaction catego rization system has access to designation rules associating attributes of transactions other than or in addition to payee name with transaction designations such as categories and transaction names The transaction categorization system uses these designation rules to automatically associate desig nations to individual transactions 0007 In one implementation the transaction categoriza tion system may assign match scores based on the number and or type of designatio
8. refers to the name of the entity with whom a user made a transaction Transaction description refers to a description that the user may assign to the transaction at the time the transaction took place e g the contents of the memo field of a paper check 0053 Further non textual transaction attributes e g numeric information may also be used in the scoring includ ing but not limited to transaction date transaction amount transaction type code account type payment method recur rence period and recurrence time Transaction date refers to the date upon which the user made the transaction with the payee Transaction amount refers to the amount of the trans action between the user and the payee Transaction type code refers to a code assigned to a transaction that identifies the nature purpose and or reason of the transaction primarily used for regulatory reporting requirements Account type refers to the user s funding source account for the transaction Example account types include but are not limited to check ing savings money market credit card and loan Payment method refers to the type of payment used for the transaction Example payment methods include but are not limited to Sep 3 2009 cash credit and debit Recurrence period refers to the period in which a transaction recurs For example rent is typically paid monthly and taxes are typically paid yearly Addition ally recurrence time refers to the tim
9. rule based on transaction attributes of the financial transaction and the user defined designation 10 The method of claim 1 further comprising re designating previously designated financial transac tions based on the first designation rule 11 A computer readable storage medium having com puter executable instructions for performing a computer pro cess for categorizing financial transactions the computer pro cess comprising generating a set of designation rules relating transaction attributes to a plurality of financial transaction designa tions receiving first transaction attributes specific to the financial transaction applying a first designation rule to the first transaction attributes to generate a first match score associating a financial transaction designation with the financial transaction based on the first match score 12 The computer readable storage medium of claim 11 the computer process further comprising applying a second designation rule to the first transaction attributes to generate a second match score and wherein the associating operation comprises selecting a first financial transaction designation as the selected financial transaction designation ifthe first match score satisfies a match criterion and selecting a second transaction designation as the selected financial transaction designation if the second match score satisfies the match criterion 13 The computer readable storage mediu
10. system administrator Further still the method may include adding the designation rule to a register of designation rules Further yet the method may include incrementing a match counter counting the number of times the designation rule has matched a transaction Still further the method may include incrementing a selection counter counting the number of times the designation rule has been selected 0045 FIG 4 is an attribute based transaction categoriza tion flowchart illustrating an algorithm for associating a trans action designation according to another implementation Similar to the method of FIG 3 the transaction categorization system first generates a set of designation rules relating trans action attributes to a plurality of financial transaction desig nations 405 Then the transaction categorization system receives a transaction profile corresponding to a transaction 410 0046 The transaction categorization system then imple ments a query operation that determines if there are any applicable designation rules to the transaction profile 415 The transaction categorization system may require a transac tion profile to share a minimum number of transaction attributes with the designation rule to apply the designation tule If there are no applicable designation rules to the trans action profile the system does not associate a transaction designation to the transaction and the method terminates 435 0047 If there are appli
11. 02 11 20 SSANISNA MOAHO 5 11 58109 NOILVZIMODALVO AYODALVO Gav 1 5 Lv Y31714 18002 lt a eee SLYA IV HSVLS 1 SLNNODOV AWOH WOO MOT14HSVOYENO LNO LIGA NNATS9W MOVE AWOOTAM 00S 4 US 2009 0222364 A1 2009 Sheet 6 of 8 3 Sep Patent Application Publication 9 Old 8006 7 20 ONIDVAY SNOANVTTAOSIN OSTV SI WALSAS MAN 335 FOVAMSELNI 900 10 10 LNO ONINIG GOO4 SYOLVYLSININGY JHL 2002 22 20 INO ONINIG GOO4 SLIGNV 9002 10 10 LNAWdINOA SONIHSINYNA ONISNOH 2002 12 70 AYVOHLIVSH 800 12 20 IWNOSUAd 800 11 10 5 1305 900 10 10 YAHLO SNOANVTTISOSIN 900 10 10 YAHLO SNOANVTISOSIN 200 c 0 2 6006 10 10 5 5 200 c 0 200 0 2002 6c 1 IWMANAd dIHSdsdWan ONIL TSN 99893 S d IWNOGOWN S901 ALIAILOV 30071 WALSAS 5445 AWOH WOOD MOTAHSVOENO Sep 3 2009 Sheet 7 of 8 US 2009 0222364 1 Patent Application Publication 2 914 8002 20 ONIDVAY SNOANVTISOSIN TIWMANSd
12. OD FOR ATTRIBUTE BASED TRANSACTION CATEGORIZATION CROSS REFERENCE 0001 This application claims the benefit of U S Provi sional Application No 61 032 578 filed Feb 29 2008 entitled System and Method for Community Based Transaction Cat egorization the content of which is hereby incorporated by reference in its entirety BACKGROUND 0002 A major challenge in helping users get value from Personal Financial Management PFM systems is reducing or overcoming the administrative effort involved in obtaining meaningful financial advice from the PFM system Today s popular PFM applications require extensive user effort to set up the PFM system and continued user effort to ensure day to day user spending is recorded and analyzed accurately 0003 Conventional PFM systems utilizing transaction categorization typically allow the user to manually assign a category to each transaction for budget analysis Some con ventional PFM systems store the categorization that the user associated with a merchant and apply that same categoriza tion to all future transactions with that same merchant Simi larly conventional PFM systems typically allow the user to manually edit a merchant name to be used later for budget analysis Further some conventional PFM systems utilize a database that stores common category and or merchant name associations for known merchants and these systems apply those associations by default unless the user specifies
