US20120330819A1 - System and method for locating and accessing account data - Google Patents

System and method for locating and accessing account data Download PDF

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Publication number
US20120330819A1
US20120330819A1 US13/213,975 US201113213975A US2012330819A1 US 20120330819 A1 US20120330819 A1 US 20120330819A1 US 201113213975 A US201113213975 A US 201113213975A US 2012330819 A1 US2012330819 A1 US 2012330819A1
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United States
Prior art keywords
account
data
accounts
database
benefits
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US13/213,975
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English (en)
Inventor
Laura Weinflash
Dawn Melvin
Tom McLaughlin
Janis E. Simm
Christopher E. Swecker
Lucius L. Lockwood
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Early Warning Services LLC
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Early Warning Services LLC
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Application filed by Early Warning Services LLC filed Critical Early Warning Services LLC
Priority to US13/213,975 priority Critical patent/US20120330819A1/en
Assigned to EARLY WARNING SERVICES, LLC reassignment EARLY WARNING SERVICES, LLC ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: MCLAUGHLIN, TOM, LOCKWOOD, LUCIUS L., MELVIN, Dawn, SIMM, JANIS E., SWECKER, Christopher E., WEINFLASH, LAURA
Priority to CA2840182A priority patent/CA2840182A1/fr
Priority to PCT/US2012/043380 priority patent/WO2012177786A1/fr
Publication of US20120330819A1 publication Critical patent/US20120330819A1/en
Priority to US14/959,881 priority patent/US20160086263A1/en
Priority to US14/970,212 priority patent/US10607284B2/en
Priority to US15/069,186 priority patent/US10504174B2/en
Abandoned legal-status Critical Current

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/02—Banking, e.g. interest calculation or account maintenance

Definitions

  • Account balance and other information for accounts held by an account owner are often needed by third parties for various reasons. For example, when applying for a mortgage, an applicant is typically required to provide information on all of the applicant's accounts to ensure there is sufficient cash attributable to the applicant (e.g., to use as a down payment). As another example, when applying for government benefits, such as supplemental security income (SSI) or other cash or services programs, a beneficiary's accounts must be located to ensure available assets have not been illegally transferred or do not otherwise exceed any qualification amount limits.
  • SSI supplemental security income
  • verifying account balances may involve sending written requests to a number of different institutions, and each institution conducting a manual look-up for each specified account. Further, the applicant may not have complete account numbers or may not remember or provide information on all accounts.
  • the applicant may not provide the correct bank name or ID (such as a routing and transit number) to enable convenient and timely verification.
  • the applicant may not provide the correct bank name or ID (such as a routing and transit number) to enable convenient and timely verification.
  • that balance may not be legitimate. That is, an applicant may have received or borrowed funds from another person (such as a relative) to temporarily show an account balance larger that what is actually owned by the account holder, to fraudulently qualify for a mortgage, loan, or government benefit.
  • an applicant may not disclose accounts, or income reflected in those accounts that would result in disqualification under the benefits program, or may have made transfers out of accounts to conceal assets.
  • Embodiments of the present invention provide systems and methods for locating and accessing assets, such as accounts.
  • accounts may include, but are not limited to, deposit accounts such as checking, savings, CDs, money market accounts in the United States, or International accounts.
  • Accounts may also include (i) reward or loyalty accounts providing merchant reward points, such as in the exemplary case of retail sales; (ii) online financial accounts such as PayPal accounts; (iii) online gaming such as Farmville or SecondLife; or (iv) frequent flyer programs or stored value accounts.
  • accounts may include credit or loan accounts, credit card accounts, debit accounts, prepaid accounts, or any account regarding any desired type of financial information.
  • a system and method for locating an account.
  • the system and method provides a database for storing account data for accounts maintained at a plurality of institutions.
  • the account data for each account includes at least a personal identifier for an account holder.
  • a request to locate an account is received, with the request including a submitted personal identifier.
  • the account is located by matching the submitted personal identifier to the personal identifier stored in the database, and at least some of the account data for the located account is retrieved.
  • a system and method for locating and accessing an account of an account holder without having to contact one or more institutions where the account might be maintained.
  • the system and method provides a database populated with account data for a plurality of accounts from a plurality of institutions maintaining the accounts.
  • Account data is initially transferred from each of the institutions.
  • the account data represents a plurality of account characteristics associated with each of the accounts.
  • the account characteristics comprise an account identifier assigned to each account by the maintaining institution, a personal identifier for the account holder that is assigned by an entity independently of the institutions, and a balance of funds in the account.
  • Updated account data is also periodically transferred from each of the institutions.
  • the account data is stored in the database.
