# US 11,443,372 B2 · Systems and methods for using social network data to validate a loan guarantee > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,443,372 B2 - Document ID: US11443372B2 - Status: Granted - Kind: B2 - Application number: 16/886,646 - Filed: 2020-05-28 - Published: 2020-09-17 - Granted: 2022-09-13 - Earliest claimed: 2018-05-06 - Assignees: Strong Force TX Portfolio 2018, LLC - Applicants: Strong Force TX Portfolio 2018, LLC - Inventors: Charles Howard Cella - Web page: https://patentgrep.com/patent/US11443372B2 ## CPC - G06Q 40/025 - G06F 9/466: {Transaction processing} - G06F 9/543: {User-generated data transfer, e.g. clipboards, dynamic data exchange [DDE], object linking and embedding [OLE]} - G06F 16/2379: {Updates performed during online database operations; commit processing} - G06F 16/27: Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor - G06K 9/6215 - G06K 9/6218 - G06K 9/6268 - G06N 3/0427 - G06N 3/08: Learning methods - G06N 5/04: Inference or reasoning models - G06N 20/00: Machine learning - G06Q 10/0639: Performance analysis of employees; Performance analysis of enterprise or organisation operations - G06Q 10/10: Office automation; Time management - G06Q 20/405: {Establishing or using transaction specific rules} - G06Q 30/018: Certifying business or products - G06Q 30/0201: Market modelling; Market analysis; Collecting market data - G06Q 30/0206: {Price or cost determination based on market factors} - G06Q 30/0208: Trade or exchange of goods or services in exchange for incentives or rewards - G06Q 30/0215: {Including financial accounts} - G06Q 30/0278: {Product appraisal} - G06Q 40/08: Insurance - G06Q 50/01 - G06Q 50/18: Legal services - G06Q 50/188: {Electronic negotiation} - G06Q 50/26: Government or public services (business processes related to the transportation industry G06Q50/40) - G16Y 10/50: Finance; Insurance - G16Y 40/10: Detection; Monitoring - H04L 9/0637: {Modes of operation, e.g. cipher block chaining [CBC], electronic codebook [ECB] or Galois/counter mode [GCM]} - G06Q 40/04: Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange - G06Q 2220/18: Licensing - 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 - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06K: GRAPHICAL DATA READING (image or video recognition or understanding G06V); PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - G16Y: INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT] - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) ## Abstract Systems and methods for using social network data to validate a loan guarantee are disclosed. An example system may include a social networking input circuit to interpret a loan guarantee parameter; a social network data collection circuit to collect data using a plurality of algorithms that is configured to monitor social network information about an entity involved in a loan in response to the loan guarantee parameter; and a guarantee validation circuit to validate a guarantee for the loan in response to the monitored social network information. ## Claims ### Claim 1 A system, comprising: a set of processors; and a non-transitory computer-readable medium storing a set of instructions that, when executed, cause the set of processors to: interpret, by a social networking input instruction, a loan guarantee parameter; collect data, by a social network data collection instruction, using a plurality of algorithms that is configured to monitor social network information about an entity involved in a loan in response to the loan guarantee parameter; determine whether a guarantee for the loan is validated, by a guarantee validation instruction, in response to the monitored social network information; create a training data set to train a robotic process automation neural network, the training data set comprising feedback data indicating outcomes of success comprising at least one of: verification of covenant defaults, yield outcomes, loan performance outcomes, collateral valuation outcomes, default outcomes, closing rate outcomes, interest rate outcomes, or return-on-investment outcomes; and iteratively self-adjust the determination of whether the guarantee for the loan is validated based on the feedback data of the training data set to configure a data collection and monitoring action based on at least one attribute of the loan. ### Claim 2 (depends on 1) The system of claim 1, wherein: the loan guarantee parameter comprises a financial condition of the entity; and the entity is a guarantor for the loan. ### Claim 3 (depends on 2) The system of claim 2, wherein the guarantee validation instruction further causes the set of processors to determine the financial condition based on at least one attribute among: a publicly stated valuation of the entity, a property owned by the entity as indicated by public records, a valuation of a property owned by the entity, a bankruptcy condition of the entity, a foreclosure status of the entity, a contractual default status of the entity, a regulatory violation status of the entity, a criminal status of the entity, an export controls status of the entity, an embargo status of the entity, a tariff status of the entity, a tax status of the entity, a credit report of the entity, a credit rating of the entity, a web site rating of the entity, a plurality of customer reviews for a product of the entity, a social network rating of the entity, a plurality of credentials of the entity, a plurality of referrals of the entity, a plurality of testimonials for the entity, a plurality of behaviors of the entity, a location of the entity, a jurisdiction of the entity, or a geolocation of the entity. ### Claim 4 (depends on 1) The system of claim 1, wherein: the set of instructions further includes a data collection instruction to cause the set of processors to obtain information about a condition of a collateral for the loan; the collateral comprises at least one item among: a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, or an item of personal property; and the guarantee validation instruction further causes the processors to validate the guarantee of the loan in response to the condition of the collateral for the loan. ### Claim 5 (depends on 1) The system of claim 1, wherein the social networking input instruction further causes the set of processors to enable a workflow by which a human user enters the loan guarantee parameter to establish a social network data collection and monitoring request. ### Claim 6 (depends on 1) The system of claim 1, wherein the set of instructions further includes a smart contract instruction to cause the set of processors to automatically undertake an action related to the loan in response to the validation of the loan. ### Claim 7 (depends on 6) The system of claim 6, wherein: the action related to the loan is in