13. US 20090222364A1 as United States a2 Patent Application Publication Pub No US 2009 0222364 Al McGlynn et al 43 Pub Date Sep 3 2009 54 SYSTEM AND METHOD FOR Publication Classification ATTRIBUTE BASED TRANSACTION 51 CATEGORIZATION G060 40 00 2006 01 75 Inventors Joseph A McGlynn Highlands 200899 Ranch US Conor Keane 52 MOSS CU 705 30 Englewood US 57 ABSTRACT 73 21 22 60 Designation Correspondence Address HENSLEY KIM amp HOLZER LLC 1660 LINCOLN STREET SUITE 3000 DENVER CO 80264 US Assignee Ourcashflow com LLC Denver CO US Appl No 12 352 012 Filed Jan 12 2009 Related U S Application Data Provisional application No 61 032 578 filed on Feb 29 2008 100 Rules N Registry 116 Transactions Report Corrections 127 Designated Transactions Report 125 Presently disclosed is a system for attribute based transaction categorization that utilizes transaction designation attributes other than or in addition to a payee name to provide reduced user effort and improved accuracy in the categorization of transactions Further the system for transaction categoriza tion may retroactively re categorize and or re name previous transactions based on subsequent transaction categorization The transaction categorization system may assign match scores based on the number and or type of designati
14. ategorization server 201 Graphical user interfaces such as those shown in the screenshots of FIGS 5 7 can be presented via user interfaces 208 0026 One or more commercial entities 222 e g banks stores restaurants etc may be in communication with the transaction categorization server 201 Commercial entities 222 may be sources of transaction profiles 223 that can be submitted to the transaction categorization server 201 Users 202 may also submit transaction profiles 223 to the transac US 2009 0222364 Al tion categorization server 201 Transaction profiles 223 include transaction attributes describing a transaction including but not limited to payee name transaction descrip tion transaction date transaction amount transaction type code account type payment method recurrence period recurrence time demographic information match count and select count 0027 The transaction categorization server 201 includes one or more designation engines 210 a transaction formatter 212 anda rules generator 214 The transaction categorization server 201 is in operable communication with a data store such as registry 216 which includes one or more designation rules 219 The transaction formatter 212 formats incoming transaction profiles 223 In one implementation the transac tion formatter 212 derives transaction attributes based on the transaction profiles 223 Example transaction attributes are mentioned above 0028 The des
15. bed above Note that the hard disk drive 818 may be either an internal component or an external component of the computer system 800 as indicated by the hard disk drive 818 straddling the dashed line in FIG 8 In some configurations there may be both an internal and an external hard disk drive 818 0069 The computer system 800 may further include a magnetic disk drive 830 for reading from or writing to a removable magnetic disk 832 tape or other magnetic media The magnetic disk drive 830 may be connected with the system bus 804 via a magnetic drive interface 828 to provide read and write access to the magnetic disk drive 830 initiated by other components or applications within the computer system 800 The magnetic disk drive 830 and the associated computer readable media may be used to provide nonvolatile storage of computer readable instructions data structures program modules and other data for the computer system 800 0070 The computer system 800 may additionally include an optical disk drive 836 for reading from or writing to a removable optical disk 838 such as a CD ROM or other optical media The optical disk drive 836 may be connected with the system bus 804 via an optical drive interface 834 to provide read and write access to the optical disk drive 836 initiated by other components or applications within the com puter system 800 The optical disk drive 830 and the associ ated computer readable optical media may be used to prov
16. cable designation rules they are applied in succession 420 until the transaction categorization system determines that there are no more applicable designa tion rules not yet applied 425 For each designation rule transaction attributes are iterated through and a transaction attribute score is generated for each transaction attribute Further the transaction attribute scores may be weighted The US 2009 0222364 Al resulting transaction attribute scores are combined e g summed averaged to generate the match score for the rule applied to the transaction profile 0048 Once all the applicable designation rules are applied to the transaction profile the resulting match scores are com pared with a match criterion to determine if any of the match scores are sufficient to apply a transaction designation to the transaction 430 If none of the match scores are sufficient the system does not associate a transaction designation to the transaction and the method terminates 435 Otherwise the system associates a transaction designation to the transaction based on the highest of the match scores 440 0049 Implementations of the transaction categorization system include functional modules or engines for carrying out the method steps described herein Implementations of computer readable media have computer executable instruc tions that when executed cause a computer to carry out method steps described herein 0050 Some implementations of
17. ct count The transaction profile may be sent to the transaction categorization system from a commercial entity e g a bank store restaurant etc a user of the transaction categorization system 0040 The transaction categorization system applies a first designation rule to the transaction profile to generate a first match score 315 More specifically applying the first desig nation rule may include generating one or more transaction attribute scores each transaction attribute score being asso ciated with an attribute of the transaction and combining the transaction attribute scores to generate the first match score Generating the first match score may include weighting each of the transaction attribute scores with a weight factor asso ciated with the corresponding attribute and or the degree to which each attribute matches a corresponding field of the first designation rule Further determining the first match score may include finding transaction attributes in the transaction profile that match at least one transaction attribute in the first designation rule Similarly the transaction categorization Sep 3 2009 system may then apply a second designation rule to the trans action profile to generate a second match score 320 0041 Finally the transaction categorization system asso ciates a transaction designation to the transaction based on the first and or second match scores 325 In one implementation there is only one