  • a personal identifier (such as a social security number) for an account holder may be used to locate and retrieve at least some of the account data.
  • a government or law enforcement agency may provide one or more personal identifier(s) corresponding to an individual or an entity named in a subpoena (or an instrument such as a National Security Letter or Writ of Execution) for financial or accounting records access, and the provided personal identifier(s) is/are used to determine which institutions, if any, have account or financial information for the individual or an entity named in the subpoena. If one or more of such institutions are found to have such account or financial information for the individual or an entity named in the subpoena, the names of the matching institutions are provided to the government or law enforcement agency with sufficient information (account number or identification information, for example) so that the subpoena may be efficiently served on the one or more matching institutions.
  • indicia showing no match found may be returned to the government or law enforcement agency.
  • a preferred embodiment provides the account identification information for subpoenas to government or law enforcement agencies, it is understood by those of skill in the art that a service could be provided to non-government entities or persons to locate bank accounts corresponding to the identified parties. As described more completely below, additional embodiments may perform analysis to provide additional information to the querying agency.
  • FIG. 1 is a block diagram of a system for locating and accessing account information in accordance with embodiments of the invention.
  • FIG. 2 illustrates exemplary data provided to and stored in the database system of FIG. 1 .
  • FIGS. 3-5 are flow diagrams illustrating several processes used within the database system of FIG. 1 , for locating and accessing account data.
  • FIG. 6 is a block diagram of one suitable scoring model and process for use in one embodiment of the invention.
  • FIG. 7 is a flow diagram illustrating a process used within the database system of FIG. 1 , in accordance with an alternative embodiment.
  • FIG. 8 is a block diagram of a computer system upon which various devices, systems, and processes described in conjunction with FIGS. 1-7 may be implemented.
  • Described embodiments of the present invention provide means for enabling assets (such as financial accounts owned by an account holder) to be located and accessed, even when maintained at a number of different institutions.
  • assets such as financial accounts owned by an account holder
  • accounts are located using a personal identifier associated with the account holder, rather than an account number.
  • the personal identifier is a social security number (SSN).
  • a system for locating assets may receive two different types of requests to locate assets (such as financial accounts).
  • One such request may be an asset search request, and the other may be an asset verification request.
  • an asset search request might be used by a government entity to locate accounts of a person applying for welfare benefits or some other form of government assistance.
  • Government programs providing benefits often have criteria that permit applicants/beneficiaries to qualify only as long as their assets (such as checking, savings and other financial accounts) have balances below a specified threshold.
  • a beneficiary must have no more than $2000 in assets in order to qualify for Medicaid nursing home benefits.
  • the systems and methods described herein permit an asset search for any accounts held by the beneficiary in order to confirm that balances in accounts held by the beneficiary are in fact below the required threshold.
  • transaction data in an identified account may be evaluated to determine or verify benefits eligibility.
  • a system and method could additionally provide account data relevant to the risk that a beneficiary is receiving income (e.g., deposited into an account) that would make the beneficiary ineligible for benefits.
  • income e.g., deposited into an account
  • transaction data in an identified account could be evaluated to provide risk scores and/or indicators pertaining to whether there might be employment income deposited to an account that would make the account holder ineligible for receiving or continuing to receive unemployment benefits.
  • Data reflecting the likelihood of employment income could be based on data provided for ACH transactions posted to the account (e.g., ACH data indicating payroll deposits), or for non-ACH deposits (e.g., check deposits), based on the payor name or account, the check amount, or other check deposit information (e.g., by comparing that information to prior employment data provided by the beneficiary or by comparing that information to transaction patterns or history).
  • the periodicity or timing of deposit transactions might be relevant and could be evaluated.
  • An asset verification request might be used by an entity (such as a mortgage company) to verify account balances.
  • a mortgage applicant may state that the applicant has sufficient funds saved in one or more accounts to make a down payment (or sufficient funds saved to supplement income as needed to make mortgage payments).
  • a mortgage company needs to verify that balances in the applicant's accounts are adequate to meet the applicant's financial needs after the mortgage has been granted.
  • Embodiments of the present invention support alternative asset search and verification queries or requests.
  • systems and methods as described herein may be used in various situations where account information (such as balances) may be needed, such as to qualify or comply with certain government programs, to obtain consumer/commercial loans, or to initiate legal or other actions.
  • account information such as balances
  • SNAP Supplemental Nutrition Assistance Program
  • SSI Supplemental Security Income
  • child support requests e.g., confirming financial means or needs
  • Housing Subsidies e.g., Earned Income Tax Credits (EITC)
  • EITC Earned Income Tax Credits
  • corporate audit verifications small business loans, student loans, student financial assistance, credit checks, and delinquent tax collections.