response to the loan guarantee not being validated; and the action comprises at least one action among: a foreclosure action, a lien administration action, an interest-rate adjustment action, a default initiation action, a substitution of collateral, a calling of the loan, or providing an alert to a second entity involved in the loan. ### Claim 8 (depends on 1) The system of claim 1, wherein the training data set comprising further include human user interactions with the social network data collection instruction. ### Claim 9 A method, comprising: interpreting a loan guarantee parameter; collecting data using a plurality of algorithms that is configured to monitor social network information about an entity involved in a loan in response to the loan guarantee parameter; determining whether a guarantee for the loan is validated in response to the monitored social network information; creating a training data set to train a robotic process automation neural network, the training data set comprising feedback data indicating outcomes of success comprising at least one of: verification of covenant defaults, yield outcomes, loan performance outcomes, collateral valuation outcomes, default outcomes, closing rate outcomes, interest rate outcomes, or return-on-investment outcomes; and iteratively self-adjusting the determining whether the guarantee for the loan is validated based on the feedback data of the training data set to configure a data collection and monitoring action based on at least one attribute of the loan. ### Claim 10 (depends on 9) The method of claim 9, further comprising enabling a workflow by which a human user enters the loan guarantee parameter to establish a social network data collection and monitoring request. ### Claim 11 (depends on 9) The method of claim 9, further comprising automatically undertaking an action related to the loan in response to the validation of the loan. ### Claim 12 (depends on 11) The method of claim 11, wherein: the action related to the loan is in response to the loan guarantee not being validated; and the action comprises at least one action among: a foreclosure action, a lien administration action, an interest-rate adjustment action, a default initiation action, a substitution of collateral, or a calling of the loan. ### Claim 13 (depends on 12) The method of claim 12, further comprising determining at least one domain to which a plurality of algorithms will apply. ### Claim 14 (depends on 11) The method of claim 11, wherein: the action related to the loan is in response to the loan guarantee not being validated; and the action comprises providing an alert to a second entity involved in the loan. ### Claim 15 (depends on 9) The method of claim 9, wherein training data set further comprises at least one of outcomes from or human user interactions with a plurality of algorithms. ### Claim 16 An apparatus, comprising: at least one processor; and a non-transitory computer-readable medium storing a set of instructions that, when executed, cause the at least one processor to: interpret, by a social networking input instruction, a loan guarantee parameter; collect data, by a social network data collection instruction, using a plurality of algorithms that is configured to monitor social network information about an entity involved in a loan in response to the loan guarantee parameter; determine whether a guarantee for the loan is validated, by a guarantee validation instruction, in response to the monitored social network information; create a training data set to train a robotic process automation neural network, the training data set comprising feedback data indicating outcomes of success comprising at least one of: verification of covenant defaults, yield outcomes, loan performance outcomes, collateral valuation outcomes, default outcomes, closing rate outcomes, interest rate outcomes, or return-on-investment outcomes; and iteratively self-adjust the determination of whether the guarantee for the loan is validated based on the feedback data of the training data set to configure a data collection and monitoring action based on at least one attribute of the loan. ### Claim 17 (depends on 16) The apparatus of claim 16, wherein: the set of instructions further includes a data collection instruction to cause the at least one processor to obtain information about a condition of a collateral for the loan; the collateral comprises at least one item among: a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, or an item of personal property; and the guarantee validation instruction further causes the at least one processor to validate the guarantee of the loan in response to the condition of the collateral for the loan. ### Claim 18 (depends on 16) The apparatus of claim 16, wherein: the loan guarantee parameter comprises a financial condition of a guarantor of the loan; and the guarantee validation instruction further causes the at least one processor to determine the financial condition of the guarantor of the loan based on at least one attribute among: a publicly stated valuation of an entity, a set of property owned by the entity as indicated by public records, a valuation of a set of property owned by the entity, a bankruptcy condition of the entity, a foreclosure status of the entity, a contractual default status of the entity, a regulatory violation status of the entity, a criminal status of an entity, an export controls status of the entity, an embargo status of the entity, a tariff status of the entity, a tax status of the entity, a credit report of the entity, a credit rating of the entity, a website rating of the entity, a set of customer reviews for a product of the entity, a social network rating of the entity, a set of credentials of the entity, a set of referrals of the entity, a set of testimonials for the entity, a set of behavior of the entity, a location of the entity, or a geolocation of the entity. ### Claim 19 (depends on 16) The apparatus of claim 16, wherein the loan comprises at least one loan type among: an auto loan, an inventory loan, a capital equipment loan, a bond for performance, a capital improvement loan, a building loan, a loan backed by an account receivable, an invoice finance arrangement, a factoring arrangement, a pay day loan, a refund anticipation loan, a student loan, a syndicated loan, a title loan, a home loan, a venture debt loan, a loan of intellectual property, a loan of a contractual claim, a working capital loan, a small business loan, a farm loan, a municipal bond, or a subsidized loan. ### Claim 20 (depends on 16) The apparatus of claim 16, wherein the social networking input instruction further causes the at least one processor to enable a workflow by which a human user enters the loan guarantee parameter to establish a social network data collection and monitoring request.