18. ction date transaction amount transaction type code account type payment method recurrence period recurrence time demographic information match count and select count 0018 In one implementation the server 101 periodically accesses a server associated with the commercial entity 122 the server then downloads the transaction profiles 123 asso ciated with the user 102 from the commercial entity 122 Designation rules 119 stored in a registry 116 are applied to the transaction profiles 123 and the results are compiled in designated transactions report 125 sent to the user 102 Optionally the user 102 may respond with transaction report corrections 127 if the designated transactions report 125 is incomplete or incorrect 0019 The transaction categorization server 101 is in oper able communication with a data store such as a registry 116 which includes one or more designation rules 119 The des ignation rules 119 are associated with designations and con tain one or more transaction attributes that are compared with one or more transaction attributes in the transaction profiles 123 Each designations rule 119 is associated with one des ignation The transaction categorization system 100 can com pute match scores for each combination of transaction profile 123 and designation rule 119 based on the number of trans action attributes that match Ifa designation rule 119 contains multiple transaction attributes application of the
19. ctions without requiring manual user designation Alternatively or in addition a user 202 may be prompted with a number of designations having matching scores according to designation rules 219 The user 202 may be prompted to manually select from the designations having matching scores 0031 According to one such implementation of the pres ently disclosed technology that learns designation strate gies from users 202 financial transactions are formatted for the server 201 by the transaction formatter 212 Keywords and other transaction characteristics are tagged in each transaction profile 223 to create an attribute set for each transaction The next step is for the transaction categorization system 200 is to learn how attribute sets are designated As users 202 manually designate transactions a rules generator 214 learns target designations for transactions with certain attributes This trains the transaction categorization system 200 allowing it to very quickly start to create designation rules 219 0032 As transactions profiles 223 are collected by the server 201 corresponding attribute sets are presented to the Sep 3 2009 rules generator 214 Once a certain level of confidence is reached through this learning process the rules generator 214 will recommend a learned target designation for a transaction and the designation engine 210 will automatically designate the transaction 0033 When a tra
20. designation rule may yield multiple attribute scores The multiple attribute scores may be summed or averaged to yield an overall match score for the transaction 0020 The designation rule that yields the highest match score or a match score that meets a match criteria e g exceeds a threshold will be applied to the transaction and the transaction will be designated according to the designation rule The transaction categorization server 101 repeats this process for all available transactions associated with the user 102 and generates a designated transactions report 125 that is sent to the user 102 Transactions where no designation rule 119 yields a match score that meets the match criteria or multiple designation rules 119 yield equal or nearly equal values are not designated in the designated transactions report 125 and are left for the user 102 to manually designate Alternatively the transaction categorization system 100 may provisionally designate such transactions but flag them for the user 102 to review later The designated transactions report 125 is sent to the user 102 over the network 106 via wireline connection wireless connection or any combination thereof The transaction designations may be categories payee Sep 3 2009 names or any other designations that a user may make or want a PFM system to make to help organize and analyze the user s financial transactions 0021 The user may then review the designated tra
21. designation rule applied and thus only one match score calculated for a transaction The transaction cat egorization system may compare the match score with a match criterion such as a value threshold to determine if the match is sufficient to associate a transaction designation to the transaction 0042 In another implementation where the first and sec ond designation rules are naming rules and the transaction designation is a payee name the transaction categorization system may further replace the contents of the payee field of the transaction profile with the payee name as specified by the first and or second naming rule In another implementation the contents of the payee field may be blank and filled in with the payee name as specified by the first and or second naming rule 0043 Inanother implementation the method may include applying multiple designation rules such as the first desig nation rule and the second designation rule to the transaction to generate multiple match scores The respective match scores are compared to one another to find the best match score The match scores may also be compared with the match criterion to determine if either match is sufficient to associate a transaction designation to the transaction An implementa tion of the method may further include applying the designa tion rules to one or more additional transactions 0044 Further the method may include communicating the designation rule to a
22. disclosed technology The user is presented with a list of expense categories on the left hand side of the computer screen These expense categories may have subcategories sub subcategories and so on The user is also presented with a list of uncategorized transactions with various transaction attributes associated with each transaction Here each trans action is accompanied with a transaction date funding account check number transaction description and amount Further the list of uncategorized transactions may be filtered to a date range or funding account 0062 The list of uncategorized transactions comprises transactions that the transaction categorization system does not yet know how to categorize For example the first time a transaction is input with a MARY KAY description attribute the transaction categorization system may not know how to categorize the transaction Thus the MARY KAY transaction is listed as uncategorized The user may then manually select a category for this MARY KAY transaction This selection may be made by any means of computer input however here the input is made by a drag and drop operation The MARY KAY transaction is dragged from the uncategorized expenses list and dropped in the Personal Care category To assist with this initial classification the transaction cat egorization system may create a categorization rule to group transactions based on common attributes For example