  • Other embodiments may support asset search and verification requests for various kinds of accounts or account information beyond those maintained at financial institutions.
  • government agencies may contribute benefits data, including details relating to those benefits and relating to the beneficiary, such as name, address, social security number (SSN), date of birth, employer (if any), date benefits applied for, type or amount of benefits, date benefits began, agency or agency location, and so forth.
  • benefits data including details relating to those benefits and relating to the beneficiary, such as name, address, social security number (SSN), date of birth, employer (if any), date benefits applied for, type or amount of benefits, date benefits began, agency or agency location, and so forth.
  • SSN social security number
  • systems and methods of the present invention permit account information from a large number of banking and other institutions as well as from government agencies to be stored in a single database system so that accounts across all of those institutions or agencies may be searched or verified with one request. Not only does this eliminate the need for contacting multiple institutions and agencies, but it also permits the data from individual accounts (or multiple accounts) to be analyzed for risk-related factors (e.g., in the case of mortgage applications, factors indicating savings patterns, suspicious deposits, and possible links to known fraudsters/con artists; and in the case of government benefits, factors indicating suspicious transfers to third parties or benefits received across multiple jurisdictions or agencies).
  • risk-related factors e.g., in the case of mortgage applications, factors indicating savings patterns, suspicious deposits, and possible links to known fraudsters/con artists; and in the case of government benefits, factors indicating suspicious transfers to third parties or benefits received across multiple jurisdictions or agencies.
  • search or verification requests may be batched and sent daily.
  • an individual search or verification request can be sent electronically (on-line and in real-time), and an immediate response can be returned by the system.
  • the located account information sent in the response can be immediately reviewed, perhaps in the presence of the applicant (e.g., while a mortgage applicant is in the presence of a mortgage officer), thus permitting the applicant to explain discrepancies and provide further information that can be used to refine subsequent requests, if appropriate.
  • Such an exchange of information in real time may significantly reduce the time and cost of mortgage qualification, cash and services benefits applications and other processes requiring a search or verification of accounts.
  • FIG. 1 there is shown an exemplary system 100 for locating and accessing account information.
  • the account information is stored and processed at a central account database system 110 having a database device 120 for storing account information and an account database management system (DBMS) 130 for managing the data in database 120 (e.g., the DBMS stores, retrieves, arranges, sorts and processes the data in the database).
  • DBMS account database management system
  • the data used to populate the database 120 is obtained from a number of financial institutions 140 .
  • requests to access the account data stored in database system 110 may be received from government agencies 150 (e.g., to establish qualification for benefits), from mortgage companies 160 (e.g., to verify account balances) and from other entities 170 (e.g., needing to locate and access account data for various reasons, such as creditworthiness, ability to supply funds, or debt or asset verification).
  • government agencies 150 e.g., to establish qualification for benefits
  • mortgage companies 160 e.g., to verify account balances
  • other entities 170 e.g., needing to locate and access account data for various reasons, such as creditworthiness, ability to supply funds, or debt or asset verification.
  • the financial institutions 140 maintain financial accounts, and include banks, savings and loan associations, investment firms and similar institutions.
  • the accounts for which data is provided may include checking accounts, savings accounts, certificates of deposit, brokerage accounts, money market accounts, and other financial accounts (in the United States or elsewhere).
  • Accounts may also include (i) reward or loyalty accounts providing merchant reward points, such as in the exemplary case of retail sales; (ii) online financial accounts such as PayPal accounts; (iii) online gaming accounts, such as Farmville or SecondLife accounts; or (iv) frequent flyer programs or stored value accounts.
  • accounts may include credit or loan accounts, credit card accounts, debit accounts, prepaid accounts, or any account regarding any desired type of financial information.
  • financial institutions 140 may also access account data in system 110 (e.g., as part of a loan application) and government agencies 150 , mortgage companies 160 and other entities 170 may contribute account data (e.g., benefits accounts and mortgage accounts).
  • financial institutions 140 may represent any kind of institution or other entity maintaining an account or asset (financial or otherwise)
  • government agencies 150 , mortgage companies 160 and other entities 170 may represent any kind of entity (governmental, commercial or otherwise) wanting to locate and/or verify accounts or assets that are maintained at various institutions.
  • FIG. 2 illustrates exemplary data provided to (and stored in) the database system 110 by each of the financial institutions 140 .
  • the data comprises account data for a bank account, and thus includes the following data fields (collectively designated as 202 in FIG. 2 ):
  • Account Type e.g., checking, savings, certificate of deposit, investment account
  • Account Status (open/present, closed, deceased, non-sufficient funds, etc.)
  • Average Balance (e.g., average balance over the past 30 days)
  • Maturity Date (e.g., maturity date for a certificate of deposit)
  • FIG. 2 shows data for only one account, and in practice there would be many accounts from many institutions stored in database system 110 .
  • the data includes an initial transfer 210 for each of the data fields (current and historical information at the time of the initial transfer), and subsequent periodic transfers 212 - 1 through 212 - n for most of the same data fields (to keep the data updated).
  • the illustrated periodic data transfers 212 - 1 through 212 - n are each transferred and stored daily (Day 1, Day 2, Day 3, etc., up to the current day). Such a frequent updating is generally preferred, although is some embodiments and applications a less frequent updating might be acceptable.
  • the updated data fields are illustrated as including the same data as the initial transfer, other than the RTN, Account Number and Account Type fields, since it is assumed, for purposes of the described embodiment, that these three data fields will remain unchanged over the life of the account.
  • FIG. 2 shows each updated daily transfer of data ( 212 - 1 through 212 - n ) having all fields 202 in database system 110 populated with data (other than RTN, Account Number and Account Type).
  • data other than RTN, Account Number and Account Type.
  • database system 110 may be managed so that only the changed data in a daily transfer will be stored (in such case, especially if updates are daily, many of the data fields illustrated in FIG. 2 would in fact not be populated in order to efficiently mange storage space and minimize unnecessary data processing).
  • This filtering of unnecessary data could be implemented in one embodiment by database system 110 being programmed to review data fields as they are received from the financial institutions 140 and to remove data that has not changed since the day before.
  • the financial institutions 140 may have systems on-site and programmed to remove unchanged data before it is transmitted.
  • the account data could be processed in a number of ways by system 110 , in addition to being available to a requester making an account search or verification request.
  • the data could be processed to provide balance information in various forms (e.g., a single, current 30 day average balance, or average balances over 6 months, over 1 year or longer).
  • the needs of the requester can thus be met by processing data in a way that is useful to the requester (e.g., a governmental entity is likely to need different information than a mortgage company).
  • the data associated with any account can be filtered, processed and stored in a way to provide only the information on the account that is most useful to the requester.
  • the data associated with an account can be analyzed (and, in some cases, compared to data from other, external sources) to provide risk scores or other risk-related data pertinent to the request.
  • the database system 110 may respond to a mortgage company request with not only basic account information (current status, current account balance, and average balance), but also with alerts and flags if critical data has recently changed (new signers, new account holder names, significant changes in balances, etc.). Also, patterns for deposits and withdrawals (e.g., as reflected in daily balances) can indicate if the account holder is a consistently good saver, or has relied on a single or a few large deposits in order to reach the current balance.
  • data stored in the database could also include a risk marker 216 (stored in a “Risk Flag” field as seen in FIG. 2 ) that indicates risk factors have been identified for the account.
  • the risk marker could be as simple as a “yes” or “no,” and in other embodiments could be a code to indicate whether the risk is relevant to specific categories of requesters, such a government benefits program, a mortgage company, a creditor, or some other request category. It should be appreciated that some factors (e.g., recent patterns of transfers out) would be relevant to a request from a government benefits program, and the same factors may have little or no relevance to a mortgage company.
  • risk-related data in addition to the risk marker itself
  • such data could be stored in a separate table of data (to be described later), and would only be accessed if the risk is relevant to the purpose of the request.
  • FIGS. 3 , 4 and 5 illustrate processes for responding to requests received at the database system 110 .
  • a request to the system 110 may have a standard format and include information pertinent to the person (for whom the account data is sought), such as account holder SSN, name, address, and bank name(s) and account numbers (if any).
  • information needed to identify any accounts for the person could be minimal and, in one embodiment, might only be an SSN.
  • the SSN may be the only identifier provided and used to locate accounts.
  • account verification request e.g., by a mortgage company wanting to verify balance information supplied by an applicant
  • account numbers would typically be provided (for redundancy) as identifiers in addition to an SSN, to make sure that any account identified by an applicant is considered in verifying account balances.
  • the system 110 could process and return account information based on a social security number.
  • the requester may only provide a social security number as an identifier, and information can be returned by system 100 based only on that identifier and not relying on account numbers or other data concerning the account holder.
  • a request for an account search (e.g., locating for a government agency any account at any institution belonging to a person that is the subject of the search) is received by system 110 (step 310 ).
  • the system determines if the request is valid (step 312 ).