23. e of the week month and year etc in which a transaction recurs For example rent is typically paid at the beginning of each month and taxes are typically paid in April each year 0054 Additionally non transaction attributes may also be used in the scoring including but not limited to demo graphic information match count select count and any other information that may be used to associate transaction desig nations that does not relate to a specific transaction itself Demographic information includes but is not limited to race sex age income disabilities mobility education home own ership employment status and location Match count refers to the number of transactions previously applied to a desig nation rule that meet the requirements of the designation rule Select count refers to the number of matched transac tions previously applied to a designation rule that are actu ally categorized as the designation rule suggests A combina tion of match count and select count is referred to as a confidence score 0055 As discussed above the presently disclosed technol ogy contemplates both static and dynamic designations While categories and transaction names are described with particularly herein any static designation associated with a designation rule may be used to designate a transaction 0056 Further the presently disclosed technology contem plates dynamic designations A dynamic designation is not a fi
24. er ences do not necessarily infer that two elements are directly connected and in fixed relation to each other It is intended that all matter contained in the above description or shown in the accompanying drawings shall be interpreted as illustrative only and not limiting Changes in detail or structure may be made without departing from the basic elements of the pres ently disclosed technology What is claimed is 1 A method of categorizing a financial transaction the method comprising generating a set of designation rules each designation rule relating a plurality of transaction attributes to a financial transaction designation receiving first transaction attributes specific to the financial transaction applying a first designation rule to the first transaction attributes to generate a first match score associating a selected financial transaction designation with the financial transaction if the first match score satisfies a match criterion 2 The method of claim 1 further comprising applying a second designation rule to the first transaction attributes to generate a second match score and wherein the associating operation comprises selecting a first financial transaction designation as the selected financial transaction designation if the first match score satisfies a match criterion and selecting a second transaction designation as the selected financial transaction designation if the second match score satis
25. fies the match criterion 3 The method of claim 1 wherein the first transaction attributes include non textual attributes associated with the financial transaction 4 The method of claim 1 wherein the first transaction attributes include non transaction attributes associated with a user 5 The method of claim 1 wherein the first transaction attributes are selected from a group comprising transaction date transaction amount transaction type code account type payment method recurrence period recurrence time demo graphic information match count and select count 6 The method of claim 1 wherein the first designation rule is a categorization rule and the financial transaction designa tion represents a transaction category 7 The method of claim 1 wherein the first designation rule is a naming rule and the financial transaction designation represents a payee name 8 The method of claim 1 wherein the financial transaction designation indicates a designation function further compris ing Sep 3 2009 executing the designation function to modify contents of a payee field of the financial transaction to generate a revised payee name and replacing the contents of the payee field with the revised payee name 9 The method of claim 1 further comprising receiving a user defined designation for the financial trans action if the first match score does not satisfy the match criterion and generating a second designation
26. ide nonvolatile storage of computer readable instructions data structures program modules and other data for the computer system 800 0071 display device 842 e g a monitor a television or a projector or other type of presentation device may also be connected to the system bus 804 via an interface such as a video adapter 840 or video card Similarly audio devices for example external speakers or a microphone not shown may be connected to the system bus 804 through an audio card or other audio interface not shown 0072 In addition to the monitor 842 the computer system 800 may include other peripheral input and output devices which are often connected to the processor 802 and memory 806 through the serial port interface 844 that is coupled to the system bus 806 Input and output devices may also or alter nately be connected with the system bus 804 by other inter faces for example a universal serial bus USB a parallel port or a FireWire IEEE 894 port A user may enter com mands and information into the computer system 800 through various input devices including for example a keyboard 846 and pointing device 848 for example a mouse Other input devices not shown may include for example a microphone a joystick a game pad a tablet a touch screen device a satellite dish a scanner a facsimile machine and a digital Sep 3 2009 camera and a digital video camera Other output devices may include fo
27. if the uncategorized expenses list contained multiple MARY KAY transactions dragging and dropping one MARY KAY trans action in the Personal Care category may cause all the MARY KAY transactions to automatically move to the Per sonal Care category Alternatively the transaction categori zation system may prompt the user asking if it should classify all MARY KAY as Personal Care The system may move only MARY KAY transactions that are not yet categorized or alternatively the system may retroactively re categorize MARY KAY transactions according to the new system cre ated rule A user can thus very quickly categorize multiple similar transactions not yet learned by the application 0063 Referring now to FIG 6 an administrator interface is shown In the Rules section of the administrator inter face a list of system rules is shown The system rules are listed by description and associated category along with a date created The system rules also show statistics such as SELECT COUNT and MATCH COUNT MATCH COUNT indicates the number of transactions that meet the require ments of the rule SELECT COUNT indicates the number of matched transactions that are actually categorized as the rule suggests The reason that the SELECT COUNT is less than Sep 3 2009 the MATCH COUNT in some transaction descriptions e g LOVELAND SKI AREA and MASSAGE ENVY is due to manual categorization overriding the categorization rule or a