  • Such a determination could be based on several possible factors, such as whether the requester is authorized (e.g., the requester has, in advance, been properly authorized as an entity or individual), whether the request has been properly formatted (e.g., a personal identifier, such as a provided SSN, has the correct number of digits or is recognized as a valid SSN), and whether the device transmitting the request is recognized (e.g., from previous transactions or has been authorized in advance by the requester). If the request is not valid, the requester is notified (and the request is not processed further). If the request is valid, the system next determines whether there is an account in the database system 110 that matches the provided personal identifier (step 314 ).
  • the requester is notified and the process ends (as indicated in FIG. 3 ).
  • other steps can be taken (point “A” in the drawings) to identify accounts without using a social security number (such steps will be described shortly in conjunction with FIG. 4 ).
  • the system looks for matches with other data (if any) provided by the requester (step 320 ). For example, a name or address provided in the request is compared to the data stored in system 110 for the identified account, and if there is no match the requester is notified and the search may end (at least temporarily). Alternatively, the process could continue, but with the understanding that the account data may not be relevant to the person that is the subject of the request. If the data matches at step 320 , then the data for the identified account is retrieved, step 322 . If risk data is also to be provided (if available and requested, step 324 ), then the risk data is retrieved (step 326 ) and the retrieved data is provided to the requester as part of the response (step 330 ).
  • the system 110 can be programmed to locate accounts using other personal information of the person in question. This is illustrated in FIG. 4 , where the system 100 first looks for other matches of personal information (e.g., names, addresses, phone numbers), and if there is match (step 412 ), the system may also analyze the match to verify that the information is for same account holder (step 414 ). As an example, this last step can be based on the amount of information matched, so that with two or more pieces of personal information being the same (both name and address for an account are the same as the name and address in the request) a match is indicated.
  • personal information e.g., names, addresses, phone numbers
  • the system 100 if there is there is no match, the system 100 notifies the requester and the search ends.
  • the system 100 may also further review any account where a match is made and verified at steps 412 and 414 , identify the personal identifier such as an SSN for that verified account, and then also identify any other accounts in the database (at any institution) having the same personal identifier as the verified account (step 416 ). This process then returns to the process in FIG. 3 , with any retrieved data provided back to the requester.
  • FIG. 5 illustrates a process similar to that of FIG. 3 , but rather than an account search request, this process is used to respond to an account verification request (e.g., from a mortgage company).
  • An account verification request is received by the system 110 (step 510 ) and the system determines if the request is valid (step 512 ). The system then determines if any accounts stored in the system are identified by the provided personal identifier such as an SSN, step 514 . Since many account verification requests will also include account numbers provided by an applicant, the system determines if any accounts are identified by provided account numbers (step 516 ). The accounts that are identified (either at step 514 or step 516 ) are retrieved (step 522 ).
  • the system notifies the requester as to the nature of the matches (step 520 ). If there is no match of any accounts (no match of either the personal identifier or the account number), the requester is so notified and the process may end with that notification at step 520 (as indicated in FIG. 5 ). Alternatively, additional steps can be taken (point “A” in the drawings) to identify accounts (such additional steps are shown in, and were earlier described in conjunction with, FIG. 4 ). If, at step 520 , there has been a match of only one of the personal identifier or account number, the requester is so notified (as to what identifier or information resulted in the match) and the process continues to the earlier described step 522 (account data for the identified account is retrieved).
  • risk data is also to be provided (if available and requested, step 524 )
  • the risk data is retrieved (step 526 ) and the retrieved data is provided to the requester as part of the response (step 530 ).
  • FIGS. 3 , 4 and 5 illustrate the search or verification process ending when no accounts are indentified or found within system 110 (e.g., at steps 314 , 412 , and 520 ), it should be appreciated that other methods could be employed to respond to a search or verification request, in the event of an account not being found within system 110 .
  • the system 110 could be configured to forward those account numbers to the institution(s) where they are maintained (e.g., using an RTN or bank name provided with the request), and then to respond to the requestor with any information supplied directly by the institution.
  • information supplied directly by the financial institution may supplement the account data retrieved from database 120 and, in those cases, both the information from the financial institution and account data retrieved from database may be provided in a response to the requestor (e.g., at steps 330 and 530 ).
  • the methods just described could be accomplished automatically (on a batched basis or in real-time) in response an account number not being found in system 110 or, alternatively, could be accomplished with the assistance of personnel involved in operating system 110 .
  • system 110 could be electronically linked to the systems at various financial institutions 140 and configured to remotely search account databases at those institutions, so that as the system 110 searches its own database 120 it could likewise search (simultaneously or otherwise) the databases of the linked financial institutions and combine any located data in a response to a requester.
  • risk-related data may be generated based on the account data provided to and stored database system 110 .
  • the scoring logic which could be implemented within the database management system 130 or a separate processing system (not shown) within central account database system 110 , may use a statistical or rules-based analysis (other forms of analysis, such as artificial neural networks, could also be used) to develop a score (examples of analysis used by scoring logic 610 will be given shortly).
  • the account data may not be sufficient to generate a score (e.g., the account has recently been opened, or there has been very little or no account activity).
  • the account data may be stored in a hold account queue 612 until sufficient data is available.
  • the account data and resulting risk score may be stored in a scored account queue 614 , which includes a risk score table 620 .
  • the process of FIG. 6 also illustrates that the scoring process may be continuous.
  • the account data is reapplied to the scoring logic 610 .
  • the additional data is also used in association with already scored accounts in scored account queue 614 to make fresh calculations of risk data for those accounts. That is, the scoring logic 610 is periodically re-run using updated account data (along with previous data in the scored account queue 614 ), and the table 620 is updated with new scores as they are generated. Over time, most of the accounts represented in the hold account queue 612 should migrate to the scored account queue 614 . Eventually, most active accounts will have risk scores in table 620 .
  • risk scores 622 in table 620 are illustrated as numerical (from 1 to 100), with “100” representing the highest risk and “1” representing the lowest. Of course other, simpler forms of risk data could be generated, such as only three risk levels (“low,” “medium,” and “high”). Also, risk reasons 624 are illustrated in table 620 . Such reasons (or codes for such reasons) could be based on risk factors described below.
  • the following tables illustrate scoring analysis (exemplary risk factors and corresponding risk impact) that could be used in scoring logic 610 , for both an account search request (involving government benefits) and an asset verification request (involving a mortgage application).
  • the risk scores could be calculated by initially assigning a neutral score (e.g., 50), and then increasing or decreasing the initial score based on the risk impact identified in the tables.
  • individual risk factors could be weighted differently, e.g., depending on desires of the requester or based on experiential data collected by the operator of the system 110 .
  • some risk factors require comparing account data to relevant data in separate, external databases (as an example, such databases might store names, addresses, email addresses, phone numbers and account numbers of suspected fraudsters). The system 110 would access those external databases as necessary in performing various risk analysis steps.
  • Risk Score Analysis Account Search-Government Benefits Factors Risk Impact Transfer In/Out Patterns Frequent deposits and withdrawals - (money flow in and out increased risk (likely attempt to keep of account) balances low) Infrequent transactions - decreased risk Dates of Withdrawals (in Withdrawals within 6 months of begin date - relation to program increased risk (likely attempt to conceal requirements specifying assets) a begin date for balances Withdrawals more than 6 moths prior to to be below program begin date - decreased risk threshold amount) Amount of Withdrawals At least one withdrawal - increased risk (e.g.
  • Risk Score Analysis Mortgage Application Factors Risk Impact Saving Pattern Infrequent deposits during each month (not a likely consistent “saver”) - increased risk Frequent and consistent deposits - decreased risk Added Signer Signer address same as applicant - decreased risk Signer address at zip code distant from applicant - increased risk Name or SSN of new signer matches suspected fraudsters - increased risk No matches with suspected fraudsters - decreased risk Recent deposits Large Amount(s) - increased risk Small amount(s) - decreased risk
  • the system 100 will likely store account information across most (if not all) financial institutions, additional data (not directly related to the account at hand) can be collected to provide additional forms of risk analysis. For example, if account data for an account is accessed and it reveals a large deposit (or a series of recent deposits that total a large amount), all other accounts in the system could be checked to see if a corresponding and identical withdrawal amount (or series of withdrawals) can be matched, thus linking another account (as a source account) to the account at hand. The system 110 could then check external databases to see if the source account is associated with a fraudster.
  • Embodiments of the invention also support other useful ways to tap the extensive and rich source of information maintained in the system 110 .
  • the account data (including the risk scores) maintained in the system 110 may be used to assess creditworthiness. Not only could stored risk data be used in such an assessment, but loan or other credit accounts could be accessed (e.g., using only a SSN) to locate outstanding balances or credit limits (when stored in association with such accounts), and thus determine either the general creditworthiness of a person or entity (e.g., a person applying additional credit), but also verify representations made by an applicant in connection with the applicant's existing accounts.
  • a government or law enforcement agency may provide one or more personal identifier(s) corresponding to an individual or an entity named in a subpoena (or an instrument such as a National Security Letter or Writ of Execution) for financial or accounting records access, and the provided personal identifier(s) is/are used to determine which institutions, if any, have account or financial information for the individual or an entity named in the subpoena.
  • the names of the matching institutions are provided to the government or law enforcement agency with sufficient information (account number or identification information, for example) so that the subpoena may be efficiently served on the one or more matching institutions. If no matching institutions are found, indicia showing no match found may be returned to the government or law enforcement agency. As described more completely below, additional embodiments may perform analysis to provide additional information to the querying agency.