28. ignation if the first match score satisfies a match criterion and selecting a second transaction designation the selected financial transaction designation if the sec ond match score satisfies the match criterion 23 The system for categorizing financial transactions of claim 21 wherein the first transaction attributes include non textual attributes associated with the financial transaction Sep 3 2009 24 The system for categorizing financial transactions of claim 21 wherein the first transaction attributes include non transaction attributes associated with a user 25 The system for categorizing financial transactions of claim 21 wherein the first transaction attributes are selected from a group comprising transaction date transaction amount transaction type code account type payment method recurrence period recurrence time demographic information match count and select count 26 The system for categorizing financial transactions of claim 21 wherein the first designation rule is a categorization rule and the financial transaction designation represents a transaction category 27 The system for categorizing financial transactions of claim 21 wherein the first designation rule is a naming rule and the financial transaction designation represents a payee name 28 The system for categorizing financial transactions of claim 21 wherein the financial transaction designation indi cates a designation function a
29. ignation engine 210 correlates incoming transaction profiles 223 with designation rules 219 In various implementations correlating a transaction profile 223 with a designation rule 219 involves determining the degree to which the associated transaction profile 223 corresponds to the designation rule 219 In one implementation a transaction profile 223 is correlated with a designation rule 219 by cor relating one or more of the transaction attributes with data in the designation rule 219 to yield attribute scores associated with each correlated transaction attribute The attribute scores may be summed or averaged to generate an overall transac tion match score As a result each match score is associated with a specific transaction and one of the designation rules 219 0029 The rules generator 214 generates designation rules 219 based on manual user transaction designation The rules generator 214 monitors manual transaction designations of users to learn user preferred designation rules 219 The rules generator 214 creates designation rules 219 that associ ate transaction attributes with specific transaction designa tions 0030 Some implementations of the transaction categori zation system 200 may be viewed as learning designation strategies from users 202 Further learned strategies can be applied to future transactions of the user 202 who created the strategy Designation strategies can be automatically applied to transa
30. ip tion may be classified using other attributes including but not limited to payee name amount of the transaction and time of month when it is paid to learn categories 0066 Anexample computer system 800 for implementing the matching designating categorizing and naming pro cesses above is depicted in FIG 8 The computer system 800 may be in the form of server computers personal computers PC or other special purpose computers with internal pro cessing and memory components as well as interface compo nents for connection with external input output storage network and other types of peripheral devices Alternatively the computer system 800 may be in the form of any of a notebook or portable computer a tablet PC a handheld media player e g an MP3 player a smart phone device a video gaming device a set top box a workstation a mainframe computer a distributed computer an Internet appliance or other computer devices or combinations thereof Internal components of the computer system in FIG 8 are shown within the dashed line and external components are shown outside of the dashed line Components that may be internal or external are shown straddling the dashed line 0067 The computer system 800 includes a processor 802 and system memory 806 connected by a system bus 804 that also operatively couples various system components There may be one or more processors 802 e g a single central processing unit CPU or
31. ll dangling meta characters e g replaces occurrences of with 97 from the payee name field 0059 The resulting pattern will then consist of one or more tokens Here the resulting pattern is The Chop House 1234 and is composed of 4 tokens Individual tokens in the payee name field are then omitted if they meet certain condi tions For example the function may omit tokens if 1 the token is only 1 character in length 2 the token is one of the US 2009 0222364 Al following AND OR IS OF BY THE THIS THAT TO FROM and or 3 the token consists of only numbers e g 1234 or 1234 0060 The resulting pattern may then join the tokens with a between them to support the technique of using regular expressions regex within a Java Pattern class to determine a match In the above example the resulting pattern that is generated is The Chop House Similarly the cleansing function maybe applied to any transaction attribute filed that contains a string of words As a result when an incoming transaction profile has a payee name that matches a designa tion rule after the payee name cleaning function is applied a weighted score is applied for the payee name attribute field to the overall match score for the designation rule 0061 FIG 5 is a screenshot of an example user interface for use in an attribute based transaction categorization sys tem according to various implementations of the presently
32. m of claim 11 wherein the first transaction attributes include non textual attributes associated with the financial transaction 14 The computer readable storage medium of claim 11 wherein the first transaction attributes include non transac tion attributes associated with a user 15 The computer readable storage medium of claim 11 wherein the first transaction attributes are selected from a group comprising transaction date transaction amount transaction type code account type payment method recur rence period recurrence time demographic information match count and select count 16 The computer readable storage medium of claim 11 wherein the first designation rule is a categorization rule and the financial transaction designation represents a transaction category 17 The computer readable storage medium of claim 11 wherein the first designation rule is a naming rule and the financial transaction designation represents a payee name 18 The computer readable storage medium of claim 11 wherein the financial transaction designation indicates a des ignation function the computer process further comprising executing the designation function to modify contents of a payee field of the financial transaction to generate a revised payee name and US 2009 0222364 Al replacing the contents of the payee field with the revised payee name 19 The computer readable storage medium of claim 11 the computer process further comp
33. n attributes that match rules for associating a designation to a transaction If a match score Sep 3 2009 exceeds a predetermined threshold and or is greater than other match scores i e the best match score the transaction is automatically designated Otherwise the user may manu ally designate the transaction 0008 In another implementation the user may manually generate rules categories and or transaction names for trans action designation Further the user may manually designate transactions and the transaction categorization system can use the manually designated transactions to generate new designation rules Still further the transaction categorization system can retroactively re categorize and or re name previ ous transactions based on new rules generated by the trans action categorization system based on manually designated transactions BRIEF DESCRIPTION OF THE DRAWINGS 0009 FIG 1 illustrates an example attribute based trans action categorization system operating over a network in accordance with one implementation of the presently dis closed technology 0010 FIG 2 illustrates an example attribute based trans action categorization system with multiple users and com mercial entities operating over a network in accordance with one implementation of the presently disclosed technology 0011 FIG 3 is an attribute based transaction categoriza tion flowchart illustrating an algorithm for associating a trans
34. nd wherein the processor fur ther executes the designation function to modify contents of a payee field of the financial transaction to generate a revised payee name and replaces the contents of the payee field with the revised payee name 29 The system for categorizing financial transactions of claim 21 wherein the network server receives a user defined designation for the financial transaction if the first match score does not satisfy the match criterion and the processor further generates a second designation rule based on transaction attributes of the financial transac tion 30 The system for categorizing financial transactions of claim 21 wherein the processor further re designates previ ously designated financial transactions based on the first des ignation rule
35. nother categorization rule with a higher match score over riding the categorization rule with a lower match score Refer ring to the MARY KAY rule the system rule indicates that there is one MATCH COUNT and one SELECT COUNT showing that the user rule created in FIG 5 is the only rule referencing MARY KAY and is applied in only one instance 0064 Further the Administrator may select a specific sys tem rule to view more information In FIG 6 the Adminis trator has selected MARY KAY to view additional informa tion shown in FIG 7 Referring now to FIG 7 the description MARY KAY has been adopted as the rule name The corresponding category Personal Care is also shown along with the description transaction type funding account type a generated field the date created and date the rule was last updated A selection is available for the Administrator to update one or more categorization parameters for the system rule The categorization parameters shown are examples only additional categorization parameters include but are not lim ited to payee name transaction description transaction date transaction amount transaction type code account type pay ment method recurrence period recurrence time demo graphic information match count and select count 0065 After a short learning cycle the system has the con fidence to categorize all MARY KAY transactions as Per sonal Care For example even transactions with no descr
36. nsac tions report 125 and optionally provide transaction report corrections 127 back to the transaction categorization server 101 In one implementation the designated transactions report 125 may not contain all of the user s transactions The user 102 may send the transaction categorization server 101 additional transaction profiles 123 as transaction report cor rections 127 for designation and inclusion in the designated transactions report 125 0022 In another implementation one or more transac tions in the designated transactions report 125 may be lacking designation or mis designated The user 102 may send the transaction categorization server 101 corrected designations for mis designated transactions and or new designations for un designated transactions The transaction categorization system 100 may use the corrected and or new designations to create new designation rules 119 or update existing designa tion rules 119 to correspond with the user s designation pref erences The corrected and or new designations may be cat egories payee names or any other designations that a user may make or want a PFM system to make to help organize and analyze the user s financial transactions 0023 In yet another implementation the transaction cat egorization system 100 may retroactively update previously designated transactions to be consistent with the user s cor rected and or new designations and corresponding corrected and or new
37. nsaction profile 223 is received by the server 201 the transaction attribute set is presented to the designation engine 210 If the designation engine 210 has learned how to designate a transaction profile 223 with this attribute set the designation engine 210 uses the appropriate rule s to designate the transaction If the designation engine 210 does not find a target designation with acceptable confi dence it will present the transaction to the user 202 for manual designation and learning The designation engine 210 may select a narrowed group of designation suggestions for the transaction For example one user 202 may shop SEARS primarily for clothing while another user 202 shops SEARS for power tools In this case the designation engine 210 will suggest both designations to the user 202 and learn which designation to use on future SEARS transactions based on the user s manual designation of the transaction 0034 The operating environments 100 and 200 shown in FIGS 1 and 2 are simplified from actual operating environ ments for case of illustration In an actual networked envi ronment there may be many users 102 202 and or commer cial entities 122 222 In addition the networks 106 206 may be composed of many networks and or sub networks For example the networks 106 206 may represent the Internet which includes numerous sub networks The network con nections between the transaction categorization server 101 201 and the user