  • the personal identifier for the individual or entity named in the subpoena may comprise any desired identification element, including, but not limited to, an SSN, a personal name, a mailing address, a physical address, the name of a corporate entity, a driver's license number, a prisoner number, an immigration number, a Matricula Consular number, or any other desired indicia.
  • personal identifiers may constitute a plurality of information designed to either narrow or broaden the search criteria depending on the desired result. Requiring more than one match for a plurality of provided identifiers might produce fewer results and would narrow the search. A match for any one of a plurality of provided identifiers might produce more results and would broaden the search.
  • furnishing a plurality of personal identifiers such as an SSN and name and address may further refine the search results and limit false positives, but depending on the amount of information returned, submissions of multiple identifiers, if a multiple match is required, could return too little information to be useful.
  • the submitting agency may specify which of the submitted personal identifiers are required, and which may be optional, or which may be required in combination. For example, the submitting agency may specify that both a last name and an SSN must match the submission.
  • personal identifiers may comprise a list of related information for a suspect individual, for instance, a list of personal identifiers corresponding to known associates of the individual, and accounts of the known associates may be identified (along with the accounts of the suspect individual).
  • additional analysis techniques which may include link analysis or network analysis, account information corresponding to known associates and to others linked to the individual or entity identified in the subpoena may be returned to the submitting agency.
  • FIG. 7 A simplified illustration of one such process is seen in FIG. 7 .
  • the process of FIG. 7 is similar to (and has steps corresponding to those of) of FIG. 3 , but more specifically involves a search request (step 710 ) from a government agency for an individual or entity contemplated as the subject of a subpoena.
  • the system 110 determines whether the request is valid, step 712 , and whether any accounts associated with a personal identifier of the subject (such as a social security number) can be identified, step 714 .
  • a personal identifier of the subject such as a social security number
  • step 720 other account data (e.g., name and address, if any, provided with the request) may be used to provide additional confirmation that the identified account is matched to the person that is the subject of the search. While not illustrated in FIG. 7 , linking and network analysis can optionally be used to identify additional accounts and provide other information that may have some association with the subject of the contemplated subpoena, as will be described in connection with a specific example to follow shortly.
  • account data e.g., name and address, if any, provided with the request
  • linking and network analysis can optionally be used to identify additional accounts and provide other information that may have some association with the subject of the contemplated subpoena, as will be described in connection with a specific example to follow shortly.
  • Account data for any identified account is retrieved at step 722 .
  • risk data associated with an identified account may also be retrieved (step 726 ).
  • risk data may be used to determine the need for quickly executing a subpoena and then seizing an account that has a high risk of being involved in fraudulent activity (and that may be likely to have its balance quickly depleted/transferred by the fraudster/account holder).
  • the retrieved data is provided (step 730 ), and a subpoena is prepared and executed at step 732 by the government agency.
  • the law enforcement agencies may be provided indicia regarding which institutions have accounts related to Vito Corleone with a matching SSN, and optionally, account indentifying information corresponding to accounts for which Vito is a signatory.
  • Vito's last known address was known by the submitting law enforcement agency (123 Genco Way, Long Island N.Y.), and a list of known associates: P. Clemenza, S. Tessio, L. Brasi, D. Tommasino, and T. Hagen.
  • a query could then be submitted to systems of the present invention to find accounts matching his address and any of his known associates, and such accounts may then be scrutinized to determine whether they are associated with Vito Corleone.
  • Those of skill in the relevant arts also realize that other cross-matching information (for example Vito's middle name “Andolini”) might be utilized with or without his SSN, and with or without other identifying information such as known associates.
  • Vito's middle name “Andolini” might be utilized with or without his SSN, and with or without other identifying information such as known associates.
  • Vito Corleone's social or financial transaction history may be analyzed to determine possible accounts that have some association with Vito.
  • Types of ancillary information provided about Vito may include checking account records of any kind (bank statements, cancelled checks, etc.), loan information (loan applications, ledgers, etc.), savings account and securities records (certificates of deposit, investments, etc.), records of any safe deposit boxes at a bank, supporting financial documents (copies of tax returns, credit reports, etc.), current or present addresses associated with an account, hot files, accounts closed for cause, mobile or land line phone numbers associated with Vito or his present or prior addresses, and the like.
  • requests for subpoena/NSL account identification may be made by the requesting agency individually in a real-time, or in a single or grouped batch mode submittal that is executed at a predetermined time interval (for example, overnight). Additionally, further analysis could produce information that may be provided to the requesting government or law enforcement agency regarding identity information for other individual signatories on joint accounts that correspond to the individual or entity named in the subpoena; prior transactions indicating financial fraud related to the individual or entity named in the subpoena, and through network analysis, identifications of or risk indicia regarding any potential fraud rings associated with the individual or entity that is named in the subpoena.