38. on attributes that match rules for associating a designation to a transaction Ifa match score exceeds a predetermined thresh old and or is greater than other match scores the transaction is automatically designated Otherwise the user may manu ally designate the transaction Manually designated transac tions may be used by the transaction categorization system to generate new designation rules User 102 Network 106 Commercial Entity 122 Sep 3 2009 Sheet 1 of 8 US 2009 0222364 1 Patent Application Publication ecb COL Jesn 913 SOL YOMEN Hod y peyeubisag Zp Ansibey 00 Sep 3 2009 Sheet 2 of 8 US 2009 0222364 A1 Patent Application Publication 800 1957 ccc Aus ce Jesse old 502 ZZ uonoesuel gZ AnsiBeay N vic AOJEIBUSS cle uoioesuel sany 072 ooz Patent Application Publication Sep 3 2009 Sheet 3 of 8 US 2009 0222364 K 300 Generate designation rules 305 Receive a transaction profile corresponding to a transaction 310 Apply a first designation rule to the transaction profile to generate a first match score 315 Ap
39. or and other mod ules may be embodied by instructions stored in memory 806 and or storage devices 832 or 838 and processed by the pro cessing unit 802 Designation rules transaction profiles des ignated transactions reports transaction report corrections and other data may be stored in memory 806 and or storage devices 832 or 838 as persistent datastores 0076 Although various implementations of presently dis closed technology have been described above with a certain degree of particularity or with reference to one or more individual implementations those skilled in the art could make numerous alterations to the disclosed implementations US 2009 0222364 Al without departing from the spirit or scope of the presently disclosed technology All directional references e g proxi mal distal upper lower upward downward left right lat eral front back top bottom above below vertical horizon tal clockwise and counterclockwise are only used for identification purposes to aid the reader s understanding of the presently disclosed technology and do not create limita tions particularly as to the position orientation or use of the presently disclosed technology Connection references e g attached coupled connected and joined are to be construed broadly and may include intermediate members between a collection of elements and relative movement between ele ments unless otherwise indicated As such connection ref
40. ply a second designation rule to the transaction profile to generate a second match score 320 Associate a transaction designation to the transaction based on the first and or second match scores 325 FIG 3 Patent Application Publication Sep 3 2009 Sheet 4 of 8 US 2009 0222364 Al 400 Generate designation rules 405 Receive a transaction profile corresponding to a transaction 410 Do not associate a transaction designation to the transaction 435 Are there any applicable designation rules to the transaction profile 415 Apply a designation rule to the transaction profile to generate a match score 420 Do any of the match scores meet a match criterion 430 Are there applicable designation rules not yet applied 425 Yes Associate a transaction designation to the transaction based on the highest of the match scores 440 IG 4 US 2009 0222364 A1 2009 Sheet 5 of 8 Sep 3 Patent Application Publication AWOONI 000 00975 3391 AHL NI TWNOSdYAd AHL AO dOL Ll 1 AWOONI ONISNOH 9 oe 00 97 15083 0922 YSAVSAWIL 8002 90 20 5 00 001 AVA 09221 80
41. r example a printer 850 a plotter a photocopier a photo printer a facsimile machine and a press the latter not shown In some implementations several of these input and output devices may be combined into a single device for example a printer scanner fax photocopier It should also be appreciated that other types of computer readable media and associated drives for storing data for example magnetic cas settes or flash memory drives may be accessed by the com puter system 800 via the serial port interface 844 e g USB or similar port interface 0073 The computer system 800 may operate in a net worked environment using logical connections through a net work interface 852 coupled with the system bus 804 to com municate with one or more remote devices The logical connections depicted in FIG 8 include a local area network LAN 854 and a wide area network WAN 860 Such net working environments are commonplace in home networks office networks enterprise wide computer networks and intranets These logical connections may be achieved by a communication device coupled to or integral with the com puter system 800 As depicted in FIG 8 the LAN 854 may use a router 856 or hub either wired or wireless internal or external to connect with remote devices e g a remote com puter 858 similarly connected on the LAN 854 The remote computer 858 may be another personal computer a server a client a peer device or other common
42. rising receiving a user defined designation for the financial trans action if the first match score does not satisfy the match criterion and generating a second designation rule based on transaction attributes of the financial transaction and the user defined designation 20 The computer readable storage medium of claim 11 the computer process further comprising re designating previously designated financial transac tions based on the first designation rule 21 A system for categorizing financial transactions the system comprising one or more storage media that stores a set of designation rules each designation rule relating a plurality of trans action attributes to a financial transaction designation a network interface that receives first transaction attributes specific to the financial transaction a processor that applies a first designation rule to the first transaction attributes to generate a first match score and associates a selected financial transaction designation with the financial transaction if the first match score satisfies a match criterion 22 The system for categorizing financial transactions of claim 21 wherein the processor further applies a second designation rule to the first transaction attributes to generate a second match score and the processor associates the selected financial transaction designation by selecting a first financial transaction designation as the selected financial transaction des