  • additional related investigatory leads may be provided to the government or law enforcement agency as a result of social or transactional associations with other entities.
  • the requesting agency or an entity, broker, or processor acting on the agency's behalf
  • the requesting entity/broker/processor may process the response on the institution's behalf directly to the law enforcement agency.
  • the requesting government agency may specify to a processor/broker the relevant laws, statutes, rules, or orders under which it has acting authority to submit the subpoena/NSL, and the processor/broker pursues obtaining the information for the agency on its behalf.
  • the processor/broker may utilize the specified listing of laws, statutes, rules or orders furnished by the government agency to tailor the information request to one or more institutions that have been determined to possess information about the subject of the subpoena/NSL, and may optionally filter or redact any information that is received from the relevant institutions that is not permitted to be provided under a legal framework of identified statutes, laws, or rules.
  • FIG. 8 is a block diagram illustrating an exemplary computer system upon which embodiments of the present invention may be implemented.
  • This example illustrates a computer system 800 such as may be used, in whole, in part, or with various modifications, to provide the functions of the central database system 110 , including the DBMS 130 and the scoring logic 610 , as well as other components and functions of the invention described herein.
  • the computer system 800 is shown comprising hardware elements that may be electrically coupled via a bus 890 .
  • the hardware elements may include one or more central processing units 810 , one or more input devices 820 (e.g., a mouse, a keyboard, etc.), and one or more output devices 830 (e.g., a display device, a printer, etc.).
  • the computer system 800 may also include one or more storage devices 840 , representing remote, local, fixed, and/or removable storage devices and storage media for temporarily and/or more permanently containing computer-readable information, and one or more storage media reader(s) 850 for accessing the storage device(s) 840 .
  • storage device(s) 840 may be disk drives, optical storage devices, solid-state storage device such as a random access memory (“RAM”) and/or a read-only memory (“ROM”), which can be programmable, flash-updateable or the like.
  • RAM random access memory
  • ROM read-only memory
  • the computer system 800 may additionally include a communications system 860 (e.g., a modem, a network card—wireless or wired, an infra-red communication device, a BluetoothTM device, a near field communications (NFC) device, a cellular communication device, etc.)
  • the communications system 860 may permit data to be exchanged with a network, system, computer, mobile device and/or other component as described earlier.
  • the system 800 also includes working memory 880 , which may include RAM and ROM devices as described above.
  • the computer system 800 may also include a processing acceleration unit 870 , which can include a digital signal processor, a special-purpose processor and/or the like.
  • the computer system 800 may also comprise software elements, shown as being located within a working memory 880 , including an operating system 884 and/or other code 888 .
  • Software code 888 may be used for implementing functions of various elements of the architecture as described herein.
  • software stored on and/or executed by a computer system, such as system 800 can be used in implementing the processes seen in FIGS. 3-7 .
  • a computer system 800 may have numerous variations from that described above. For example, customized hardware might also be used and/or particular elements might be implemented in hardware, software (including portable software, such as applets), or both. Furthermore, there may be connection to other computing devices such as network input/output and data acquisition devices (not shown).
  • the central account database system 110 system may be implemented by a single system having one or more storage device and processing elements.
  • the central account database system 110 system may be implemented by plural systems, with their respective functions distributed across different systems either in one location or across a plurality of linked locations.

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US13/213,975 US20120330819A1 (en) 2011-06-21 2011-08-19 System and method for locating and accessing account data
CA2840182A CA2840182A1 (fr) 2011-06-21 2012-06-20 Systeme et procede de localisation et d'acces a des donnees de comptes
PCT/US2012/043380 WO2012177786A1 (fr) 2011-06-21 2012-06-20 Système et procédé de localisation et d'accès à des données de comptes
US14/959,881 US20160086263A1 (en) 2011-06-21 2015-12-04 System and method for locating and accessing account data to verify income
US14/970,212 US10607284B2 (en) 2011-06-21 2015-12-15 System and method to search and verify borrower information using banking and investment account data and process to systematically share information with lenders and government sponsored agencies for underwriting and securitization phases of the lending cycle
US15/069,186 US10504174B2 (en) 2011-06-21 2016-03-14 System and method to search and verify borrower information using banking and investment account data and process to systematically share information with lenders and government sponsored agencies for underwriting and securitization phases of the lending cycle

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US8676611B2 (en) 2014-03-18
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US20120330689A1 (en) 2012-12-27

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