43. s 102 202 and or commercial entities 122 222 may be virtual private networks Generally the connec tions are secure connections using any secure communication protocol known in the art 0035 Using common attributes of transactions such as but not limited to payee name transaction description trans action date transaction amount transaction type code account type payment method recurrence period recurrence time demographic information match count and select count the transaction categorization system 100 200 can quickly learn how to designate transactions for spending analysis The transaction categorization system 100 200 automatically creates designation rules 219 for a user based on the user s initial manual designations as well as utilizing designation rules 219 defined by a system administrator 0036 Statistical categorization and machine learning techniques have been applied to unstructured data categori zation including multivariate regression models Bayesian models decision trees neural networks and symbolic rule learning Most recently Support Vector Machines SVMs for classification have been shown to learn faster and catego rize more accurately than earlier methods Some implemen tations described herein use an adapted version of SVM for providing transaction categorization functionality Experi ments conducted separately by Microsoft and Joachims found that SVM s categorized even the simplest doc
44. the presently disclosed technology utilize a matching algorithm to determine the best fit designation for an individual transaction The algorithm generates a match score for a transaction with respect to each applicable designation rule This process may be performed iteratively through all the designation rules After the trans action has been evaluated against all designation rules the designation rule that generates the best match score is utilized to associate a transaction designation to the transaction In one implementation the best match score must satisfy a match criterion e g exceed a confidence threshold to be considered applicable If the best match score satisfies the match criterion then the transaction will be designated according to the designation rule If the best match score does not satisfy the match criterion then the transaction will remain undesignated 0051 The scoring of a designation rule against the trans action is performed by combining e g summing averaging individual scores on transaction attributes e g textual non textual and non transactional with a configurable weight applied to each attribute The weighting enables specific attributes to contribute more or less to the match score 0052 Example textual transaction attributes that may be used in the scoring include but are not limited to payee name transaction description and any other words that directly describe the transaction Payee name
45. ument representation using individual words delimited by white spaces with no stemming accurately for up to 98 of the documents presented The inventors have seen similar results in initial tests with an implementation of the presently dis closed transaction categorization system Other implementa US 2009 0222364 Al tions do not use an SVM but rather a pattern matching based approach Dumas et al for Microsoft Inductive Learning Algorithms and Representa tions for Text Categorization 1988 Joachims Text categorization with support vector machines Learning with many relevant features In Proceedings 10th European Conference on Machine Learning ECML Springer Verlag 1998 0037 Implementations of a method and system for trans action categorization may use any existing and emerging unstructured data categorization approaches that support tasks as diverse as real time sorting of new reports spam filtering hand writing recognition structured search and image classification These data categorization approaches may be adopted and modified for financial transactions des ignation according to the presently disclosed technology Attribute based designation the assignment of unstructured data and natural language text to one or more predefined designations based on the content is a key component in taking the effort out of PFM administration according to the presently disclosed technology 0038 FIG 3 is an attribute
46. xed designation for a financial transaction but rather a pointer to a way of revising an aspect of a financial transac tion For example a dynamic designation may point to a look up table for modifying an aspect of the transaction In another example a dynamic designation may point to a formula for cleansing the payee field of a financial transaction 0057 An implementation of a dynamic designation func tion checking for a best match using the payee name in a transaction profile is described below This implementation utilizes a pattern generation and matching process rather than an SVM Various parts of the following process are carried out by the modules and engines of the transaction categorization server 201 as shown in FIG 2 0058 In this implementation when a user manually des ignates a transaction a designation rule is created that con tains a payee name cleansing function for the payee name attribute field This function is used for scoring the payee name attribute of the transaction For example an incoming transaction profile may have The Chop House 1234 29856 in the payee name attribute field The payee name cleansing function may be designed to 1 truncate all char acters from the payee name field after the occurrence of 7 2 truncate all characters from the payee name field after the occurrence of lt 3 truncate all characters from the payee name field after the occurrence and or 4 remove a
47. y is more beneficial to the user than a conventional PFM application 0016 Transaction categorization referred to throughout this disclosure contemplates static designations e g the des ignation of financial categories to transactions and designa tion of abbreviated or customized names for transactions with a payee Further transaction designation also con templates dynamic designations designations that alter the characteristics of a transaction attribute For example trun cation of various features of a payee field of a transaction and US 2009 0222364 Al payee field feature look up in a feature database based on transaction attributes Further any other designations that a user may make or want a PFM system to make to help orga nize and analyze the user s financial transactions are contem plated herein 0017 FIG 1 illustrates an example transaction categori zation system 100 operating over a network 106 in accor dance with one implementation of the presently disclosed technology A commercial entity 122 e g banks stores restaurants etc is in communication with and submits trans action profiles 123 associated with a user 102 to a transaction categorization server 101 via a wireline connection wireless connection or any combination thereof Transaction profiles 123 include transaction attributes describing a transaction including but not limited to payee name transaction descrip tion transa
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